2012 AGU Chapman Conference on Remote Sensing of the ...

SCIENTIFIC PROGRAMSUNDAY, 19 FEBRUARY1500h – 2100h1700h – 1710h1710h – 1750h1800h – 1900hRegistrationWelcome RemarksAndrew C. Revkin, Keynote Speaker The New York TimesWelcome ReceptionMONDAY, 20 FEBRUARY0800h – 0840h0840h – 0920h0920h – 1000h1000h – 1030h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200hOral Session 1: Current Challenges in Terrestrial HydrologyNaupaka BallroomDennis P. Lettenmaier | Planning for the Next Generation of Water CycleMissions INVITEDJames S. Famiglietti | Getting Real About the State of HydrologicalModeling: Priorities for Advancing the Next Generation of Integrated,Data-Assimilating Water Cycle SimulatorsJared Entin | Terrestrial Hydrology in the Context of NASA’s Earth ScienceProgram INVITEDMonday AM Coffee and Networking BreakBreakout Session 1 - Variables Observed by Satellite RemoteSensing: Evapo TranspirationBreakout Session 2 - Variables Observed by Satellite RemoteSensing: Evapo TranspirationBreakout Session 3 - Variables Observed by Satellite RemoteSensing: Soil MoistureBreakout Session 4 - Variables Observed by Satellite RemoteSensing: Soil Moisture5

1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1200h – 1330h1330h – 1410h1410h – 1450h1450h – 1530h1530h – 1600h1600h – 1630hBreakout Session 5 - Variables Observed by Satellite RemoteSensing: SnowBreakout Session 6 - Variables Observed by Satellite RemoteSensing: SnowBreakout Session 7 - Variables Observed by Satellite RemoteSensing: Surface WaterBreakout Session 8 - Variables Observed by Satellite RemoteSensing: Surface WaterBreakout Session 9 - Variables Observed by Satellite RemoteSensing: GroundwaterBreakout Session 10 - Variables Observed by Satellite RemoteSensing: GroundwaterBreakout Session 11 - Variables Observed by Satellite RemoteSensing: PrecipitationBreakout Session 12 - Variables Observed by Satellite RemoteSensing: PrecipitationLunch on Your Own (Monday)Oral Session 2: Estimating Water Storage Components: SurfaceWater, Groundwater, and Ice/SnowPresiding: Douglas E. Alsdorf, Matthew RodellNaupaka BallroomJohn M. Melack | Inland Waters and the Carbon Cycle INVITEDTom G. Farr | Remote Monitoring of Groundwater with Orbital RadarThomas H. Painter | New Era of Understanding Snow Properties fromSpaceborne and Airborne Remote SensingWilfried Brutsaert | Some Indirect Estimates of Changes in HydrologicConditions During the Past Century INVITEDMonday PM Coffee Break6

1600h – 1900hMM-1MM-2MM-3MM-4MM-5MM-6MM-7MM-8MM-9MM-10MM-11MM-12MM-13MM-14MM-15MM-16MM-17Poster Session I - Modeling and Data AssimilationNaupaka V - VIIAlbert Rango | Hydrology with Unmanned Aerial Vehicles (UAVs)Ngwa J. Nde | Geospatial Analysis of Surface Water Pollution fromAutomobile Waste in Ife Central, NigeriaAugusto Getirana | The hydrological modeling and analysis platform(HyMAP): model results and automatic calibration with ENVISATaltimetric dataJason P. Evans | The Impact of Remotely Sensed Dynamic Land SurfaceConditions on the Simulation of Drought in AustraliaShawana P. Johnson | Geospatial Intelligence and Biomass Research forFreshwater, Food, Feed and EnergyQianlai Zhuang | Modeling the Effects of Land Use Change Due to BiofuelDevelopment on Water Dynamics in the United StatesGuangyu Wang | Sustainability and Landuse Pattern Change Detection inthe Min River Watershed, ChinaHualan Rui | NLDAS Views of North American 2011 Extreme EventsSaumitra Mukherjee | Heliophysical and cosmic ray fluctuation changeshydrological cyclePraveen Kumar | Assessing the Impact of 2011 Mississippi RiverMegaflood on the Landscape Using Lidar and AVIRIS ImagingSpectrometer DataTadanobu Nakayama | Coupling with satellite data and eco-hydrologymodel for evaluation of two extremes in continental scalePrasad S. Thenkabail | Water Use and Water Productivity of Key WorldCrops using Hyperion-ASTER, and a Large Collection of in-situ FieldBiological and Spectral DataMartin Kappas | Simulation of water balance components in a watershedlocated in central drainage basin of IranKholoud Kahime | Water Vulnerability, Agriculture and Energy Impacts ofClimate Change in Morocco: A Case Study the Region of AgadirBaozhang Chen | Spatially explicit simulation of hydrologically controlledcarbon-water cycles based on remote sensing in the Po Yang Lakewhatershed, Jiangxi, ChinaThian Y. Gan | Modeling Gross Primary Production Of Deciduous ForestUsing Remotely Sensed Radiation And Ecosystem VariablesJuan P. Guerschman | Modelling water balance in Australia: understandingthe effects of vegetation structure and biophysical dynamics7

MM-18MM-19MM-20MM-21MM-22MM-23MM-24MM-25MM-26MM-271600h – 1900hGM-1GM-2GM-3GM-4GM-5GM-6Calum Baugh | Using field data to assess the effectiveness of adjustedspaceborne derived DEMs for replicating Amazon River floodplain hydrodynamicsDaeun Kim | Spatio-Temporal Patterns of Hydro-Meteorological variablesproduced from SVAT model incorporated with KLDAS in East AsiaJean Bergeron | Snow cover estimation from blended MODIS and AMSR-Edata for improved springflood forecast in Quebec, CanadaPaul C. Milly | Use of Remotely Sensed Data to Advance Global HydrologicModelingSam Benedict | Validation and Application of Remote Sensing Data as partof a Joint Cross-cutting Initiative by the Global Energy and Water CycleExperiment (GEWEX) Hydroclimatology Panel’s (GHP’s) RegionalHydroclimate Projects (RHPs)Gerarda M. Shields | Developing a Prioritization Plan to Assess the Impactof Climate Change Predictions on the Hydraulic Vulnerability of CoastalBridgesJordi Cristobal | Hourly and Daily Regional Scale Validation of a MeteosatSecond Generation Solar Radiation ProductStacy E. Howington | High-Fidelity Numerical Simulation to SupportInterpretation of Electro-optical and Infrared ImageryJohn T. Reager | Effective global soil parameters from GRACE and impacton land surface simulationsJohn D. Bolten | Evaluation of the Middle East and North Africa LandData Assimilation SystemPoster Session I - GroundwaterNaupaka V - VIIHassan Rezaie Boroon | Linking Groundwater Quality and Quantity: AnAssessment of Satellite-Based Groundwater Storage Anomalies FromGRACE Against Ground Measurements of Contaminants in CaliforniaSrinivas V. Bettadpur | Challenges in extraction and interpretation ofGRACE mass flux estimates in near real timeMatthew Rodell | Integrating Data from GRACE and Other ObservingSystems for Hydrological Research and ApplicationsPaul A. Rosen | DESDynI-R Mission Concept Overview and Possible Usesfor Hydrological Sciences and ApplicationsSean C. Swenson | A Gridded GRACE Total Water Storage Dataset forHydrological ApplicationsByron D. Tapley | The Status of the GRACE Mass Flux Measurements8

GM-7GM-8GM-9GM-10GM-11GM-12GM-131600h – 1900hEM-1EM-2EM-3EM-4EM-5EM-6EM-7EM-8Alexandra S. Richey | Quantifying Water Stress Using Total Water Volumesand GRACEIsabella Velicogna | Increase in groundwater storage in discontinuouspermafrost areas in Eurasia and impact on vegetation productivityJean-Paul Boy | Monitoring surface and sub-surface mass changes in Africausing high resolution GRACE mascon solutions and altimetryAmber Jean M. Kuss | Tools for improving groundwater storage estimatesin the Sacramento River Basin: a comparison of remote sensing techniques,a hydrological model, and in-situ groundwater elevationsMaile Sweigart | Drought Characterization of the Las Vegas Valley usingSatellite Observations of Terrestrial Groundwater StorageFrank G. Lemoine | Monitoring Mass Change Using Global HighResolution GRACE Mascon SolutionsMohamed Sultan | An Integrated (remote sensing, GIS, hydrogeology,geochemistry, geophysics, and hydrologic modeling) Approach for a BetterUnderstanding of the Hydrology of the Nubian Aquifer, NE AfricaPoster Session I - EvapotranspirationNaupaka V - VIIGuoyu Qiu | Estimation of evapotranspiration (ET) and its partition intoevaporation (Es) and transpiration (Ec) based on three-temperature modeland MODIS productsSimon J. Hook | Warming Trends in Inland Water Surface Temperaturesfrom Thermal Infrared Satellite ImageryMireia Romaguera | Comparison of remote sensing ET estimates andmodel simulations for retrieving irrigationJoshua B. Fisher | Global Terrestrial Evapotranspiration From RemoteSensing: The History and Progress of Two Mechanistic, Energy-balance,Dedicated ProductsIsabella Mariotto | Application of SEBAL Modified for TopographicReflectance and Roughness to Map the Spatial Distribution of ET in aHeterogeneous AreaLindsay Gilbertson | An Intercomparison of EvapotranspirationEstimation Methods for the Godomey Well Field in Benin, West AfricaDominique Courault | Assessment of modelling uncertainties over aMediterranean agricultural region using evapotranspiration models basedon LANDSAT thermal dataMichael Borsche | Estimation of high Resolution Land Surface Heat FluxDensity Utilizing Geostationary Satellite Data9

EM-9EM-10EM-11EM-12EM-13EM-14EM-15EM-16EM-17EM-18EM-19EM-20EM-21EM-22EM-23EM-24William P. Kustas | Utility of Thermal Remote Sensing for DeterminingEvapotranspirationMartha C. Anderson | A Satellite-Based Drought Product using ThermalRemote Sensing of EvapotranspirationVenkataraman Lakshmi | Climate Studies of intertidal using MODISsurface temperaturesChanyang Sur | Relationship of Remote sensing-based Evapotranspirationand Eco-hydrological Factor; Water Use EfficiencyAndrew N. French | Evapotranspiration Estimation with SimulatedHyspIRI ObservationsGabriel Senay | Evaluating the performance of remote sensing basedevapotranspiration products using flux tower and water balanceapproachesJiao Wang | Remotely Sensed Evapotranspiration Estimation in CentralTexasWilliam Connor | Strategies for validating Vegetation Index EnvironmentalData Records from Visible Infrared Imaging Radiometer Suite using towerreflectance measurementsEric Fetzer | The Water Vapor and Temperature Record from the NASAAtmospheric Infrared SounderJordi Cristobal | Juniper Tree Actual Evapotranspiration Estimation byMeans of Landsat-5 TM Imagery and the TSEB Model in the DoñanaBiological ReserveHatim M. Geli | Evapotranspiration of Natural Vegetation using Landsatand Airborne Remote SensingJordi Cristobal | Tundra Energy Fluxes Retrieval on the Alaskan NorthSlope by Means of Landsat and Modis Imagery and the Tseb Method:Preliminary ResultsRichard G. Allen | Conditioning of NLDAS, NARR and arid weatherstation data for estimating evapotranspiration under well-wateredconditionsRichard G. Allen | Ground-based Energy Balance, Scintillometer andEvapotranspiration Studies in Natural Systems to Support Remote SensingModelsKyle G. Pressel | Scale Invariance of the Water Vapor Field Observed by theAtmospheric Infrared SounderRichard G. Allen | Impact of Aerodynamic Algorithms in Mountains whenApplying Landsat-scale Energy Balances10

EM-25EM-26EM-27EM-28EM-29EM-301600h – 1900hSWM-1SWM-2SWM-3SWM-4SWM-5SWM-6SWM-7SWM-8SWM-9SWM-10Ayse Irmak | Requirements for Evapotranspiration at Field-Scale usingLandsat-scale Remote Sensing-Based Energy Balance in the Central Platteand Sand Hills of Nebraska, USAThomas C. Moran | Comparing annual evapotranspiration estimatesderived from remote sensing and surface measurement for water-limitedcatchments in CaliforniaWilliam D. Collins | A Comparison of the Scale Invariance of the WaterVapor Field Observed by the Atmospheric Infrared Sounder to the ScaleInvariance of In Situ Observations from a Very Tall TowerMatthew F. McCabe | Multi-model regional scale estimation ofevapotranspirationEric Wood | Internal validation of a distributed hydrological modelthrough land surface temperature from remote sensingMatthew F. McCabe | Intercomparison of flux measurement approaches:eddy covariance, scintillometers and remote sensing retrievals over agrasslandPoster Session I - Surface Water StorageNaupaka V - VIIBrian Brisco | Wetland Coherence for Water Level EstimationErnesto Rodriguez | The Measurement of Reach-Averaged Discharge bythe SWOT MissionErnesto Rodriguez | The Estimation of Reach-Averaged Bathymetry andFriction Coefficient from SWOT DataDelwyn Moller | Initial Evaluations of SWOT Water Surface ElevationRetrievals Using a High-Fidelity Dynamic SimulatorDelwyn Moller | Topographic Mapping of the Water Surface usingAirborne Millimeter-Wave InterferometryAmanda C. Hall | Observing the Amazon Floodplain with Remote Sensing:ICESat, Radar Altimetry and DGPSC. K. Shum | SURFACE FLOOD AND SMALL WATER BODYMONITORING USING RADAR ALTIMETRY: PROSPECTS FOR SWOTMatthew D. Wilson | The Surface Water and Ocean Topography SatelliteMission – An Assessment of Swath Altimetry Measurements of RiverHydrodynamicsDaniel Esteban Fernandez | KARIN: THE KA-BAND RADARINTERFEROMER FOR THE SWOT MISSIONMichael T. Durand | Optimal interpolation of spaceborne heightmeasurements of river height to support SWOT discharge algorithms11

SWM-11SWM-12SWM-13SWM-14SWM-15SWM-16SWM-17SWM-18SWM-19SWM-201600h – 1900hSMM-1SMM-2SMM-3SMM-4SMM-5SMM-6SMM-7Douglas E. Alsdorf | Transforming Surface Water Hydrology ThroughSatellite MeasurementsBrian Pollard | The Surface Water / Ocean Topography Mission: HighResolution, Wide Swath Surface Water Topography from SpaceKonstantinos Andreadis | Assessing the information content of SWOTobservations for hydrologic estimationJohn Lenters | An international collaboration to examine global laketemperature trends from in situ and remote sensing data: Project objectivesand preliminary resultsJean Négrel | River surface roughness sensitivity to wind conditions : insitu measurement technique, processing method and resultsMatthew K. Mersel | Effects of Reach Averaging on Empirically-Based,Remotely-Sensed Estimates of River DepthJoecila SANTOS DA SILVA | ALTIMETRY OF THE AMAZON BASINRIVERSDavid C. Goodrich | TRMM-PR Satellite-Based Rainfall Retrievals overSemi-Arid Watersheds Using the USDA-ARS Walnut Gulch Gauge NetworkHyongki Lee | Characterization of Terrestrial Water Dynamics in theCongo Basin Using GRACE and Satellite Radar AltimetryDavid C. Goodrich | TRMM-PR Satellite-Based Rainfall Retrievals overSemi-Arid Watersheds Using the USDA-ARS Walnut Gulch Gauge NetworkPoster Session I - Soil MostureNaupaka V - VIIMichael H. Cosh | Validating the BERMS in Situ Soil Moisture Networkwith a Large Scale Temporary NetworkEni G. Njoku | Soil Moisture Active Passive (SMAP) Mission Science andData Product DevelopmentMarkus C. Enenkel | Improved agricultural Drought Monitoring viaremotely sensed Soil Moisture DataEric Wood | Creating Global Soil Moisture Data Record From AMSR-EThrough Calibration of a Radiative Transfer ModelAngelika Xaver | Recent progress on the International Soil MoistureNetworkHelin Wei | The application of satellite remote-sensing data products forland surface modeling in the NCEP operational modelsHans Lievens | Assimilation of SMOS data into a coupled land surface andradiative transfer model for improving surface water management12

SMM-8SMM-9SMM-10SMM-11SMM-12SMM-13SMM-14SMM-15SMM-16SMM-171600h – 1900hSCM-1SCM-2SCM-3SCM-4SCM-5SCM-6SCM-7Jeffrey P. Walker | The Soil Moisture Active Passive Experiment: TowardsActive Passive Retrieval and DownsclaingSamuel Chan | SMAP Instrument Design For High Resolution SoilMoisture And Freeze/Thaw State MeasurementsChristoph Rudiger | SMOS Soil Moisture Validation in AustraliaYoomi Hur | Serious Radio Frequency Interference from SMOS: Case studyin East AsiaRobert Parinussa | Global quality assessment of active and passivemicrowave based soil moisture anomalies for improved blendingAlejandro Monsiváis-Huertero | SOIL MOISTURE FIELDMEASUREMENTS:THE VALIDATION PROCESS USING MICROWAVEREMOTE SENSINGAlejandro Monsivais-Huertero | Optimal use of active/passive microwaveobservations at L-band for improving root zone soil moistureNarendra Das | Past, Present and Future of Satellite-based Remote Sensingto Measure Surface Soil Moisture: With Emphasis on Soil Moisture ActivePassive Mission (SMAP) MissionHamidreza Norouzi | Land Surface Characterization Using Multi-satelliteMicrowave ObservationsBrian K. Hornbuckle | Iowa: Field (Experiment) of Dreams?Poster Session I - Snow and Cold RegionsNaupaka V - VIIJessica E. Cherry | Advances in Airborne Remote Sensing of HydrologicChange in Cold RegionsNai-Yu Wang | Developing Winter Precipitation AlgorithmKristine M. Larson | GPS Snow SensingJonathan Muñoz Barreto | CREST-SAFE: The CREST-Snow Analysis andField ExperimentR. D. Garg | Estimating Snow Water Equivalent (SWE) in the Part ofNorth West Himalayan Catchment of Beas River, using Synthetic ApertureRadar (SAR) dataJames L. McCreight | Validation of satellite-derived seasonal snow cover byairborne LiDARSteven Mitchell | Bathymetric Polarization Lidar for Hydrologic RemoteSensing Applications13

SCM-8SCM-9SCM-10SCM-11SCM-12Anne Walker | Airborne and Ground-Based Passive Microwave RadiometerField Campaigns for the Development and Validation of new SatelliteDerived Snow DatasetsAnne Walker | Spring thaw detection from satellite active and passivemicrowave measurementsAndrés Varhola | Combining Coordinate-Transformed Airborne LiDARand LANDSAT Indices to Obtain Forest Structure Metrics Relevant toDistributed Hydrologic ModelingAnne E. Walker | Canadian Advancements in Characterizing High LatitudeSnow Cover Properties Using Satellite DataMelody Sandells | Can simpler models reproduce the snow temperaturegradients of many-layered models for remote sensing of snow mass? ASNOWMIP2 intercomparisonSCM-13 Thian Y. Gan | Changes in North American Snow packs for 1979-2004Detected from the Snow Water Equivalent data of SMMR and SSM/IPassive Microwave and related Climatic FactorsSCM-14SCM-15SCM-16SCM-17SCM-18SCM-19SCM-20SCM-21SCM-22SCM-23Kathryn A. Semmens | Remote Sensing of Snowmelt - Understanding aChanging (and Melting) FutureMichael T. Durand | Snow microstructure and passive microwave remotesensing of snow: Field experiments at Storm Peak Laboratory, Colorado,USANarges Shahroudi | Microwave Emissivities of Land Surfaces: Detection ofSnow over Different Surface TypesBenjamin J. Vanderjagt | How sub-pixel snow depth, vegetation, and grainsize variability affect the ability to estimate large-scale SWE frommicrowave measurements in alpine areasSusan Frankenstein | Using microwave remote sensing to determinepatterns of swe and melt timing in remote environmentsNoah P. Molotch | Remote Sensing of the Mountain Snowpack:Integration of Observations and Models to Support Water ResourceManagement and Ecosystem ScienceJeffrey S. Deems | LiDAR for snow depth mapping: overview, error sources,and snow as a laser targetEdward Kim | Multilayer Snow Microwave Model Intercomparisons andScale Implications for Future Snow MissionsPeter B. Kirchner | Measuring under-canopy snow accumulation withairborne scanning LiDAR altimetry and in-situ instrumentalmeasurements, southern Sierra Nevada, CaliforniaKazuyo Murazaki | Discrimination Between Rain and Snow in Japan Withan Operational Conventional C-band Radar Network14

SCM-24SCM-251600h – 1900hPM-1PM-2PM-3PM-4PM-5PM-6PM-7PM-8PM-9PM-10PM-11PM-12Hiroshi Ishimoto | Microwave Scattering Properties of Complex ShapedSnowflakesThomas Painter | The JPL Airborne Snow Observatory: Cutting edgetechnology for snow hydrology and water managementPoster Session I - PrecipitationNaupaka V - VIIAbebe S. Gebregiorgis | Characterizing Satellite Rainfall Errors based onLand Use and Land Cover and Tracing Error Source in Hydrologic ModelSimulationTristan S. L’Ecuyer | The Role of Spaceborne Cloud Radars in TerrestrialHydrologyBin Yong | Evolving TRMM-based Multi-satellite Real-Time PrecipitationEstimation Methods: Their Impacts on Hydrologic Prediction Using theVariable Infiltration Capacity Model in a High Latitude BasinVincent Fortin | Improving the Canadian Precipitation Analysis (CaPA)Over the Laurentian Great Lakes Through Data Assimilation of RadarReflectivity and GOES ImageryMatthew D. Lebsock | The Complementary Role of Observations of LightRainfall from CloudSatAmila S. Ratnayake | GIS-based hydrological predictions and estimationsof hydropower potential: Implications for flood risk mitigation at GinRiver, Sri LankaOmowumi O. Alabi | Validation of TRMM Satellite Data in theFarmington/Du River Basin of LiberiaJaya kumar A | Role of El Niño in Modulating the Period of PrecipitationVariability of Asian Summer Monsoon Using Satellite ObservationsRobert F. Adler | Status and Future of a Real-time Global Flood andLandslide Estimation System Using Satellite Rainfall Information andHydrological ModelsQi Chen | Using Bayesian Methods to Fuse Data from Multiple Sources(Raingages, Radar, Meteorological Model, PRISM maps, and VegetationAnalysis) for Mapping Rainfall in the State of HawaiiShaun Lovejoy | The Space-time variability of precipitation frommillimeters to planetary scales, from hours to centuries: emergent laws andmultifractal cascadesJay Mace | A new instrument for high-speed, high resolution stereoscopicphotography of falling hydrometeors with simultaneous measurement offallspeed15

PM-13PM-14Praveen K. Thakur | Inter Comparison of Satellite and Ground BasedRainfall Products - A Case Study for IndiaYuezhen Luo | High-Resolution Regional Analyses of Daily and HourlyPrecipitation Climatology over Eastern ChinaTUESDAY, 21 FEBRUARY0800h – 0840h0840h – 0920h0920h – 1000h1000h – 1030h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200h1030h – 1200hOral Session 3: Remote Sensing the Dynamic Water Cycle: SoilMoisture, Precipitation, and EvapotranspirationPresiding: Martha C. Anderson, Michael H. CoshNaupaka BallroomYann H. Kerr | SMOS and Hydrology: First Lessons Learnt INVITEDMichael R. Raupach | Interactions Between the Terrestrial Water andCarbon Cycles INVITEDRobert F. Adler | The Global Precipitation Measurement (GPM) Mission:Overview and U.S. Science Status INVITEDTuesday AM Coffee Break and Networking BreakBreakout Session 1 - Applications of Water Cycle Variables:Modeling and Data AssimilationBreakout Session 2 - Applications of Water Cycle Variables:Modeling and Data AssimilationBreakout Session 3 - Applications of Water Cycle Variables:Floods and DroughtsBreakout Session 4 - Applications of Water Cycle Variables:Floods and DroughtsBreakout Session 5 - Applications of Water Cycle Variables:Snow MeltBreakout Session 6 - Applications of Water Cycle Variables:Snow MeltBreakout Session 7 - Applications of Water Cycle Variables: InSitu Data and Observations16

1030h – 1200h1030h – 1200h1030h – 1200h1200h – 1330h1330h – 1410h1410h – 1450h1450h – 1530h1530h – 1600h1600h – 1630h1600h – 1900hGT-1GT-2GT-3GT-4GT-5Breakout Session 8 - Applications of Water Cycle Variables: InSitu Data and ObservationsBreakout Session 9 - Applications of Water Cycle Variables:Weather and Climate ModelingBreakout Session 10 - Applications of Water Cycle Variables:Weather and Climate ModelingLunch on Your Own (Tuesday)Oral Session 4: Integration of Space-borne, Airborn, andGround-based Measurement SystemsPresiding: Michael H. CoshNaupaka BallroomThomas J. Jackson | Advances in the Validation of Satellite Soil MoistureProducts with In Situ Observations INVITEDJerad D. Bales | In Situ and Remotely-Sensed Hydroclimate Data forWater- Resources ManagementRalf Bennartz | Measuring High-latitude Precipitation From SpacePingping Xie | Gauge - Satellite Merged Analyses of Land Precipitation: APrototype Algorithm INVITEDTuesday PM Coffee BreakPoster Session II - GroundwaterNaupaka V - VIIVenkateswara Rao Bekkam | Groundwater and Surface Water StorageDynamics in the Musi River IndiaEdwin H. Sutanudjaja | Using space-borne remote sensing products tocalibrate a large-scale groundwater model: a test-case for the Rhine-MeusebasinJacque L. Kelly | Practical applications of infrared imagery for investigatingsubmarine groundwater discharge and other thermal anomalies in coastalzonesJessica Reeves | Uncertainty in InSAR deformation measurements forestimating hydraulic head in the San Luis Valley, ColoradoJean Wilson | Regional scale assessment of Submarine GroundwaterDischarge in Ireland combining medium resolution satellite imagery andgeochemical tracing techniques17

GT-6GT-7GT-8GT-91600h – 1900hET-1ET-2ET-3ET-4ET-5ET-6ET-7ET-8ET-9ET-10ET-11ET-12Amit Singh | ASSESSMENT OF MORPHOTECTONIC INFLUENCES ONHYDROLOGICAL ENVIRONMENT IN VICINITY OF AN ACTIVE FAULTMatthew W. Becker | Wetlands as Groundwater Piezometers in BorealForestsMartin Kappas | Simulation of water balance components in a watershedlocated in central drainage basin of Iran by A. Rafiei Emam and Martin W.KappasWei Feng | Evaluation of groundwater depletion in North China using theGravity Recovery and Climate Experiment (GRACE)Poster Session II - EvaportranspirationNaupaka V - VIIEslam F. Farg | Estimation of Evapotranspiration and Crop Coefficient Kcof Wheat, in south Nile Delta of Egypt Using integrated FAO-56 approachand remote sensing dataYoungryel Ryu | Integration of MODIS Land and Atmosphere ProductsWith a Coupled-process Model to Estimate Evapotranspiration From 1 kmto Global ScalesNana Yan | An Operational Regional ET Monitoring System (ETWatch)and Its ValidationMirza M. Billah | Impacts of Different Evapotranspiration Estimates onQuantify Regional Scale Terrestrial Water StorageJoseph G. Alfieri | The Factors Influencing Seasonal Variations inEvaporative Fluxes from Spatially Distributed Agro-EcosystemsJohn Worden | Constraints on High Latitude Moisture Fluxes andContinental Recycling Using Satellite and Aircraft Measurements of WaterVapor IsotopesShusen Wang | Characterization of Spatiotemporal Variations inEvapotranspiration Over Canada’s LandmassJared W. Oyler | Assessment of the MODIS Global TerrestrialEvapotranspiration Algorithm within a Mountainous LandscapeLahouari Bounoua | Century Scale Evaporation Trend: An ObservationalStudyGregory J. Tripoli | Trends in Evapo-transpiration in the Great Lakes StatesPrasad S. Thenkabail | Global croplands and their water use assessmentsthrough advanced remote sensing and non-remote sensing approachesMarcelo Nosetto | Land-use changes in temperate Argentina: Assessingtheir hydrological impacts with remote sensing18

ET-13ET-14ET-15ET-16ET-17ET-18ET-19ET-20ET-21ET-22ET-23ET-24ET-25ET-26ET-271600h – 1900hSWT-1Kaniska Mallick | Development of MODIS-based global net radiation forevapotranspiration studies at 1 km2Kaniska Mallick | A satellite net available energy retrieval scheme for globalevapotranspiration studies using AQUA platformMarta Yebra | Remote sensing canopy conductance for combined waterand carbon studiesPoolad Karimi | Remote sensing application to support water accountingin the transboundary Indus BasinHan Dolman | Analyzing the Magnitude and Variability of LandEvaporation using Satellite InformationPercy Link | Variability of oceanic and terrestrial water vapor sources in theAmazon Basin: An investigation using TES satellite and MERRA reanalysisat varying temporal resolutionsMekonnen Gebremichael | Estimation of Daily Evapotranspiration overAfrica using MODIS/Terra and SEVIRI/MSG dataHolly Maness | The Hydrologic Impact of the British Columbia MountainPine Beetle Infestation From Remotely Sensed DataForrest S. Melton | An Operational Framework for Estimation ofAgricultural Evapotranspiration with the Terrestrial Observation andPrediction SystemJordan Borak | A Dynamic Vegetation Aerodynamic Roughness LengthDatabase Developed From MODIS Imagery for Improved Modeling ofGlobal Land-Atmosphere ExchangesJuan Guerschman | An operational actual ET product for AustraliaJavzandulam Tsend-Ayush | Generating a long-term vegetation index datarecord from AVHRR and MODISDavid C. Noone | Evaluation of tropical continental water cycling fromspace-based observations of water isotope ratiosMax B. Berkelhammer | Moisture budgets in the southwestern US ondiurnal to seasonal timescales and their association with sub-canopy tobasin-wide processesChristopher M. Neale | Water balance of Large Irrigation Systems usingRemotely Sensed ET EstimatesPoster Session II - Surface Water StorageNaupaka V - VIIEtienne Fluet Chouinard | Towards a High-Resolution Global InundationDelineation Dataset19

SWT-2SWT-3SWT-4SWT-5SWT-6SWT-7SWT-8SWT-9SWT-10SWT-11SWT-12SWT-13SWT-14SWT-15SWT-16SWT-17SWT-18Daniel A. Slayback | Near Real-Time Satellite Monitoring Of GlobalFlooding EventsQiuhong Tang | Terrestrial Water Storage Variations from GRACE andWater Budget in Major River Basins of ChinaJoseph Awange | Understanding the Changes in the Nile Basin’s StoredWater Patterns and Their Link to Climate VariabilityKenneth L. Verosub | Determining River Flows Using Historical AerialPhotography and Satellite ImageryPascal Kosuth | A method for river discharge estimate from satelliteobservation alone, without any in situ measurementBrian Brisco | Mapping Surface Water and Flooded Vegetation using SARRemote Sensing for Critical Ecosystems in North AmericaPrasad S. Thenkabail | Selecting Areas of Wetland Cultivation andPreservation in Africa: Satellite Sensor Data Fusion Synthesized withSocio-economic data in a Spatial Modeling Framework to Support Africa’sGreen and Blue RevolutionAyoub Moradi | Multi-sensor study of hydrological changes in Caspian SeaZhao Liu | An Explicit Representation of High Resolution River Networksusing a Catchment-based Land Surface Model with the NHDPlus datasetfor California RegionAlejandra S. Membrillo | SEASONAL CHANGE DETECTION WITHMULTISPECTRAL IMAGES ON THE LAKE OF CHAPALA, MEXICOYaakov Anker | Small stream monitoring by spectral classification of highspatial resolution, digital RGB aerial imagesOlusegun Adeaga | Estimation of Terrestrial Water Storage for waterresources system managementWenchao Sun | Estimating River Discharge by the Hydrological ModelCalibrated Based on River Flow Width Derived from Synthetic ApertureRadar ImagesJianbin Duan | VALIDATION OF GRACE HYDROLOGIC STORAGECHANGE SOLUTIONS USING SATELLITE ALTIMETRY AND IN SITUDATATamlin M. Pavelsky | Continuous River Width-Drainage AreaRelationships in the Yukon River BasinJohn F. Galantowicz | Toward Daily Inundation Extent Mapping:Demonstration of a Multi-Scale Data Merging Algorithm with AMSR-Eand Simulated SMAP DataHahn Chul Jung | Improved calibration of modeled discharge and storagechange in the Atchafalaya Floodplain using SAR interferometry20

SWT-19SWT-201600h – 1900hSMT-1SMT-2SMT-3SMT-4SMT-5SMT-6SMT-7SMT-8SMT-9SMT-10SMT-11SMT-12SMT-13Kyle C. McDonald | Satellite Remote Sensing of Inundated Wetlands: DataRecord Assembly and Cross-Product ComparisonErika Podest | A Multi-Scale Comparison of Palm Swamp WetlandEcosystems Inundation State Between High and Low Microwave RemoteSensingPoster Session II - Soil MoistureNaupaka V - VIIGrey Nearing | Estimating Thermal Inertia with a Maximum EntropyProduction Boundary ConditionAnthony Freeman | The EV-1 Airborne Microwave Observatory ofSubcanopy and Subsurface (AirMOSS) InvestigationSebastian Hahn | Improvements and Challenges in the METOP ASCATSurface Soil Moisture Retrieval SchemeBinayak P. Mohanty | An Entropy based Assessment of Evolution ofPhysical Controls of Soil Moisture Across Watersheds in a Humid and Sub-Humid ClimateYao-Cheng Lin | Remote Sensing of Soil Moisture with Signals ofOpportunityJørgen L. Olsen | Estimating variations in bare soil and vegetation surfacemoisture, using solar spectrum geostationary earth observation data over asemi-arid areaMarek Zreda | Measuring area-average soil moisture using mobile cosmicraydetectorHans Lievens | Soil moisture retrieval from SAR over bare soil and wheatfields based on Water Cloud modeling, the IEM and effective roughnessparametersVenkataraman Lakshmi | Downscaling of passive microwave soil moistureusing vegetation and surface temperatureClara Chew | USING GPS INTERFEROMETRIC REFLECTOMETRY TOESTIMATE SOIL MOISTURE FLUCTUATIONSThian Y. Gan | Soil Moisture Retrieval From Microwave and OpticalRemotely Sensed DataRobert Parinussa | A Multi-decadal soil moisture dataset from passive andactive microwave soil moisture retrievalsKristen M. Brubaker | Multi-scale lidar greatly improve characterization offorested headwater streams in central Pennsylvania21

SMT-14SMT-15SMT-16SMT-171600h – 1900hSCT-1SCT-2SCT-3SCT-4SCT-5SCT-6SCT-7SCT-8SCT-9SCT-10SCT-11SCT-12SCT-13Karthik Nagarajan | An Observing System Simulation Experiment forEvaluating Scaling Algorithms Under Dynamic Land Cover Conditions forSoil Moisture ApplicationsEric E. Small | Sensing Vegetation Growth with Reflected GPS SignalsWilliam L. Teng | NASA Giovanni: A Tool for Visualizing, Analyzing, andInter-comparing Soil Moisture DataRussell J. Skuse | Thermophysical Characteristics of Surface Materials forMapping the Spatial Distribution of Soil Moisture in the Mojave Desertusing multi-scene ASTER TIR Remote Sensing ObservationsPoster Session II - Snow and Cold RegionsNaupaka V - VIIJuraj Parajka | MODIS Snow Cover Mapping Accuracy in Small AlpineCatchmentMatthew Sturm | Remote Sensing and Ground-based Snow Measurements:Limitations, Strengths, and Optimal BlendingAlexander Braun | On the Correlation Between Glacier Melting and LakeLevel Change on the Tibetan Plateau from Altimetry and GRACEDustin M. Schroeder | Remote Sensing of Subglacial Water Networks withIce Penetrating RadarNai-Yung C. Hsu | Satellite Remote Sensing of Snow/Ice Albedo over theHimalayasAnne W. Nolin | Vegetation and Snow: Remote Sensing and Interactionsfrom the Local to the Continental ScaleBruce F. Molnia | Global Fiducials Program Remote Sensing of the ColdRegions Terrestrial Water CycleIrina Gladkova | Seasonal snow cover of Yellowstone estimated withrestored MODIS Aqua, and MODIS Terra snow cover mapsKaren I. Mohr | Multi-scale observations and modeling of the hydrologicaldynamics of Andean peatbogsGlen E. Liston | An Improved Global Snow Classification Dataset forHydrologic ApplicationsLaura M. Hinkelman | Use of Satellite-Based Surface Radiative Fluxes toImprove Snowmelt ModelingFelix W. Landerer | Assessing water storage, winter precipitation anddischarge of Arctic drainage basins using GRACE and Global PrecipitationAnalysesDavid Selkowitz | Exploring Landsat-derived Snow Covered Area (SCA)Probability Distributions for Downscaling MODIS-derived Fractional SCA22

SCT-14SCT-15SCT-16SCT-17SCT-18SCT-191600h – 1900hPT-1PT-2PT-3PT-4PT-5PT-6PT-7PT-8PT-9PT-10Barbara M. Hauzenberger | Recent glacier changes in the Trans-AlaiMountains (Kyrgyzstan/Tajikistan) derived from remote sensing dataKarl E. Rittger | Assessment of Viewable and Canopy Adjusted Snow Coverfrom MODISJohn D. Lenters | Towards a Circum-Arctic Lakes Observation Network(CALON)Igor Appel | Improved VIIRS Snow Cover Information for Terrestrial WaterCycle ApplicationsRussell J. Qualls | Use of MODIS Snow-Covered-Area to DevelopHistorical, Current and Future Snow Depletion Curves for SnowmeltRunoff ModelingBaike Xi | AN EVALUATION AND INTERCOMPARISON OF CLOUDFRACTION AND RADIATIVE FLUXES IN RECENT ATMOSPHERICREANALYSES OVER ARCTIC CYCLE BY USING SATELLITEOBSERVATIONSPoster Session II - PrecipitationNaupaka V - VIIJayaluxmi Indu | RAIN/NO RAIN CLASSIFICATION OVER TROPICALREGIONS USING TRMM TMIGeorge J. Huffman | Upgrades to the Real-Time TMPALuigi J. Renzullo | An on-going intercomparison of near real-time blendedsatellite-gauge precipitation estimates for AustraliaAlfredo R. Huete | Shifts in Rainfall Use Efficiency and PrimaryProduction along a Savanna Aridity Gradient Assessed Using Satellite andFlux Tower Time Series DataBin Xu | Hourly Gauge-satellite Merged Precipitation Analysis over ChinaAhoro Adachi | Rainfall estimation and detection of hazardous convectivecells with a dual-polarized C-band radarSeyed Z. Hosseini | Relationship between terrestrial vegetation dynamicand precipitation using remote sensing and geostatistics in an aridecosystemShoichi Shige | Improvement of rainfall retrieval for passive microwaveradiometer over the mountain areasLina M. Castro | Assessment of TRMM Multi-satellite PrecipitationAnalysis (TMPA) in the South of Chile’s Andes MountainsMarielle Gosset | The Megha-Tropiques Mission23

PT-11PT-12PT-13PT-14PT-15PT-16PT-17PT-18PT-19PT-20PT-21PT-22PT-23PT-24PT-25PT-261600h – 1900hMT-1John B. Eylander | Remotely Sensed Precipitation and Land DataAssimilation System supporting Hydrology and Hydraulics in AustereEnvironmentsDaniel A. Vila | Validation of the Hydrological Monthly Products usingPassive Microwave SensorsDaniel A. Vila | Satellite Rainfall Retrieval Assessment over DifferentRainfall Regimes and the ‘Chuva’ Experiment Preliminary ResultsMekonnen Gebremichael | Error Model and Tuning Extremes for SatelliteRainfall EstimatesKwo-Sen Kuo | Precipitation Characteristics of Tornado-ProducingMesoscale Convective Systems in the Continental United StatesYang Hong | HyDAS: A GPM-era Hydrological Data Assimilation Systemfor Evaluating the Water Cycle and Hydrological Extremes at Global andRegional ScalesMallory Barnes | Detection of Spatial and Temporal Cloud Cover Patternsover Hawai’i Using Observations from Terra and Aqua MODISGraeme Stephens | A CloudSat perspective of the atmospheric water cycle:recent progress and grand challengesSteven P. Chávez Jara | CHARACTERIZATION OF HEAVY STORMS INTHE PERUVIAN ANDES USING THE TRMM PRECIPITATION RADARShinta Seto | Necessity of Integrated Observations of Soil Moisture andPrecipitation by Microwave Remote SensingAndrew Rhines | Tropical Loading Patterns Associated with AtmosphericRivers: Lagrangian Diagnosis and Prospects for Remote DetectionSteven Cooper | On the limitations of satellite passive remote sensing forclimate process studiesFrancisco J. Tapiador | Comparing Precipitation Observations, SatelliteEstimates and Regional Climate Model Outputs over EuropeYalei You | The Proportionality between Surface Rainfall and VerticallyIntegrated Water and Its Implications to Satellite Rainfall RetrievalMichael D. Grossberg | Multivariate structural signatures of precipitationand water dischargeMenberu M. Bitew | Can One Use Streamflow Observations as a Way ofEvaluating Satellite Rainfall Estimates?Poster Session II - Modeling and Data AssimilationNaupaka V - VIISagy Cohen | Calibration of Orbital Microwave Measurements of RiverDischarge Using a Global Hydrology Model24

MT-2MT-3MT-4MT-5MT-6MT-7MT-8MT-9MT-10MT-11MT-12MT-13MT-14MR-15MR-16MR-17Dai Yamazaki | Adjustment of a spaceborne DEM for use in floodplainhydrodynamic modellingChrista D. Peters-Lidard | The Impact of AMSR-E Soil MoistureAssimilation on Evapotranspiration EstimationYijian Zeng | Impact of Land Model Physics on One-dimensional SoilMoisture and Temperature Profile RetrievalLuciana Cunha | Exploring the Potential of Space-Based Remote Sensing inFlood PredictionXuan Yu | Using NLDAS-2 for Initializing Integrated Watershed Models:Model Spin-up for the AirMOSS CampaignRolf Reichle | AMSR-E Brightness Temperature Estimation over NorthAmerica Using a Land Surface Model and an Artificial Neural NetworkCedric H. David | Getting ready for SWOT: modeling of water flow andheight in thousands of mapped rivers covering hundreds of thousands ofsquare kilometersNorman L. Miller | Developing a High-Resolution Modeling andAssimilation Scheme for Terrestrial Groundwater ChangeLuigi J. Renzullo | Assimilating satellite-derived soil moisture alongsidestreamflow into the Australian water resources assessment systemJeffrey C. Neal | A simple hydraulic model for wide area inundationmodeling in data sparse areasFeyera A. Hirpa | Assimilation of Satellite Soil Moisture observations in aHydrologic Model for Improving Streamflow Forecast AccuracyAna Nunes | Challenges in Assessing South American Hydroclimate: HowCan Satellite-Based Precipitation Products Help?Yeosang Yoon | An ensemble-based approach for estimating riverbathymetry from SWOT measurementsHuidong Liu | Validation of modeled lake water level variations due tochanging climate, thermal variations and human activities using satelliteobservationsAdrien Paris | IMPROVING DISCHARGE ESTIMATES IN A LARGE,POORLY GAUGE BASIN BY TUNING A HYDROLOGICAL MODELWITH SATELLITE ALTIMETRY INFORMATIONMohamed E. Ahmed | Use of GRACE Data to Monitor Climate Change (ElNiño / La Niña)-induced Variations in Water Availability Across the AfricanContinent25

MT-18MT-191900h – 2130hRobert Pipunic | Impacts of satellite surface soil moisture assimilation onmodelled root zone soil moisture and ET over a six year period: Assessmentacross an in-situ soil moisture monitoring network, Murray-Darling Basin,AustraliaGerald G. Mace | Use of Dual Frequency Doppler Radar Spectra to InferCloud and Precipitation Properties and Air Motion StatisticsGroup DinnerGhassem Asrar, Keynote SpeakerDirector, World Climate Research ProgramWorld Meteorological OrganizationWEDNESDAY, 22 FEBRUARY0800h – 0840h0840h – 0920h0920h – 1000h1000h – 1015h1015h – 1200h1200h – 1330hOral Session 5: Future Directions in Remote Sensing of theTerrestrial Water CyclePresiding: Venkataraman LakshmiNaupaka BallroomEric F. Wood | Challenges in Developing Long-term Climate Data Recordsfor the Terrestrial Water and Energy Cycles INVITEDKevin E. Trenberth | Challenges for Observing and Modeling the GlobalWater Cycle INVITEDDiane L. Evans | New Measurements for Understanding the TerrestrialWater CycleWednesday AM Coffee and Networking BreakBreakout Summaries and Discussions from Monday AMEvapotranspiration - 1015h-1030hSoil Moisture - 1030h-1045hSnow - 1045h-1100hSurface Water - 1100h-1115hGroundwater - 1115h-1130hPrecipitation - 1130n-1145hLunch on Your Own (Wednesday)26

1330h – 1530h1530h – 1600h1600h – 1630hBreakout Summaries and Discussions from Tuesday AMModeling and Data Assimilation - 1330h-1345hFloods and Droughts: Extreme Events - 1345h-1400hSnow Melt - 1400h-1415hIn Situ Data and Observations - 1415h-1430hLinks to Weather and Climate Modeling - 1430h-1445hConcluding RemarksCoffee Break and AdjournTHURSDAY, 23 FEBRUARY0815h – 1715hOptional Post-conference Field Trip to Volcano National Park27

ABSTRACTSlisted by name of presenterAdachi, AhoroRainfall estimation and detection of hazardousconvective cells with a dual-polarized C-band radarAdachi, Ahoro 1 ; Kobayashi, Takahisa 1 ; Yamauchi, Hiroshi 1 ;Onogi, Shigeru 21. Meteorological Satellite and Observation SystemDepartment, Meteorological Research Institute, Tsukuba,Japan2. Physical Meteorology Department, MeteorologicalResearch Institute, Tsukuba, JapanLocal heavy rainfalls in urban area are drawing attentionin Japan because many people have been injured or even diedrecently due to flush floods associated with local heavyconvective rainfalls. Horizontal distributions of rainfall havebeen estimated from conventional weather radarobservations using the so-called Z-R relationship. Althoughthis relationship is relatively accurate for stratiform rain, thismethod is unreliable for convective precipitation, whichproduces heavy rainfall. It is well known that dual-polarizedradars can improve the accuracy of rainfall estimation, andthe accuracy of dual-polarized radar rainfall productsimproves with increasing rain intensity (Bringi andChandrasekar 2001). One key application of dual-polarizedradars at the operational frequency bands (S, C, and X) is theradar-based rainfall input to hydrological models (e.g.,Krajewski and Smith 2002, and Bringi et al. 2011). A varietyof rain-rate algorithms that uses the dual-polarized radardata have been proposed in the literature. Variables obtainedby the dual-polarized radars include radar reflectivity factor(Zhh), differential propagation phase (dp) and differentialreflectivity (Zdr). Because the differential reflectivity (Zdr)measured with C-band radar is more sensitive to largeraindrops associated with heavy rainfalls than is radarsoperating at other frequencies because of Mie scatteringresonance effect, the rain intensity estimated from thedifferential reflectivity (Zdr) and radar reflectivity factor(Zhh) measured with the dual-polarized C-band radar at theMeteorological Research Institute (MRI) in Tsukuba, Japanis used in the present study to analyze a local heavy rainfallevent that occurred on 7 July 2010 as a case study. Theestimate of rainfall using data from the MRI C-pol radar inthe local heavy rainfall event is compared against two opticaldisdrometers (PARSIVEL) located at about 30 km and 60 kmaway from the radar, respectively, with time intervals of 2minutes. Results show that the rainfall intensity estimatedfrom the Zdr and Zhh agrees well with the disdromterobservations and is more reliable than that estimated fromthe Z-R relationship. Moreover, the so-called high Zdrcolumn, a large differential reflectivity region was clearlyanalyzed aloft about 10 minutes prior to the local heavyrainfall on the ground, suggesting that the differentialreflectivity observed with dual-polarized C-band radar canbe a good index to detect subsequent heavy precipitationevents on the ground in advance.Adeaga, OlusegunEstimation of Terrestrial Water Storage for waterresources system managementAdeaga, Olusegun 11. Geography, University of Lagos, Lagos, NigeriaExtreme hydrological events have continued to poseserious threats to mankind with unique challenges to globalsocio-economic development and growth as aftermath. Suchchallenges demands for better understanding anddevelopment of an integrated water resources system withcapacity to accommodate the varied extreme events andexpected modification in water resources quantity andavailability at varied spatio-temporal level. The system is alsoof importance since water remains the fundamental linkbetween the climate system, human society and theenvironment. Unfortunately, suitable water resourcesassessment scheme has been greatly affected by pressure ofeconomic stringency through insufficient budget allocationand varied neglect of water resources assessmentinfrastructure. Vital information required in mosthydrological analysis for the purpose of water resourcesplanning are therefore in paucity, except for a fewcatchments. Intensive studies on hydrological processes andmechanisms have therefore being neglected for a longtimewith reported cases of station neglect while in most cases,the level and accuracy of available dataset is notcommensurate with present water developmental needs,especially in the developing countries. Paucity of groundbasedhydrological data has resulted in poor understandingof hydrologic response processes and its spatio-temporalvariability within drainage basins. Hence, Proper estimationof space-based Terrestrial Water Storage data will go a longway to provide adequate indices needed for achievingappropriate lead time information on extreme hydrologicalevents magnitude, intensity, occurrence and other waterrelated hazards. Such information will also play animportant supportive decision role in resolving practicalwater resource management and planning sinceprecipitation is invaluable as a source of renewablefreshwater. In this paper, terrestrial water storage estimationwas carried-out using 3-hourly TRMM Rainfall estimate andGRACE terrestrial water storage data in order to estimateavailable surface water distribution and its variability as wellas the uncertainty quantification for the period 2001 to2010, in Nigeria. This is necessary since adequate knowledgeon the distribution and quantification of terrestrial waterand its storage will be helpful as a measure towardsaddressing disaster prevention and water management in thedata scare region. The region is also characterizes with lowdensehydro-meteorological gauging network and little or no28

esilience to hydrological hazards and is highly susceptible toseasonal and spatial rainfall variability and increasingextreme hydrological events. The estimates also provide basicspatially-based indices towards estimating the hydrologicalextreme lead time information and the appropriateness ofthe available water resources system and adaptation schemewithin the region, in the 21st century and beyond.Adler, Robert F.Status and Future of a Real-time Global Flood andLandslide Estimation System Using SatelliteRainfall Information and Hydrological ModelsAdler, Robert F. 1 ; Wu, Huan 1 ; Kirschbaum, Dalia 2 ; Hong,Yang 31. 5825 University Research Court, University of Maryland,College Park, MD, USA2. NASA Goddard Space Flight Center, Greenbelt, MD, USA3. University of Oklahoma, Norman, OK, USAOver the last several years systems have been running inreal-time to estimate the occurrence of floods and landslides(see trmm.gsfc.nasa.gov and click on “Floods andLandslides”). These systems use 3-hr resolution compositerainfall analyses (TRMM Multi-satellite PrecipitationAnalysis [TMPA]) as input into a hydrological model thatcalculates water depth at each grid (at 0.25 degree latitudelongitude)over the tropics and mid-latitudes. In addition, asimple landslide algorithm using a static landslidesusceptibility map in conjunction with rainfall Intensity-Duration (I-D) thresholds based on the TMPA data is usedto estimate locations of high probability of landslideoccurrence. These calculations can provide informationuseful to national and international agencies inunderstanding the location, intensity, timeline and impacton populations of these significant hazard events. The statusof these flood calculations will be shown by case studyexamples and a statistical comparison against a global floodevent database. The flood validation study indicates thatresults improve with longer duration (> 3 days) floods andthat the statistics are impacted by the presence of dams,which are not accounted for in the model calculations. Acomparison of the landslide calculations with a new globallandslide inventory indicates a general over-estimation, butgeneral agreement on statistics of geographic location,seasonal variations and inter-annual differences. Limitationsin the flood and landslide calculations that are related to thesatellite rainfall estimates include space and time resolutionlimitations and underestimation of shallow orographic andmonsoon system rainfall. The current quality of these floodand landslide estimations is at the level of being useful, butthere is a potential for significant improvement, mainlythrough improved and more timely satellite precipitationinformation and improvement in the hydrological modelsand algorithms being used. NASA’s Global PrecipitationMeasurement (GPM) program should lead to betterprecipitation analyses utilizing space-time interpolationsthat maintain accurate intensity distributions along withmethods to disaggregate the rain information. Higherresolution flood models with accurate routing and regionalcalibration, and the use of satellite soil moisture retrievalsshould advance the state-of-the-art. Landslide algorithmswill be improved by a higher resolution susceptibility map,the use of soil moisture information, and regionallyvariableI-D thresholds. The use of forecast precipitation to augmentthe satellite-observed rainfall estimates and extrapolate theflood estimates for 1-5 day forecasts will also be discussed.Adler, Robert F.The Global Precipitation Measurement (GPM)Mission: Overview and U.S. Science StatusINVITEDHou, Arthur Y. 1 ; Adler, Robert F. 21. NASA Goddard SFC, Greenbelt, MD, USA2. University of Maryland, College Park, College Park, MD,USAThe Global Precipitation Measurement (GPM) Missionis an international satellite mission that will unify andadvance precipitation measurements from a constellation ofmicrowave sensors to provide next-generation globalprecipitation products for research and applications.Building upon the success of the U.S.-Japan TropicalRainfall Measuring Mission, the National Aeronautics andSpace Administration (NASA) of the United States and theJapan Aerospace and Exploration Agency (JAXA) will deployin 2014 a GPM “Core” satellite carrying a Ku/Ka-band DualfrequencyPrecipitation Radar (DPR) and a conical-scanningmulti-channel (10-183 GHz) GPM Microwave Imager (GMI)to establish a new standard for precipitation measurementsfrom space. For global coverage, GPM relies on satelliteprovided by a consortium of international partners thatinclude France, India, Europe, Japan, and the United States.In addition to the DPR and GMI, the GPM constellationcomprises the following sensors: Special Sensor MicrowaveImager/Sounder instruments on the U.S. DefenseMeteorological Satellite Program satellites, the AdvancedMicrowave Scanning Radiometer-2 on the GCOM-W1satellite of JAXA, the Multi-Frequency Microwave ScanningRadiometer and the microwave humidity sounder on theIndo-French Megha-Tropiques satellite, the MicrowaveHumidity Sounder (MHS) on the National Oceanic andAtmospheric Administration (NOAA)-19, MHS instrumentson MetOp satellites launched by the European Organisationfor the Exploitation of Meteorological Satellites, theAdvanced Technology Microwave Sounder (ATMS) on theNational Polar-orbiting Operational Environmental SatelliteSystem (NPOESS) Preparatory Project, and ATMSinstruments on the U.S. Joint Polar Satellite Systemsatellites. The current generation of global rainfall productsuses observations from a network of uncoordinated satellitemissions using a variety of merging techniques. GPM willprovide “next-generation” inter-calibrated globalprecipitation products characterized by: (1) more accurateinstantaneous precipitation measurement (especially forlight rain and cold-season solid precipitation), (2) intercalibratedmicrowave brightness temperatures from29

constellation radiometers within a unified framework, and(3) physical-based precipitation retrievals from allconstellation radiometers using a common observationconstrainedglobal hydrometeor database consistent withGPM Core sensor measurements, instead of a limited set ofmodel-generated hydrometeor database. As a science missionwith integrated applications goals, GPM will provide a keymeasurement for improving understanding of global watercycle variability and freshwater availability. GPM Coresensors will offer insights into 3-dimensional structures ofstorms, microphysical properties of precipitating particles,and latent heat associated with precipitation processes. GPMwill also provide data in near realtime for societalapplications ranging from position fixes of storm centers forcyclone track prediction, assimilation of precipitationinformation in operational weather forecasts, monitoringand predictions for floods and landslides, to management offreshwater resources. An overview of the GPM missiondesign and U.S. science activities will be presented.Ahmed, Mohamed E.Use of GRACE Data to Monitor Climate Change(El Niño / La Niña)-induced Variations in WaterAvailability Across the African ContinentAhmed, Mohamed E. 1 ; Sultan, Mohamed 1 ; Wahr, John 2 ; Yan,Eugene 3 ; Milewski, Adam 5 ; Chouinard, Kyle 4 ; Mohsen, Fadi 41. Department of Geosciences, Western MichiganUniversity, Kalamazoo, MI, USA2. Physics, University of Colorado at Boulder, Boulder, CO,USA3. Environmental Sciences, Argonne National Laboratory,Argonne, IL, USA4. Computer Science, Western Michigan University,Kalamazoo, MI, USA5. Geology, University of Georgia, Athens, GA, USAThe deviation of the sea surface temperature (SST) fromthe normal in the equatorial Pacific Ocean is usuallyexpressed by the El Niño/ La Niña cycles where El Niño ischaracterized by unusually warm temperatures and La Niñaby unusually cool temperatures in the equatorial Pacific.These two cycles not only change the precipitation patternsin the equatorial Pacific area but also introduce climatechange in remote areas around the World. Becauseprecipitation anomalies could induce a signature on themass distribution on land, we explore the utility of GravityRecovery and Climate Experiment (GRACE) data toinvestigate the spatial and temporal distribution of the areasaffected by El Niño / La Niña cycle. During the period fromApril 2002 to November 2010 four El Niño (5/2002-3/2003,6/2004/2/2005, 8/2006/1/2007, and 6/2009-4/2010) and twoLa Niña (9/2007-5/2008, and 7/2010- 4/2011) cycles wereidentified from Oceanic Nino Index (ONI). Monthly GRACEgravity field solutions (Center of Space Research [CSR]RL04) in form of Spherical Harmonic Coefficients (SHC’s)that span the period from April 2002 through November2010 were processed (temporal mean was removed, destriped,smoothed [250 km; Gaussian], and converted to 0.5x 0.5 deg. equivalent water thicknesses). A GIS platform wasused to examine the spatial and temporal variations inGRACE monthly solutions and to compare these variationsto observations extracted from other relevant temporalremote sensing data sets (e.g., precipitation, soil moisture),and geologic (e.g., geologic maps), hydrologic data(distribution of lakes, streams, etc), and topographic data(landscape type and distribution). Preliminary findingsindicate: (1) areas impacted by the El Niño cycle are thoseshowing consistent monthly GRACE mass solution patternsthroughout each of identified four El Niño cycles and thoseaffected by the La Niña cycles show consistent patternsthroughout the two recorded La Niña cycles; and (2) climateinduced mass variations could be observed on sub-basinscales (e.g., source areas) in areas of high signal to noiseratios. Implications for using GRACE data to evaluateimpacts of climate change on water availability over largedomains are clear.Alabi, Omowumi O.Validation of TRMM Satellite Data in theFarmington/Du River Basin of LiberiaAlabi, Omowumi O. 1 ; Gar-Glahn, Eugene 21. Department of Satellite Meteorology, African RegionalCentre for Space Science & Technology Education(ARCSSTE-E), Ile Ife, Nigeria2. Division of Meteorology, Ministry of Transport,Monrovia, LiberiaThis research was focused on the Farmington/Du RiverBasin (latitude 6.4° North and longitude 10.4° West) locatedin Margibi county, one of the 15 counties in Liberia. Thestudy compared the Tropical Rainfall Measuring Mission(TRMM) Satellite derived monthly precipitation(TRMM3B42V6) with rain gauge data recorded at onemeteorological station in the Farmington/Du River Basin,and the possibility of using satellite estimated rainfall tocomplement ground-measured values. The monthly rainfallcomparisons showed that the TRMM rainfall trends werevery similar to the observed data trends. The correlationbetween the monthly datasets ranged from 0.75 to 0.98. Thetwo sets of data captured the phenomenon known as the‘little dry season’, characterized by an abnormal decrease inprecipitation which occurred during the month of July atthe peak of the rainy season. Although the overall catchmentrainfall was well represented by TRMM data, it was observedthat the annual ground measured values were eitheroverestimated or underestimated. TRMM’s persistentunderestimations which occurred from 1998 to 2004 weregenerally below 18% while the overestimations which wererecurrent between 2005 and 2009 were below 9%. This studyconcluded that even though the TRMM precipitation didnot perfectly match with the rain gauge data, it can still beused to supplement ground measurements and forestimating rainfalls in un-gauged basins. This is especiallyimportant in Liberia, a country where political instabilityresulted in the extinction of almost all the fewmeteorological stations in the region.30

Alfieri, Joseph G.The Factors Influencing Seasonal Variations inEvaporative Fluxes from Spatially Distributed Agro-EcosystemsAlfieri, Joseph G. 1 ; Kustas, William P. 1 ; Gao, Feng 1 ; Prueger,John H. 2 ; Baker, John 3 ; Hatfield, Jerry 21. HRSL, USDA, ARS, Beltsville, MD, USA2. NLAE, USDA, ARS, Ames, IA, USA3. SWMU, USDA, ARS, St. Paul, MN, USAThe exchange of moisture between the land surface andthe atmosphere is the result of complex network ofinteracting processes, most of which are regulated, at least inpart, by spatially variable atmospheric and surfaceconditions. Because these processes are often stronglynonlinear, scaling measurements collected at one scale toanother remains a nontrivial task. Since field measurementsare commonly used to develop, calibrate, and validate bothnumerical models and remotely sensed products, errors inthe upscaling of point measurements can propagate intoand adversely impact the accuracy and utility of thesemodels and products. In an effort to identify the keyenvironmental drivers controlling the latent heat flux (E)from agro-ecosystems and their potential impacts onupscaling in-situ flux measurements, eddy covariance andmicrometeorological data collected over maize and soy atthree distinct sites located in Maryland, Iowa, andMinnesota, respectively were evaluated. The magnitudes ofthe evaporative fluxes were comparable for measurementscollected during clear-sky days with similar environmentalconditions; on average, the measurements of E agreed towithin 50 W m-2, or 10%. When considered in terms ofevaporative fraction (f e), however, there were markeddifferences among the sites. For example, while themagnitude and diurnal pattern of f efor mature maize at theMinnesota site was nearly constant (f e= 0.66) during the day,(f e) at both the Maryland and Iowa site increased steadilyduring the day from a minimum value near 0.68 at midmorningto peak value of 0.87 in the afternoon. Thesedifferences appear to be primarily linked to differences insoil moisture and vegetation density at the various sites. Theutility of remote sensing data to provide the necessaryvegetation metrics to identify the underlying cause of thedifference in f ewill also be discussed.Allen, Richard G.Conditioning of NLDAS, NARR and arid weatherstation data for estimating evapotranspirationunder well-watered conditionsAllen, Richard G. 1 ; Huntington, Justin 2 ; Irmak, Ayse 3 ;deBruin, Henk 4 ; Kjaersgaard, Jeppe 51. Civil Engineering, University of Idaho, Kimberly, ID, USA2. Desert Research Institute, Reno, NV, USA3. School of Natural Resources, University of Nebraska,Lincoln, NE, USA4. Retired, Wageningen University, Wageningen,Netherlands5. Biological Engineering, South Dakota State University,Brookings, SD, USAMany satellites like MODIS and Landsat have returntimes of multiple days. Therefore, calculation ofevapotranspiration (ET) over extended time periods requiresweather data in between overpasses. NLDAS and NARRgridded weather data systems are produced by the WRFmodel or similar. These gridded sets represent ‘ambient’weather and surface energy balance under rainfallconditions. The water balance is generally not informed onirrigation and associated ET so that weather data generatedby these models represent that occurring under rainfedconditions. Local dryness tends to elevate near surfacetemperature (T) measurements by as much as 5 C, andreduces vapor pressure by up to one-half, when compared tomeasurements made over an evaporating surface. When thedata are entered into standardized reference ET equationsfor estimating crop water requirements in irrigatedagriculture, the higher air temperatures and lower vaporpressures associated with the ambient conditions tend tooverestimate ET anticipated in an irrigated environment byup to 20%. A procedure is described for “conditioning”ambient weather data from ‘arid’ environments having lowvapor fluxes and high sensible heat fluxes so that datarepresent near surface air properties for the same climate,but over an evaporating, “reference” surface. Theseadjustments are necessary before applying ‘referenceevapotranspiration’ methods such as the ASCE-EWRIPenman-Monteith equation that assume equilibriumbetween the reference, evaporating surface and near surfaceair. Following conditioning, the “equilibrium reference ET”can be scaled using crop coefficients or other parameters toestimate actual ET for a variety of vegetation. Theconditioning completes the feedback processes betweensurface evaporation and near surface air properties. Theprocedure extrapolates T, vapor and wind speed profiles toand from a blended height of 50 m using ambient andreference vapor fluxes and sensible heat fluxes. T, humidity,solar radiation and wind speed are utilized and theprocedure can be applied to hourly or daily data. Theprocedure can be applied to measured weather data and togridded weather data from WRF-Noah and other landsimulation models. The approach uses standard M-Osimilarity theory. In applications in southern Idaho, theprocedure estimated a 4 C decrease in 2 m T, doubling of 2m31

vapor pressure, and a 20% reduction in 2m wind speed overan evaporating surface as compared to the original ‘desert’condition. These differences were confirmed by datameasurements over an irrigated alfalfa field. Theconditioned data reduced estimated reference ET by 20%which has significant, negative consequences for ETestimates used in irrigation water management, in waterbalance studies and water rights transfers, that, in thefuture, may be based on gridded weather data from theWRF-Noah and similar models. Partially funded by NSFEPSCoR.Allen, Richard G.Ground-based Energy Balance, Scintillometer andEvapotranspiration Studies in Natural Systems toSupport Remote Sensing ModelsAllen, Richard G. 1 ; Zhao, Wenguang 1 ; deBruin, Henk 2 ;Germino, Matt 3 ; Sridhar, Venkat 4 ; Robison, Clarence 1 ;Greth, Jeremy 11. Civil Engineering, University of Idaho, Kimberly, ID, USA2. Retired, Wageningen University, Wageningen,Netherlands3. Biology, Idaho State University, Pocatello, ID, USA4. Civil Engineering, Boise State University, Boise, ID, USAMany river basins contain complex combinations andgradients of vegetation and gradients in elevation,precipitation, soils, aspect and slope. These complexitiesmake it difficult to estimate evapotranspiration (ET) for thebasins, thereby complicating the establishment of waterbalances and the parameterization of hydrologic models.Satellite-based energy balance computation systems havebecome widely used during the past decade; however, thesesystems have some uncertainty and themselves need someindependent calibration. In Idaho, we have strong interest indeveloping a better understanding of the time-based releaseof precipitation, in the form of evaporation andtranspiration, from extensive systems of sagebrush andinvasive cheatgrass in order to better predict impacts toground-water and ecosystem health under land-use andclimate change and tendencies for cheatgrass invastions tospread. Sensible heat fluxes over a sagebrush and an invasivecheat grass have been measured since late 2009 usingmultiple eddy covariance stations and large aperaturescintillometers (LAS). We have used combinations of CSAT3and RM Young 81000 3D sonic anemometers with LI-7500CO2/H2O analyzers placed along transects of ScintecBLS900 LAS systems to independently derive H at each site.Optical large aperture scintillometers (LAS) have beendeployed over sagebrush and invasive cheatgrass systems indesert and above a 1600 m transect over lodgepole pineforest near Yellowstone National Park to estimate H andultimately ET. Results show the H derived by thescintillometry method to closely agree with that derived bythe eddy covariance over both sagebrush and cheatgrassecosystems during fall, winter, spring and summer,including during nighttime, when boundary layer conditionsare sometimes highly stable. Four different computationschemes have been used with the LAS that use varyingamounts of measurements from the sonic anemometer,including friction velocity and the Monin-Obukhov stabilitylength. We have also used multiple linear regression with themore than 10 soil heat flux subsights to determine aweighted combination of soil heat flux data to explain themeasured energy balance data. Uses of the data are describedincluding improving our understanding of surfaceconductance behavior of vegetation during soil waterdepletion, projection of energy balance behavior underfuture climates and improved parameterization of remotesensing models. The challenges with deriving H fromscintillometry include uncertainties in effective path heightover mixed vegetation/terrain systems and uncertainties inspecifying an effective friction velocity for these samecomplex systems. The need for many replicates of netradiometers and soil heat flux sensors (we use 16 at eachlocation) is emphasized and illustrated. Funding is by theNSF EPSCoR.Allen, Richard G.Impact of Aerodynamic Algorithms in Mountainswhen Applying Landsat-scale Energy BalancesAllen, Richard G. 1 ; Trezza, Ricardo 1 ; Irmak, Ayse 2 ; Healey,Nathan 2 ; Tasumi, Masahiro 31. Civil Engineering, University of Idaho, Kimberly, ID, USA2. School of Natural Resources, University of Nebraska,Lincoln, NE, USA3. University of Miyazaki, Miyazaki, JapanThermal satellite-based energy balance models havebecome common for producing images of ET over largeareas. Applications are typically made using Landsat imageryto produce 30 m resolution data for obtaining field-scale ETinformation. This same resolution is useful for describingsurface energy balance and partitioning on mountain slopes.In mountains and complex terrain, solar radiation is astrong function of slope and aspect. We describe a recentlyrefined technique to estimate beam, diffuse and terraincomponents of solar radiation independently and thepositive impact this has on reflectance retrievals at 30 mresolution. We describe an adjustment in terraintemperature for cross-valley thermal emission of long-wave.In addition to radiation effects, we describe the sensitivity ofsensible heat flux estimation to wind speed and terrainroughness in mountainous areas. To conduct the sensitivityanalysis, we increase wind speed in proportion to a relativeelevation parameter computed for a 3 km locality of eachpixel and we increase aerodynamic roughness to assimilateimpacts of relative terrain roughness, estimated inproportion to standard deviation of elevation within a 3 kmlocality. These aerodynamic modifications increaseconvective heat transfer in complex terrain and reduceestimated ET. In some applications we reduce estimatedwind speed on leeward slopes of mountains when winddirection is judged to be consistent within the image.Illustrations of estimated ET with and without thesealgorithms is demonstrated in mountainous areas of Idaho,32

Montana and Oregon. Other applications with and withoutthe terrain algorithms are illustrated in applications to theSandhill area of Nebraska. Partial funding is by NSFEPSCoR.Alsdorf, Douglas E.Transforming Surface Water Hydrology ThroughSatellite MeasurementsAlsdorf, Douglas E. 1 ; Mognard, Nelly 2 ; Rodriguez, Ernesto 31. Byrd Polar Research Center, Ohio St Univ-Scott Hall#123, Columbus, OH, USA2. LEGOS, CNES, Toulouse, France3. JPL, NASA, Pasadena, CA, USAThe Surface Water and Ocean Topography satellitemission (SWOT, http://swot.jpl.nasa.gov/) is both atremendous opportunity for hydrology and a tremendousinvestment by CNES and NASA. What do we expect to learnfrom SWOT’s measurements? A driver of this knowledge willbe the geographic coverage of SWOT, whether that isconsidered locally across floodwaters or globally across thecontinents. As an example, consider floodwaters. Ourcurrent methods of measuring floodwater dynamics areeither sparsely distributed or temporally inadequate. Flooddepths are measured by using high water marks, whichcapture only the peak of the flood wave, not its temporalvariability. SWOT overcomes these limitations. Floodwatersare driven by fluvial processes, such as those of the Amazon,and by rainfall-runoff processes such as those of the Congo.Differentiating these flows is difficult when using DEMsand in-situ discharge estimates, given the geomorphiccomplexity of floodplains and of interfluvial wetlands.Instead, SWOT’s measurements of the water surface are adirect measurement of the flow hydraulics. This is atransformative measurement. It has yet to be made in anysubstantial way for any flood with any frame of consistency.Instead, it is inferred through modeling, wrack marks, anddischarge estimates, all of which are not sufficient. Nextconsider the water and energy cycle. The simple startingequation of deltaS = P – ET – Q belies the complexity ofmeasurements required to ensure closure. For example, just a1.0 mm/day error in ET over the Congo Basin translates to a35,000 m3/s discharge error in river flow. The annuallyaveraged flow of the Congo River is of the same order as thissuggested ET induced discharge error. Thus, knowing thedischarge of the Congo River and its many tributariesshould significantly improve our understanding of the waterbalance throughout the basin. The Congo is exemplary ofother basins around the globe. While science remains thecornerstone and driver of SWOT, there are applicationsoriented opportunities that also fit this geographic driver ofknowledge. For example, well over 100 rivers crossinternational boundaries, yet the sharing of water data ispoor. Overcoming this via SWOT measurements should helpto better manage the entire river basin while also providing abetter assessment of potential water related disasters.http://swot.jpl.nasa.gov/33Anderson, Martha C.A Satellite-Based Drought Product using ThermalRemote Sensing of EvapotranspirationAnderson, Martha C. 1 ; Hain, Christopher R. 2 ; Kustas,William P. 1 ; Mecikalski, John R. 3 ; Gao, Feng 11. US Dept Agr ARS, Beltsville, MD, USA2. NOAA/NESDIS, Camp Springs, MD, USA3. Atmospheric Sciences, U Alabama-Huntsville, Huntsville,AL, USAThermal infrared (TIR) remote sensing of land-surfacetemperature (LST) provides valuable information about thesub-surface moisture status: soil surface temperatureincreases with decreasing water content, while moisturedepletion in the plant root zone leads to stomatal closure,reduced transpiration, and elevated canopy temperatures. Inthis paper, a satellite-based methodology for routinedrought monitoring will be described using basin- tocontinental-scale maps of evapotranspiration (ET) obtainedwith a TIR-based surface energy balance model. In thisapproach, moisture stress is quantified in terms of thereduction of ET from the potential rate (PET) expectedunder non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model is used to mapland-surface water and energy fluxes across the continentalU.S. at 100m to 10km resolution using TIR imagery frompolar orbiting and geostationary satellites. A derivedEvaporative Stress Index (ESI), describing standardizedanomalies in the ET/PET ratio, shows good correspondencewith standard drought metrics and with patterns ofantecedent precipitation, but at significantly higher spatialresolution due to limited reliance on ground observations.The ALEXI ESI algorithm does not require precipitation orsoil texture information, unlike the Palmer Drought Index,the Standardized Precipitation Index, and other droughtindices based on rainfall or soil water balance. Being anindependent means for assessing drought conditions, theESI has significant potential for enhancing the existing suiteof drought monitoring products. Work is underway tofurther evaluate multi-scale ESI implementations over theU.S. and other continents with geostationary satellitecoverage.Andreadis, KonstantinosAssessing the information content of SWOTobservations for hydrologic estimationAndreadis, Konstantinos 1 ; Moller, Delwyn 2 ; Rodriguez,Ernesto 1 ; Durand, Michael 3 ; Alsdorf, Douglas 31. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA2. Remote Sensing Solutions, Sierra Madre, CA, USA3. Byrd Polar Research Institute, Ohio State University,Columbus, OH, USAThe Surface Water Ocean Topography (SWOT) satelliteobservations will include water surface elevation (WSE),slope and inundated area. Althought these are important intheir own right, measurements of river discharge are of key

importance to global hydrology. The SWOT mission willprovide data products of river discharge globally at anunprecedent spatial resolution (at least 100m), using twotypes of algorithms. One of these algorithms is based on adata assimilation framework, that ingests SWOTobservations into a hydrodynamic model and producesoptimal estimates of river discharge and other hydrualicvariables. In this study, results from a fraternal twinsynthetic experiment are presented where “true” WSEs aresimulated over the Ohio River basin, and are then fed intothe SWOT Instrument Simulator to produce syntheticsatellite observations over the same study area with thecorrect orbital and error characteristics. A “first-guess”simulation that emulates the measurement availability andmodeling capabilities globally, is produced by using asimpler model at a coarser spatial resolution with artificialerrors added to boundary inflows and river channelcharacteristics (geometry, roughness etc.). An EnsembleKalman Filter and Smoother are used to assimilate theSWOT observations into the “first-guess” (open-loop)model, and different configurations of the state vectors aretested. Assimilated estimates of river discharge and WSE areevaluated against the “true” values, and the impact of thepartial spatial coverage of SWOT at different times isassessed. In addition, the temporal persistence of the SWOT“corrections” to the “first-guess” discharge estimates isquantified and related to the river topology. AlthoughSWOT observations will be provided at 100m resolution, it ishypothesized that the assimilation will be able to downscalethat information to rivers smaller than that providingdischarge estimates upstream. Finally, the informationcontent of SWOT observations is evaluated for theestimation of other hydraulic variable such as river bedtopography and channel roughness.Anker, YaakovSmall stream monitoring by spectral classificationof high spatial resolution, digital RGB aerial imagesAnker, Yaakov 1, 3 ; Hershkovic, Yaron 2 ; Gasith, Avital 2 ; BenDor, Eyal 3 ; Livne, Ido 31. Samaria-Jordan Rift R&D, Ariel University Center, Ariel,Israel2. Zoology, Tel-Aviv University, Tel-Aviv, Israel3. Remote Sensing Laboratory, Tel-Aviv University, Tel-Aviv,IsraelAquatic plants proliferation in small streams is oftenmanaged by seasonal variables. Occasionally biomassesaccumulation might result in damming effect and over-bankflow. Under these circumstances habitat scale monitoring ofan entire stream section is essential for crops andinfrastructure destruction prevention. The present workevaluated the application of High Resolution RGB airbornedigital images spectral analysis (ADP-SA) for small streams(

accuracy of snow derivation from simulated daily VIIRSobservations. Another method implemented to analyze theperformance of snow algorithms utilizes high-resolutionobservations as an effective source of ground truthinformation for snow fraction. The algorithms developed bythe author were accepted to retrieve all VIIRS snow productsand have been successfully used to routinely generate dailyglobal maps of snow cover fraction at GSFC/NASA. Thequality of fractional snow cover retrieval was extensivelyvalidated and used for different applications includinghydrological studies of small arctic catchments. Snow coverareal depletion curves inferred from satellite observationswere validated and then applied in a catchment-based landsurface model for numerical simulations ofhydrometeorological processes. It has been shown thatpersistent snowdrifts on the arctic landscape, associatedwith a secondary plateau in the snow areal depletion curves,are hydrologically important. This provided the opportunityto apply the subgrid-scale snow parameterization inwatersheds subject to seasonal snow covers. To furtherimprove processing of satellite observations on snow, first ofall, it is proposed to implement scene-specific parameterscharacterizing local properties of snow and non-snowendmembers. Such an approach is applicable for global snowretrieval, when algorithms are adjusted on the fly to varyingregional conditions. But when snow detection from remotesensing is aimed at local applications including hydrological,it is possible to directly utilize properties of snow providedby conventional surface observations. Including local in situobservations on snow properties in remote sensingalgorithms could be considered as another form of synergyof conventional and remote sensing observations in additionto traditional integration of remote sensing data withsurface observation for the purpose of assimilation foratmospheric circulation in hydrological and snow processmodels. Improving snow retrieval is also related to the use ofsnow BRDF models. It has been demonstrated that means ofgeometric optics could reliably describe angulardependencies related to bidirectional snow reflectance, and asimple asymptotic analytical model could be used tocalculate bidirectional reflectance. The analytical modelrobustly reproduces directional reflectance even for largezenith angles. Possible applications of the asymptoticanalytical BRDF model for remote sensing includecalculating snow albedo and normalizing reflectances forthe purpose of remote sensing. The combination of scenespecificalgorithms with analytical BRDF model and synergyof remote sensing retrieval algorithms with conventionalobservations will help create unbiased and consistentinformation on snow cover not only required for globalstudies, but useful for regional and local scale hydrologicalapplications.Awange, JosephUnderstanding the Changes in the Nile Basin’sStored Water Patterns and Their Link to ClimateVariabilityAwange, Joseph 1, 4 ; Forootan, Ehsan 2 ; Bauer, Oliver 3 ; Heck,Bernhard 4 ; Abd-Elmotaal, Hussein 51. Spatial Sciences, Curtin University, Perth, WA, Australia2. Institute of Geodesy and Geoinformation, BonnUniversity, Bonn, Germany3. Space Research Institute, Austrian Academy of Sciences,Vienna, Austria4. Geodetic Institute, Karlsruhe Institute of Technology,Karlsruhe, Germany5. Civil Engineering Department, Minia University, Minia,EgyptWater resources of the Nile Basin are under intensepressure from both humans and the changing climate,leading to a decline in available water in a wide area of thebasin. The GRACE (Gravity Recovery And ClimateExperiment) has recently been used to monitor the storedwater within the Nile Basin. However, because of thedominant influence of some hydrological resources, e.g.,Lake Victoria Basin, detecting the hydrological signals fromother areas within the basin is extremely difficult. This studyapplies the Independent Component Analysis (ICA) tolocalize the changes in the Nile Basin’s stored water intotheir major patterns (e.g., Lake Victoria Basin, Ethiopianhighlands, Bar-El-Ghazal, and the Lake Nasser), thusallowing an in-depth analysis of these patterns. The relationbetween those patterns and El Nino Southern Oscillation(ENSO) and the Indian Ocean Dipole (IOD) are studied toassess the effects of climate variability on the major waterresources. TRMM (Tropical Rainfall Measuring Mission) andGlobal Land Data Assimilation System (GLDAS) data arealso analysed over the same period. The results indicate thatthat Lake Nasser not only loses water through evaporationbut also through groundwater flow in the north-eastdirection. The inter-annual variability of the stored watershow positive correlations to climate variability for the LakeVictoria Basin, Ethiopian highlands, and Bar-El-Ghazalindicating the influence of climate variability on the waterstorage changes within the Nile Basin.Bales, Jerad D.In Situ and Remotely-Sensed Hydroclimate Datafor Water- Resources ManagementBales, Jerad D. 11. U.S. Geological Survey, Reston, VA, USAWater resources are managed at the local to perhapsregional level, but data used for management, whenavailable, are measured continuously at a point orintermittently as a gridded data set that is not coincidentwith basin or political boundaries. Each approach offersadvantages, but integration of these data types has thepotential to vastly improve global water management.35

Numerous challenges remain, however, in integrating thesedata and providing them at scales appropriate for managingwater resources in a dynamic climate. Continuous in siturecords extend for more than 130 years in some locations ofthe U.S. These systematic records can never be duplicatedand are an invaluable source for understanding changes inthe environment. Moreover, archived hydroclimate data mayprove useful for purposes unimagined during networkimplementation, e.g., streamflow data initially collected forwater development in the U.S. West now provide the longestsystematic record of climate variability and change.Development of water budgets in the natural and engineeredenvironment remains a challenging problem, and must beinformed by data from remotely-sensing, in situ sensors, andmodels. The U.S. Geological Survey Water Census initiativehas, for example, a goal to develop water budgets for all HUC12 (hydrologic unit code) watersheds in the U.S. A piloteffort for water budget development recently was completedin the U.S. portion of the Great Lakes watershed, anddemonstrates the challenges of developing water budgets atthis scale. One challenge in water budget development isthat many important processes, e.g., evapotranspiration,cannot be directly measured. Process understanding requiresdata at the scale of the process in order develop models thatcan be used to predict effects of changes on water budgets.Data collected using in situ sensors play a critical role inprocess understanding and extension of this understandingto predictive models. Aspects of the engineered waterenvironment are not measured and must be estimatedthrough statistical sampling, models, and basinwide data,available only through remote sensing. Water quality is animportant aspect of water availability. In order to accuratelypredict the quality of water leaving a particular reservoir (i.e.,unsaturated zone, etc.), it is necessary to understand andquantify the water movement through that reservoir. This,again, requires process understanding that is dependent onthoughtfully collected in situ data and models to extrapolateto meaningful spatial scales. Although recent progress hasbeen made, there is tremendous need and opportunity fornew sensors for measuring key water-quality parameters. Thetransition of new data types and modeling results to watermanagement requires a deliberate effort. Whereas, forexample, a point rainfall amount is readily understood bywater managers, integrated, multi-sensor products that offermuch more information than a single measure currently arerarely appreciated or used in operational activities. Newsensors, more sophisticated models, and increasinglyresolved remotely-sensed data are exciting scientificchallenges, but this new information also must be madereadily available for water management and archived in aconsistent and accessible manner for future analyses.Barnes, MalloryDetection of Spatial and Temporal Cloud CoverPatterns over Hawai’i Using Observations fromTerra and Aqua MODISBarnes, Mallory 1 ; Miura, Tomoaki 1 ; Giambelluca, Thomas 2 ;Chen, Qi 21. NREM, University of Hawaii - Manoa, Honolulu, HI, USA2. Geography, University of Hawaii - Manoa, Honolulu, HI,USAAn understanding of patterns in cloud cover is essentialto analyzing and understanding atmospheric and hydrologicprocesses, particularly evapotranspiration. To date, there hasnot yet been a comprehensive analysis of spatial andtemporal patterns in cloud cover over the Hawaiian Islandsbased on high resolution cloud observations. The MODISinstruments aboard the Aqua and Terra satellites have thepotential to supply the necessary high resolutionobservations. The MODIS instrument has a spatialresolution of 250m in bands 1-2, 500m in bands 3-7, and1000m in bands 8-36 and acquires data continuously,providing global coverage every 1-2 days. The objectives ofthis study were to generate high resolution cloud cover datafrom the Terra MODIS satellite sensors and to evaluate theirability to detect the spatial patterns of cloudiness and theirdiurnal changes over the Hawaiian Islands. The TerraMODIS cloud mask product (MOD35) was obtained for themonth of January for three years (2001 – 2003). MOD35provides cloudiness data at 1km resolution twice per day(once in the morning and once at night). Monthly statisticsincluding mean cloud cover probability at each of the twooverpass times were generated by processing the dailyMOD35 cloudiness time series. The derived monthlystatistics were analyzed for diurnal changes in total amountand spatial patterns of cloudiness. Our results indicated thatthere were consistent differences in the diurnal cycle betweenwindward and leeward sides of the main Hawaiian Islands.In general, the windward sides of the islands were cloudier atnight than during the day. The leeward sides of the islands,on the other hand, were generally less cloudy at night thanduring the day. On Hawai’i, the windward (Hilo) side of theisland was cloudier at nighttime than during the day. Theleeward (Kona) side, in contrast, was less cloudy at nighttimethan during the day. The pattern was similar on Oahu,where the windward sides of the island were cloudier atnight but the leeward sides and central portion of the islandwere less cloudy at night than during the day. Kauai andMolokai demonstrated the pattern as well, with thewindward side of both islands more cloudy at night and theleeward sides less cloudy at night. Overall, there was morecontrast between cloudiness on windward and leeward sidesat nighttime than during the day. These results appeared tocorrespond with existing knowledge of the diurnal variationin precipitation. We conclude that MODIS 1 km daily cloudmask data can provide spatial patterns of cloud cover overthe Hawaiian Islands in detail. We plan to extend ouranalysis to include the Aqua MODIS cloud product(MYD35), process the full MODIS record (10+ years) for36

seasonal trends, and integrate cloud cover data from theGeostationary Environmental satellites for an improvedtemporal resolution.Baugh, CalumUsing field data to assess the effectiveness ofadjusted spaceborne derived DEMs for replicatingAmazon River floodplain hydro-dynamicsBaugh, Calum 1 ; Yamazaki, Dai 2, 3 ; Hall, Amanda 1 ; Bates,Paul 1 ; Schumann, Guy 11. School of Geographical Sciences, University of Bristol,Bristol, United Kingdom2. Institute of Industrial Science, The University of Tokyo,Tokyo, Japan3. Byrd Polar Research Center, Ohio State University,Columbus, OH, USAHydro-dynamic modelling requires accurate DEM datato provide the topographic boundary condition. In the caseof the Amazon, vegetation distortion of the only suchavailable dataset (SRTM) can degrade the accuracy of thismodelling. However the extent of these impacts are not yetfully understood because of the lack of hydro-dynamic fieldobservations from the floodplain. Such field data can beused firstly to identify the original impact of vegetationdistortion upon a hydro-dynamic simulation. Second, it canassess the effectiveness of DEM adjustment algorithms atremoving the distortion. Therefore, to address this issue thefollowing data were collected within the floodplain 250 kmupstream from Manaus on the central Amazon mainstemduring July 2011; flow velocity, direction and depth, watersurface elevation and tree height. A hydro-dynamicsimulation using the LISFLOOD-FP model was thenperformed using the original SRTM DEM. Comparing thesimulation results to the field flow data showed pooragreement, for example the velocity gradients differed by twoorders of magnitude. Therefore a version of the SRTM DEMfrom Yamazaki et al., (submitted to J. Hydrol) who adjustedit to better include floodplain channels was used. Thisdemonstrated greater agreement between the field flow dataand the model in areas of channelized floodplain flow.However a comparison of water surface elevations betweenthe field and modelling data showed that vegetationdistortion still remained in the adjusted DEM. A vegetationcorrection method, validated using the tree height field data,was then applied to the adjusted DEM. The results showedthe greatest agreement between the field and modellingdata. This work therefore shows how floodplain hydrodynamicdata collected in the field can be used to validateand correct an adjusted DEM in the context of hydrodynamicsimulations of large remote rivers.Becker, Matthew W.Wetlands as Groundwater Piezometers in BorealForestsBecker, Matthew W. 1 ; Babonis, Gregory S. 2 ; Fredrick, Kyle C. 31. Dept Geological Sciences, California State Long Beach,Long Beach, CA, USA2. Geology, University at Buffalo, Buffalo, NY, USA3. Department of Earth Sciences, California University ofPennsylvania, California, PA, USABoreal forests are considered a critical component ofglobal carbon cycling. Groundwater plays an important partin boreal forests as depth to water table influencesbiodiversity and groundwater discharge provides droughtresistance and nutrients for plants. Understanding howgroundwater influences these remote ecologicalenvironments on a sub-continental scale requires the use ofremote sensing combined with hydrologic models. Wepresent an example of such an application, in whichwetlands and seepage lakes are used as groundwaterhydraulic head observations in a numerical flow model. Thetest area is the Northern Highland Lakes Region ofWisconsin, USA, which is a southern boreal / temperateforest biome punctuated by kettle lakes, wetlands, and bogs.These surface water features are often well connected togroundwater so can serve as measurements of groundwaterhydraulic head which, in turn, can be used to determinegroundwater flow and storage and its potential forbiogeochemical transport. The key is to isolate those featuresthat are hydraulically connected to groundwater and thenmake accurate elevation measurements of their surface. Toisolate seepage lakes that were well connected togroundwater we used thermal band temperaturemeasurements from the ASTER satellite. We used AIRSAR toseparate open wetlands from mixed wetlands so thataccurate elevations measurements could be made. Wecompared SRTM elevations to ground-based measurementsof elevation and investigated their influence of theiraccuracy on a 900 square kilometer numerical flow model.These investigations indicate that seepage lakes, wetlands,and bogs are effective measurements of ground-waterelevations, but in flat-lying areas small errors in surfaceelevations can have significant impacts on groundwater flowmodels. Rigorous classification of remotely sensed surfacewater features is, therefore, critical to confident prediction ofgroundwater flow and biogeochemical transport. Radarband imaging is particularly useful tool locating suitablepoints of water elevation measurements in lakes, wetlands,and bogs.37

Bekkam, Venkateswara RaoGroundwater and Surface Water Storage Dynamicsin the Musi River IndiaBekkam, Venkateswara Rao 1 ; Vajja, Varalakshmi 21. Centre for Earth Atmosphere an, JNT University,Hyderabad, India2. Centre for water resources, JNT University Hyderabad,Hyderabad, IndiaHimayatsagar and Osmansagar reservoirs are supplyingdrinking water to the Hyderabad city India. It has beenobserved that there is a continuous decrease of inflows tothese reservoirs in the recent past (1961 -2009). The fact thatthe Hyderabad City is very close (9.0 km) to the catchmentsof Osmansagar and Himayathsagar reservoirs, there may belot of demand for agricultural produce (such as vegetables,grains, pulses etc.) that must be necessarily being suppliedfrom these catchments by tapping more surface andgroundwater by the farmers in the catchments, resulting inthe reduction of inflows to the reservoirs. For theverification of this hypothesis, an analysis has been carriedout by calculating NDVI (Normalized Difference VegetationIndex ) using the medium to high spatial resolution multispectral data provided by remote sensing satellites, such asLandsat TM, IRS-1C/1D LISS-III and IRS-P6 LISS-III for theyears 1989, 1994, 1998, 2002 and 2008 for the kharif ( June-October: monsoon period) season, and in the years 1975,1994, 1998, 2003 and 2008 for rabi (November-April: nonmonsoon period) season. From the NDVI analysis it is foundthat, in the kharif season the total cropping area recorded anincrease of 25.8% and reservoirs/ tanks/ lakes occupied withwater got reduced by 43% from 1989 to 2008. As against this,in the rabi season during the period 1975 - 2008, the totalcropping area increased by 141.32%, while water-coveredareas of reservoirs/ tanks/ lakes got reduced by 67.47%. Thismeans that during the Rabi season Groundwater is beingincreasingly utilized in the catchments for irrigation due tonon- availability of surface water, thereby depleting thegroundwater seriously. Consequently the inflows werereduced to the reservoirs in the recent years due to the factthat whatever the rainfall that occurs in the catchment, it isfirst utilised for meeting the depleted soil moisture andgroundwater, thereby reducing the surface runoff. This facthas been further investigated with the analysis ofgroundwater levels and proved that the deeper thegroundwater levels the more the recharge in the in thecatchmentsBenedict, SamValidation and Application of Remote SensingData as part of a Joint Cross-cutting Initiative bythe Global Energy and Water Cycle Experiment(GEWEX) Hydroclimatology Panel’s (GHP’s)Regional Hydroclimate Projects (RHPs)Benedict, Sam 1 ; van Oevelen, Peter 11. International GEWEX Project Office, Coronado, CA,USAThe vision statement of the Global Energy and WaterCycle Experiment (GEWEX) states that fresh water is a majorpressure point for society owing to increasing demand andvagaries of climate. Extremes of droughts, heat waves andwild fires as well as floods, heavy rains and intense stormsincreasingly threaten to cause havoc as the climate changes.Other challenges exist on how clouds affect energy andclimate. Better in-situ and remote sensing observations andanalysis of these phenomena, and improving our ability tomodel and predict them will contribute to increasinginformation needed by society and decision makers forfuture planning. The Regional Hydroclimate Projects (RHPs)that are part of the GEWEX Hydroclimatology Panel (GHP)are a source of hydrologic science and modeling withinGEWEX. GHP, through its network of Regional Projects,provides flux site data sets for different regions, seasons andvariables, that can be used to evaluate remote sensingproducts with energy, water and carbon budget components.In turn, the scope of the contribution made by the RHPsthrough the application of in-situ and remote sensing dataincludes advances in seasonal forecasting, the detection andattribution of change and the development and analysis ofclimate projections. Challenges also remain for GHP indefining a cooperative framework in which to deal withmonsoons and to help coordinate the multitude of nationaland regional initiatives in this area. GHP and the RegionalHydroclimate Projects are poised to meet these challengesand contribute in a number of ways to the other majorissues associated with improved understanding of the role ofwater and energy in the climate system. We will report on theRHPs and how they assist in the improvement of remotesensing data products for climate research and how theyapply remotely sensed data to answer regional climatequestions.Bennartz, RalfMeasuring High-latitude Precipitation From SpaceBennartz, Ralf 11. Dept Atmos & Ocenic Sciences, Univ Wisconsin,Madison, WI, USAOver the last years our capabilities to remotely sensehigh-latitude precipitation have increased. Significantprogress has been made in particular in three areas. Firstly,new in-situ and ground-based remote sensing techniquesallow us to better specify snowfall size distribution, fallspeed, and particle shapes. Secondly, our understanding of38

a single mission, the phrase “near-real-time” within thiscontext refers to an effective latency of approximately 5 to 15days. For the last few years of the mission, the GRACEscience data system has been producing near real-timeestimates of the Earth gravity field on a best-effort basis,using automated processes. The Level-1B tracking data,produced for monitoring the health of the flight system, isbeing opportunistically used for producing these gravityfield estimates. The short latency, and process automation,implies that the ancillary data and models used in thisprocessing cannot be put to the same scrutiny as theoperational Level-2 gravity field data products. Theseproducts have so far been used for correlative interpretationwith other remote-sensing and in situ data during floods inthe Amazon (spring 2009), Pakistan (fall 2009), and inQueensland, Australia (winter 2010). This paper, after a briefpresentation of the processing approach, will focus on thechallenges imposed on the interpretation of these lowlatencydata products due to processing methods and due tothe choice of background models.Billah, Mirza M.Impacts of Different Evapotranspiration Estimateson Quantify Regional Scale Terrestrial WaterStorageBillah, Mirza M. 1 ; Goodall, Jonathan L. 1 ; Narayan, Ujjwal 2 ;Lakshmi, Venkat 11. Civil and Environmental Engg., University of SouthCarolina, Columbia, SC, USA2. Department of GIS, Richland County, Columbia, SC,USAEvapotranspiration is difficult flux to quantify atregional spatial scales. It is a crucial component of terrestrialwater balance, which is important to estimate wateravailability and sustainable water resources management. Wetest three different approaches for estimatingevapotranspiration and evaluate how well each approachperforms at closing the water budget for sub-watersheds thatrange in size from 1.2 km2 to 3350 km2 in South Carolina.The Variable Infiltration Capacity (VIC) model, NorthAmerican Regional Reanalysis (NARR) program and remotesensing derived estimates are used for evapotranspiration.Results from the analysis show that all the three methods forestimating evapotranspiration produce similar variation inseasonal water storage (positive in fall and winter, negative inspring and summer), but differences exist in the magnitudeand spatial patterns of the estimates. In the spring andsummer months, relatively low evapotranspiration rates wereestimated by remote sensing as compared to VIC and NARRmodels. The remotely sensing evapotranspiration in fall andwinter months fell between the higher VICevapotranspiration and the lower corrected NARRevaporation estimates. We compared our estimates of changein terrestrial water storage using the threeevapotranspiration estimates with drought indices providedby the Drought Monitor (DM) program and observedgroundwater levels as independent means for validating theestimates. On an annual and seasonal basis, the change interrestrial water storage estimated using remote sensingevapotranspiration was consistent with annual and seasonaldrought variation recorded by the DM program.Comparison with groundwater levels showed that remotesensing evapotranspiration approach resulted in the highestcorrelation among the three estimates of evapotranspiration.We conclude from this study that remote sensing is morereliable and consistent at estimating regional scaleevapotranspiration as compared to the two model-basedestimates in our study area.Bitew, Menberu M.Can One Use Streamflow Observations as a Way ofEvaluating Satellite Rainfall Estimates?Bitew, Menberu M. 1 ; Gebremichael, Mekonnen 11. Civil & Environmental Engineering, University ofConnecticut, Storrs, CT, USAObserved streamflow data are increasing used as a wayof evaluating the accuracy of satellite rainfall estimates,particularly in gauged watersheds where there are no reliableground-based rainfall measuring sensors. The procedureconsists of (1) calibrating hydrologic models with satelliterainfall inputs, (2) using satellite rainfall estimates as inputsinto hydrologic model, and (3) comparison of simulated andobserved streamflow. The authors investigated the feasibilityof this approach for two watersheds within the Blue NileRiver Basin in Ethiopia: Gilgel Abay Watershed (Area of1,656 km2, rainfall accounting for 71% of streamflow), andBlue Nile River Basin (Area of 176,000 km2, rainfallaccounting for 20.4% of streamflow). The approach was putto test to evaluate PERSIANN rainfall estimates, which hadlarge underestimation biases as found out throughcomparison with rain gauge values. The approachsuccessfully detects the underestimation bias in the GilgelAbay watershed, but fails to detect it in the Blue Nile Riverbasin. Apparently, in the Gilgel Abay Watershed,precipitation is a significant portion of the streamflow, andany errors committed in the model parameter estimatespertaining to evapotranspiration and groundwater flow(during calibration phase due to lack of these datasets)cannot hide the substantial bias in the rainfall estimates.However, in the Blue Nile River Basin, precipitation is asmall portion of the streamflow, and any errors committedin model parameter estimates can easily hide the substantialbias in the rainfall estimates. The authors recommend thatstrong caution be exercised in using observed streamflow toevaluate the accuracy of satellite rainfall estimates inwatersheds where precipitation is only a small fraction of thestreamflow. In the absence of reliable model parameterestimates pertaining to evapotranspiration and groundwater,the authors recommend against the use of streamflowobservations a way of evaluating satellite rainfall estimates inregions where precipitation is not a large portion of thestreamflow.40

Bolten, John D.Evaluation of the Middle East and North AfricaLand Data Assimilation SystemBolten, John D. 1 ; Rodell, Matt 1 ; Zaitchik, Ben 11. Hydrological Sciences Lab, NASA GSFC, Greenbelt, MD,USAThe Middle East and North Africa (MENA) region isdominated by dry, warm deserts, areas of dense population,and inefficient use of fresh water resources. Due to thescarcity, high intensity, and short duration of rainfall in theMENA, the region is prone to hydroclimatic extremes thatare realized by devastating floods and times of drought.However, given its widespread water stress and theconsiderable demand for water, the MENA remains relativelypoorly monitored. This is due in part to the shortage ofmeteorological observations and the lack of data sharingbetween nations. As a result, the accurate monitoring of thedynamics of the water cycle in the MENA is difficult. TheLand Data Assimilation System for the MENA region(MENA LDAS) has been developed to provide regional,gridded fields of hydrological states and fluxes relevant forwater resources assessments. As an extension of the GlobalLand Data Assimilation System (GLDAS), the MENA LDASwas designed to aid in the identification and evaluation ofregional hydrological anomalies by synergistically combiningthe physically-based Catchment Land Surface Model (CLSM)with observations from several independent data productsincluding soil-water storage variations from the GravityRecovery and Climate Experiment (GRACE) and irrigationintensity derived from the Moderate Resolution ImagingSpectroradiometer (MODIS). In this fashion, we estimate themean and seasonal cycle of the water budget componentsacross the MENA.Borak, JordanA Dynamic Vegetation Aerodynamic RoughnessLength Database Developed From MODIS Imageryfor Improved Modeling of Global Land-Atmosphere ExchangesBorak, Jordan 1, 2 ; Jasinski, Michael F. 21. Earth System Science Interdisciplinary Center, Universityof Maryland, Greenbelt, MD, USA2. Hydrological Sciences Laboratory, NASA Goddard SpaceFlight Center, Greenbelt, MD, USAA new global database of seasonally varying vegetationaerodynamic roughness for momentum is being developedfor all global land areas by combining a physical model ofsurface drag partition with MODIS vegetation dataproducts. The approach, previously published in Jasinski etal. (2005) and Borak et al. (2005), utilizes Raupach’s (1994)roughness sublayer formulation, employing specific dragparameters developed for each MODIS land cover type. Theprocedure yields a unique vegetation roughness length (z0)and zero-plane displacement height (d0), on a pixel-by-pixelbasis, on the basis of land cover type, canopy area index, andcanopy height. Time series roughness quantities arecurrently being computed at 1 km resolution for all globalland regions for each MODIS 8-day compositing period forthe 10 complete years of data available for the MODISperiod of record (2001-1010). The new dynamic satellitebasedroughness fields, when employed within large-scalehydrologic, mesoscale and climate models, are expected toimprove representation of surface fluxes and boundary layercharacteristics, compared to models that utilize a traditionalroughness look-up table. The roughness formulation isvalidated using published roughness data from past fieldexperiments.Borsche, MichaelEstimation of high Resolution Land Surface HeatFlux Density Utilizing Geostationary Satellite DataBorsche, Michael 1 ; Loew, Alexander 11. Max Planck Institute for Meteorology, Hamburg,GermanyIn this study a flexible framework is presented whichallows for the estimation of land surface energy and waterfluxes based mainly on remote sensing satellite observationsas input. Major data input is taken from geostationarysatellite observations which are available at a very hightemporal (30min) and moderate spatial (5x5km) resolutionfrom the ISCCP reprocessing effort. The land surface schemeconsists of a single layer surface resistance model which isdriven by consistent input from remote sensing observationsand is constrained by remote sensing based observations ofsurface skin temperature and soil moisture. The coupling ofthe land surface model with a dynamic boundary layermodel implements an additional constraint to the surfaceflux estimations. The paper is focused on the evaluation ofthe estimated heat fluxes at the global scale. The heat fluxestimates are validated against globally selected eddycovariance measurements from stations of the FLUXNETflux station network. Specific experiments are presented thatdisentangle the various sources of uncertainties in the usedsatellite forcing data and propagate these uncertainties toerrors of latent heat fluxes. Finally we present a quasi-globalmulti-year latent heat flux record and its correspondinganomalies to demonstrate the climate applicability of theframework.Bounoua, LahouariCentury Scale Evaporation Trend: AnObservational StudyBounoua, Lahouari 11. Bospheric Sciences Branch, Code 691 SSED, Greenbelt,MD, USASeveral climate models with different complexityindicate that under increased CO2 forcing, runoff wouldincrease faster than precipitation overland. However,observations over large U.S watersheds indicate otherwise.This inconsistency between models and observationssuggests that there may be important feedbacks between41

climate and land surface unaccounted for in the presentgeneration of models. We have analyzed century-scaleobserved annual runoff and precipitation time-series overseveral United States Geological Survey hydrological unitscovering large forested regions of the Eastern United Statesnot affected by irrigation. Both time-series exhibit a positivelong-term trend; however, in contrast to model results, thesehistoric data records show that the rate of precipitationincreases at roughly double the rate of runoff increase. Weconsidered several hydrological processes to close the waterbudget and found that none of these processes acting alonecould account for the total water excess generated by theobserved difference between precipitation and runoff. Weconclude that evaporation has increased over the period ofobservations and show that the increasing trend inprecipitation minus runoff is correlated to observed increasein vegetation density based on the longest available globalsatellite record. The increase in vegetation density hasimportant implications for climate; it slows but does notalleviate the projected warming.Boy, Jean-PaulMonitoring surface and sub-surface mass changesin Africa using high resolution GRACE masconsolutions and altimetryBoy, Jean-Paul 1 ; Carabajal, Claudia C. 2, 3 ; Lutcke, Scott B. 2 ;Rowlands, David D. 2 ; Sabaka, Terence J. 2 ; Lemoine, FrankG. 21. IPGS (UMR 7516 CNRS-UdS), EOST, Strasbourg, France2. Planetary Geodynamics Lab., Code 698, NASA GoddardSpace Flight Center, Greenbelt, MD, USA3. Sigma Space Corporation, Lanham, MD, USASince its launch in March 2002, Gravity Recovery AndClimate Experiment (GRACE) has recovered mass variationsat the Earth’s surface with unprecedented temporal andspatial resolution. We invert directly mass variations fromthe inter-satellite K-band range rate (KBRR) data using alocalized mascon (mass concentrations approach. Usingappropriate constraints, our regional solutions allow bettertemporal (10 days) and spatial (2 degree) resolutions, thanthe classical spherical harmonic solutions. We compare oursolutions to global and regional hydrology models, with aparticular emphasis on the Western Africa monsoon area,where regional models were produced in the context ofALMIP (the AMMA Land-surface Model Inter-comparisonProject). We see that GRACE also captures the currentdrought in Eastern Africa, in agreement with other spacederivedprecipitation and soil-moisture measurements.Thanks to decade of radar altimetry (Topex/Poseidon, Jason-1 & -2 or Envisat), and more recently laser altimetry(ICESat), surface water level variations for major lakes andreservoirs are monitored with a few-centimeter accuracy. Wecompare our GRACE estimates of mass variations of majorlakes and reservoirs in Africa to estimates deduced fromaltimetry measurements. The agreement is larger whencontinental hydrology models, such as GLDAS (Global LandData Assimilation System), which do not include surfacewaters and ground waters, are forward-modeled prior to theinversion of KBRR data. Forward modeling with modelssuch as GLDAS also allows for better retrieval ofgroundwater changes, for example in Northern Africa.Braun, AlexanderOn the Correlation Between Glacier Melting andLake Level Change on the Tibetan Plateau fromAltimetry and GRACEBraun, Alexander 1 ; Duan, Jianbin 2 ; Cogley, Graham 4 ; Lee,Hyongki 3 ; Shum, C. K. 21. Deptartment of Geosciences, The University of Texas atDallas, Richardson, TX, USA2. School of Earth Sciences, The Ohio State University,Columbus, OH, USA3. Civil and Environmental Engineering, University ofHouston, Houston, TX, USA4. Department of Geography, Trent University,Peterborough, ON, CanadaThe Tibetan Plateau (TP) hosts about 37,000 glacierscovering a region of 50,000 km^2. Increasing temperaturesat a rate of 0.3 degrees Celsius per decade in the last 30 yearshave led to significant amounts of melt water with run-offinto several hundred large lakes which on average indicaterising lake levels at a rate of 0.25 m/year (Zhang et al, 2011).The Chinese Glacier Inventory lists 50,000 ice coveredpolygons on the TP, 4000 of those are crossed by ICESatlaser altimetry tracks, and 70 glaciers have more than 100footprints between 2003-2009. We conduct a glacierelevation change analysis from ICESat near-repeat tracksusing up to 19 epochs between March 2003 and October2009. Results in regions covered by in situ mass balanceestimates show excellent agreement with the elevationchange estimates, e.g. ice elevations of the Lhagu glacierchange at a rate of -0.85 m/year compared to fieldobservations for 4 neighboring glaciers at -0.9 m waterequivalent (Yang et al, 2008). We correlate elevation loss withlake level change considering the snow depth change,although the dry climate does not produce significant snowdepth variability. Lake levels are determined using ICESatlaser altimetry, Envisat radar altimetry, and GRACEgravimetry. The estimated contribution of glacier melting tosurface water change will eventually shed light onunderstanding the mass change processes acting on the TPin terms of separating solid Earth, hydrosphere andcryosphere components.Brisco, BrianWetland Coherence for Water Level EstimationBrisco, Brian 1 ; Wdowinski, Shimon 2 ; Murnaghan, Kevin 1 ;Ahern, Frank 3 ; Kaya, Shannon 11. CCRS, Ottawa, ON, Canada2. Univeristy of Miami, Miami, FL, USA3. TerreVista Earth Imaging, Cormac, ON, CanadaINSAR is a mature technology being used operationallyfor a variety of applications including volcano monitoring,42

land subsidence monitoring, DEM generation, andearthquake impact assessment. Recent research hasdemonstrated the potential to apply this technique to waterlevel estimation in wetlands with suitable vegetation andhydrologic characteristics. This is particularly true forwetlands with stable double bounce scattering from areas offlooded vegetation. This presentation will review the wetlandand hydrologic characteristics that lead to suitablecoherence from Lake Clear watershed which is a mixed forestsite in Ontario and the Everglades National Park in Florida.The approach will be demonstrated with a number ofexamples using RADARSAT and Terra-SAR data from boththese sites for a variety of wetland types including mangrovemarshes, cattail and bulrush marshes, as well as saw-grassand mixed forest swamps. The processing methodology toproduce the coherence and the interferograms will beoutlined as well as the wetland characteristics resulting inhigh coherence for the two study sites. On-going researchactivities which are working towards bringing this approachto an operational status will be described including the useof in-situ corner reflectors for phase calibration.Brisco, BrianMapping Surface Water and Flooded Vegetationusing SAR Remote Sensing for Critical Ecosystemsin North AmericaKaya, Shannon 1 ; Brisco, Brian 1 ; White, Lori 1 ; Gallant, Alisa 2 ;Sadinski, Walt 3 ; Thompson, Dean 41. Natural Resources Canada, Canada Centre for RemoteSensing, Ottawa, ON, Canada2. United States Geological Survey, Earth ResourcesObservation and Science (EROS) Center, Sioux Falls, SD,USA3. United States Geological Survey, Upper MidwestEnvironmental Sciences Center, La Crosse, WI, USA4. Natural Resources Canada, Canadian Forest Service,Sault St. Marie, ON, CanadaSurface water constitutes a considerable proportion offreshwater sources in North America. Global change,however, is resulting in modifications to hydrologic systemswhich are impacting the landscape characteristics of wetlandecosystems on both an inter-seasonal and annual basis. Thedeterioration of water quality, overexploitation of freshwaterresources, hydrological hazards and adverse effects oflandscape degradation have an effect on the functioning ofcritical ecosystems and their suitability as cohesivelandscapes for several species at risk. The Terrestrial WetlandGlobal Change Research Network (TWGCRN), led by theUnited States Geological Survey, is studying landscaperesponses to climate/global change across a vital portion ofNorth America in the United States and Canada using anintegrated approach which includes the use of multiplesources of geospatial information to understand thedynamic conditions at specific network study sites.Assessments of landscape conditions are being conducted ona range of variables measured in situ and via airborne andspace-borne sensors, including SAR systems. Over the past 3seasons (2009, 2010, 2011), the Canada Centre for RemoteSensing has collected a comprehensive set of RADARSAT-2data over key TWGCRN study sites in Canada and theUnited States. For each site, RADARSAT-2 Fine Quad-Polmode multi-temporal data were acquired to satisfy the needfor identifying surface water extent and temporal/seasonalchange, as well as flooded vegetation extent and changeassociated with wetland landscape features. Semi-automatedmodels were developed to extract surface water informationfor each acquisition using a magnitude thresholdingapproach. The single-look complex polarimetric data wassubsequently processed using the Freeman-Durdendecomposition algorithm to identify areas associated withthe double bounce scattering mechanism. The modelsdeveloped, validated, and explained in this paper show greatpromise towards operational characterization of bothsurface water and flooded vegetation changes over time, asassociated with critical wetland areas. Results to date showthat SAR remote sensing can help provide a betterunderstanding of surface water extent and temporal change.Derived products will serve as important inputs tounderstanding hydrological dynamics within criticalecosystems.Brubaker, Kristen M.Multi-scale lidar greatly improve characterizationof forested headwater streams in centralPennsylvaniaBrubaker, Kristen M. 1, 2 ; Boyer, Elizabeth 21. Center for Sustainability Education, Dickinson College,Carlisle, PA, USA2. School of Forest Resources, The Pennsylvania StateUniversity, University Park, PA, USAMost current hydrographic data used in GeographicInformation Systems (GIS) have been derived by digitizingblue line streams from USGS topographic maps or bymodeling streams using traditional digital elevations models(DEMs) in GIS. Both methods produce stream models thatlack detail and accuracy, particularly in headwater streams.In addition to channel network delineation, anotherhydrologic attribute that is of interest to hydrologists,modelers, and ecologists, is topographic index (TI) asmeasured by the formula ln(a/tan). This metric and itsdistribution is an important component to the hydrologicmodel TOPMODEL and other hydrologic models, but is alsoused extensively to represent soil moisture in fields ofecology, forestry, and soil science. Newly available lidar dataavailable statewide in Pennsylvania can produce DEMs withan accuracy and resolution that far exceed previouslyavailable elevation data. In this study, streams were modeledusing lidar-derived DEMs of 1 m, 3 m, and 10 m resolutionsusing existing GIS software programs and compared to bothactual streams and streams modeled using a 10 meterNational Elevation Dataset (NED) DEM. Results showedthat the most accurate stream locations could be modeledusing a lidar-derived DEM thinned to 3m resolution orsmoothed using a mean smoothing filter. Also, when a 10 m43

esolution lidar-derived DEM was compared to the NED 10m resolution DEM, the streams delineated with the 10 mlidar data were significantly better than those modeled withthe 10 m NED data, showing that significant improvementin accuracy can be achieved with no increase in data storage.When topographic index was modeled with multipleresolutions of lidar-derived DEMs, the spatial and statisticaldistributions were both very different, with finer resolutionDEMs not accurately modeling areas of high TI.Additionally, depending on the flow accumulationalgorithm used, there were differences in the change instatistical resolution with response to initial DEMresolution.Brutsaert, WilfriedSome Indirect Estimates of Changes in HydrologicConditions During the Past Century INVITEDBrutsaert, Wilfried 11. Civil & Environmental Eng, Cornell Univ, Ithaca, NY,USAThe water budget of a natural river basin can beformulated as P - Q - E = dS/dt, where P is the precipitationrate, Q the net surface outflow rate per unit area, E theevaporation rate and S the water stored per unit area in thebasin. The variables P and Q can be and have been measureddirectly and many long-term data sets are available for basinsall over the world, with which their evolution over time canbe studied in great detail. The construction of reliable longterm data sets for E and S for climate change purposes ismore challenging; indeed, the direct and routinemeasurement of these variables is still very difficult, so thatin practice to gain information on past trends they mustinvariably be estimated by indirect methods. In the case of E,attempts have been made to estimate past trends oflandscape evaporation from available pan evaporationrecords. Because pan and landscape evaporation areintrinsically different especially under drying conditions,there is still no unanimity regarding the interpretation ofthese studies. In the case of S, it is generally agreed thatterrestrial storage in a basin is related to the baseflows or dryweather river flows from the basin; this has allowed todocument the evolution of groundwater storage in manylarge basins under widely different climate conditions fromavailable streamflow records. While these approaches toestimate E and S involve obvious challenges, they can beovercome.Castro, Lina M.Assessment of TRMM Multi-satellite PrecipitationAnalysis (TMPA) in the South of Chile’s AndesMountainsCastro, Lina M. 1 ; Miranda, Marcelo 2 ; Fernandez, Bonifacio 11. Department of Hydraulic and EnvironmentalEngineering, Pontificia Universidad Catolica de Chile,Santiago de Chile, Chile2. Department of Forest Science, Pontificia UniversidadCatólica de Chile, Santiago De Chile, ChilePrecipitation is the most crucial variable in applicationof hydrological models because it provides most of themoisture input for hydrologic processes over land.Hydrological models require accurate rainfall data at thehighest possible resolution for streamflow predictions.Nevertheless, due to the high variability in space and time ofprecipitation it is necessary to have a dense rain gaugesnetwork to achieve high accuracy. The gauge network inChile is sparse or nonexistent, especially in the AndesMountains where the most Chilean rivers are born.Although the rain gauges have the advantage of a hightemporal resolution, the scarcity and difficulty of getting thedata in real time limit their application into hydrologicalmodels for simulation and forecasting in real time. This gapcan be solved using data from space-borne sensors. In recentyears, several satellite-based, near global, high-resolutionprecipitation estimates have become available withincreasing temporal and spatial resolution. Rainfallestimates from space-borne sensors offer a valuable source ofinformation for capturing the rainfall and for understandingof terrestrial rainfall behavior over some regions that areungauged like some parts of the Andes Mountains. Thepresent work aims to assess the rainfall estimations ofTropical Rainfall Measurement Mission (TRMM) MultisatellitePrecipitation Analysis (TMPA) in a region in theSouth of Chile over the Andes Mountains. The assessmentbetween TMPA product and gauge measurements was madeusing statistical error (Bias, Root Mean Square Error, andCorrelation Coefficient) and detection measurements (FalseAlarm Ratio - FAR and Frequency Bias Index - FBI). TheTMPA product represents 50% of total rainfall in almost allground truth stations, with the highest bias values in winterseason. When the TMPA estimates show high FAR and FBIvalues, it means that satellite has overestimated the numberof rain events with highest FAR and FBI values in the dryseason. Bias, RMSE, FAR and FBI show a spatial patternwhich increases with elevation because of the orographiceffect in the rainfall distribution and intermittentoccurrence. The temporal aggregation improves Bias, RMSEand Coefficient of Correlation values. For a monthly timescale the coefficient of correlation and bias reach values 0.95and 28% respectively. Improvements on a monthly scale mayarise from the TMPA processing algorithm which usesmonthly histograms to calibrate the satellite data. TMPAproducts like other ones (STAR or CMORH) have coarsespatial resolution (between 4km – 27 km) and represent asnapshot at a given time. The spatial and temporal44

characteristics of rainfall in this zone is highly variable andin winter season the rainfall inside one cell of TMPA productcan be strongly variable as well. The use of the monthlyTMPA product can be feasible in hydrological models with amonthly time step; however daily satellite data is restricteddue to the time scale by which it was obtained and thealgorithm used to calibrate the TMPA estimates.Chan, SamuelSMAP Instrument Design For High Resolution SoilMoisture And Freeze/Thaw State MeasurementsChan, Samuel 1 ; Spencer, Michael 11. Jet Propulsion Laboratory, Pasadena, CA, USASoil moisture controls water cycles fluxes, such as runoffand evapotranspiration, and modulates the energy cyclethrough the exchange of energy between the land and theatmosphere. Near-surface soil moisture and its freeze/thawstate are also the primary determinants of carbon exchangeat the land surface. Consequently, measuring theseparameters globally is vital to understanding the globalwater, energy and carbon cycles. The Soil Moisture ActivePassive (SMAP ) mission has the scientific objective ofmeasuring and monitoring both soil moisture andfreeze/thaw state globally from space with unprecedentedresolution and accuracy. SMAP will provide estimates ofsurface soil moisture with an accuracy of 0.04 [cm3/cm3], at10 km resolution, and with 3-day average revisit-time overthe global land area. The requirements for 10 km spatialresolution and 3 day temporal resolution are driven byphenomena in hydrologic and atmospheric science whichhave distinguishing features or significant physicalinteractions at the hydrometeorological scale of 10 km. Inthe past, soil moisture measurements have primarily utilizedpassive microwave data, because of the greater sensitivity ofbrightness temperature to surface soil moisture. Thedisadvantage of this approach is the coarse resolution ofmeasurement. For example, a spatial resolution of 35 km isthe best case for the recently launched SMOS mission. Toaccomplish the requirement for higher resolution, SMAPemploys a radar instrument in addition to a radiometer.Both instruments are operated at L-band, rather than C-band or higher frequencies, to cover a much larger range ofvegetation conditions. The radar and radiometer share asingle feedhorn and parabolic mesh reflector, which is offsetfrom nadir and rotates at a constant rate. A swath of 1000km is covered with this conical scanning geometry. Inaddition, the scanning antenna beam has a constant surfaceincidence angle and this reduces the complexity of the soilmoisture retrieval algorithm. The SMAP radar is designed toallow synthetic aperture radar (SAR) processing, and theresolution of the resulting measurement is less than 1 kmover the outer 70% of the swath. Data collected include bothco-pol signals, HH and VV, and one cross-pol, HV or VH. Thebackscattering coefficients measured by the radar will beused to retrieve soil moisture with a time series algorithm.The L-band radar measurements are effected by vegetationand surface roughness. The cross-pol measurements willhelp to identify and correct for the presence of surfacevegetation. Because the radar data alone is still unlikely tomeet the overall soil moisture accuracy requirement, SMAPwill utilize an algorithm which merges the active and passivemeasurements to derive the soil moisture product. Thisalgorithm will combine the spatial resolution advantage ofthe radar with the sensitivity advantage of the radiometer toachieve an optimal blend of resolution and accuracy.Freeze/thaw state will also be derived from the radar data toyield high resolution spatial and temporal mapping of thefrozen or thawed condition of the surface soil and vegetationin the boreal zones.Chávez Jara, Steven P.CHARACTERIZATION OF HEAVY STORMS INTHE PERUVIAN ANDES USING THE TRMMPRECIPITATION RADARChávez Jara, Steven P. 1 ; Takahashi Guevara, Ken 11. Research in Natural Disaster Prevention, PeruvianGeophysical Institute, Lima, PeruIn the Peruvian Andes, the great geographicalheterogeneity and the sparcity of raingauge networksprecludes an adequate characterization of the precipitationdistribution and estimation techniques based in remotesensing satellite cloud observations have not been successfulin this region. However, the available data indicates verystrong year-long rainfall in the eastern slopes of the Andesthat is probably a substantial contribution to the Amazondischarge, whereas rainfall in the internal Andean valleys issubstantially weaker but has great importance for the localpopulation, In this study we characterize storms in bothregions using data from the precipitation radar (PR)onboard TRMM, particularly the products 2A25 and 2A23,which allows us to obtain the three-dimensional spatialdistribution of rainfall, an estimated surface rainfall, as wellas other properties such as rain type (i.e. convective vsstratiform) and storm depth. Images from the GOESgeostationary satellite also provide information of cloudsand their brightness temperature. Field measurements of theDrop Size Distribution (DSD) using the filter papertechnique in the Mantaro Valley in the central Andes ofPeru, are used to validate the PR 2A25 algorithm for this theregion, particularly the a and b parameters in the relationbetween rain rate (R) and reflectivity (Z), i.e. R=aZ^b, findingan excelent agreement for b, but an overestimation of a inthe 2A25 algorithm We found than in the TRMM PR datafor the central Andes, the overall majority of the rainingpixels are stratiform and only a few pixels are convective, yetthe total rain associated to the convective pixels equals to thestratiform ones. On the other hand, for a orographicallyforcedrainfall core in the eastern slope of the Andes, wefound that although there is a larger fraction of convectivepixels than in the highlands, the total stratiform andconvective rainfall are similar highlighting the importance ofstratiform precipitation in this heavily raining region. Thus,rainfall estimation techniques that assume a relationshipbetween storm height and rainfall rates do not work. It was45

further verified that even for convective events, GOES IR4brightness temperature, which provides a measure of cloudtop height, does not present a significant relationship withrainfall rates. These results yield some light on the reportedunderestimation of rain by some satellites-based rainfallproducts in the upper Amazon Basin.Chen, BaozhangSpatially explicit simulation of hydrologicallycontrolled carbon-water cycles based on remotesensing in the Po Yang Lake whatershed, Jiangxi,ChinaChen, Baozhang 1 ; Zhang, Huifang 11. Institute of Geographic Sciences and Natural ResourcesResearch,Chinese Academy of Sciences, Beijing, ChinaIt has recently obtained great recognitions that howhydrological controls affect biogeochemical carbon (C)cycles, forest ecosystem functions and climate change. It isalso well known that topographically driven water fluxessignificantly influence the spatial distribution of C sourcesand sinks because of their large contribution to the localwater balance. However, ecosystem models that simulatebiogeochemical processes usually ignore hydrologicalcontrols that govern them and do not take into account thetopographically driven water horizontal movements such assurface runoff and groundwater flow. Since water horizontalmovements contribute largely to the local water balance, thesimulation accuracy of the spatial and temporal distributionof C sources and sinks will be limited if the horizontal waterdynamics are not well simulated. To improve this, in thisstudy we coupled a remote sensing based land surface model(EAASS: Ecosystem Atmosphere Simulation Scheme) withthe spatially explicit hydrology model (DBH: DistributedBiosphere-Hydrological) to develop a new integratedecohydrological model (EASS-DBH), which has a tightcoupling of ecophysiological, hydrological, andbiogeochemical processes. The coupled EASS-DBH modelwas then applied to the Po Yang lake watershed (162,200km2) which contains a large area of evergreen forestecosystem (40.05%), to simulate the C dynamics, soilmoistures, energy, and momentum. The simulated resultsshowed that the coupled model can capture most of thespatial and temporal C and water exchange dynamics whencompared with the observed data.Chen, QiUsing Bayesian Methods to Fuse Data fromMultiple Sources (Raingages, Radar,Meteorological Model, PRISM maps, andVegetation Analysis) for Mapping Rainfall in theState of HawaiiChen, Qi 1 ; Giambelluca, Thomas 1 ; Frazier, Abby 1 ; Price,Jonathan 2 ; Chen, Yi-Leng 3 ; Chu, Pao-Shin 3 ; Eischeid, Jon K. 41. Geography, University of Hawaii at Manoa, Honolulu, HI,USA2. Department of Geography and Environmental Sciences,University of Hawai‘i at Hilo, Hilo, HI, USA3. Department of Meteorology, University of Hawai‘i atManoa, Honolulu, HI, USA4. Cooperative Institute for Research in EnvironmentalScience, University of Colorado, Boulder, Boulder, CO,USADifferent techniques have been developed to mergerainfall information from different sources in order toobtain the “best” estimate of the “true” rainfall field usingstatistical models (e.g. Pegram and Clothier, 2001; Todini,2001) or models based on the physical properties of a raincell or cloud (Gupta and Waymire, 1993). Rainfallinformation derived from raingages, weather radar, orsatellites may not individually be adequate to represent thespatial details required, for example, by hydrological models(Frezghi and Smithers 2007). In this study, we proposed aBayesian statistical method to fuse different data sources,including raingage measurements, NEXRAD radar imagery,MM5 meso-scale meteorological simulations, PRISM rainfallmaps, and vegetation analysis to map the mean rainfallduring the recent 30 years (1987-2007) for the state ofHawaii. In this Bayesian data fusion method, each type ofdata provides evidences for estimating the true rainfall at agiven spatial location, with a certain error associated with it.The rainfall at a given location is estimated bysimultaneously considering both the spatial autocorrelationwith the rainfall nearby and the relationships with multiplesecondary datasets (radar imagery, MM5 model simulation,and PRISM maps). The spatially-varying errors associatedwith each input data determine their relative contributions(in other words, weights) to the final rainfall estimate at eachlocation. The use of Fourier transform for preprocessingradar imagery will also be introduced. The final rainfallmaps will be evaluated against the raingage measurementsand the caveats and future directions will be discussed aswell.http://rainfall.geography.hawaii.edu/46

Cherry, Jessica E.Advances in Airborne Remote Sensing ofHydrologic Change in Cold RegionsCherry, Jessica E. 11. IARC 408, University of Alaska Fairbanks and NorthernScience Services, Fairbanks, AK, USASeveral challenges face the study of hydrologic change incold regions from remote sensing, including the relativelylow-resolution of commonly used satellite products such asMODIS snow covered area. Higher resolution products, inthe case of TerraSAR, are costly—in part because there is nocurrent U.S. Synthetic Aperture Radar (SAR) satellitemission. Airborne remote sensing can lower costs andincrease resolution, relative to current satellite products.This presentation will review advances made possible by thefalling costs of high quality airborne sensors, as well as newcapabilities of automated software. Examples will be shownfrom different cold region hydrologic applications usingairborne techniques: use of forward-looking infrared todetect ground water contributions to runoff, use of opticalimagery for snow melt and water equivalent estimates,multispectral imagery for wetland delineation, and use ofoptical and SAR for estimating liquid water resources duringthe cold season.Chew, ClaraUSING GPS INTERFEROMETRICREFLECTOMETRY TO ESTIMATE SOILMOISTURE FLUCTUATIONSChew, Clara 1 ; Small, Eric 1 ; Larson, Kristine 2 ; Zavorotny,Valery 31. Geological Sciences, University of Colorado Boulder,Boulder, CO, USA2. Aerospace Engineering, University of Colorado Boulder,Boulder, CO, USA3. NOAA, Boulder, CO, USAHigh-precision GPS receivers can be used to estimatefluctuations in near surface soil moisture. This approach,referred to as GPS-Interferometric Reflectometry (GPS-IR),relates precise changes in the geometry of reflected GPSsignals to estimate soil moisture. Standard GPS antennaconfigurations, for example that used in NSF’s PlateBoundary Observatory network, yield sensing footprints of~1000 m2. Previous remote sensing research has shown thatmicrowave signals (e.g., L-band) are optimal for measuringhydrologic variables, such as soil moisture. GPS satellitestransmit similar signals and therefore are useful for sensingwater in the environment. Given this sensitivity, hundreds ofGPS receivers that exist in the U.S. could be used to providenear-real time estimates of soil moisture for satellitevalidation, drought monitoring and related studies. We haveestablished nine research sites with identical GPS andhydrologic infrastructure to study this problem. These sitesspan a wide range of soil, vegetation, and climate types. Inaddition to daily GPS and hourly soil moisture data, we havecollected weekly vegetation water content samples at all sites.Our data demonstrate that soil moisture fluctuations can beestimated from GPS-IR records with RMSE < 0.04. GPS-IRmetrics are best correlated with soil moisture data from thetop of the soil column (2.5 cm). Soil moisture estimates areless reliable when vegetation water content exceeds 2 kg m-2.A similar problem exists when using other L-band signals forremote sensing of soil moisture. Results from a forwardmodel show that the phase, amplitude, and frequency of thereflected signal are sensitive to soil moisture regardless ofsoil type. The same model suggests that the L-band signal ismost strongly affected by the surface soil moisture. Weoutline different approaches for separating the soil moistureand vegetation signals and quantifying errors in our retrievalalgorithm.Cohen, SagyCalibration of Orbital Microwave Measurements ofRiver Discharge Using a Global Hydrology ModelCohen, Sagy 1 ; Brakenridge, G. R. 1 ; Kettner, Albert J. 1 ;Syvitski, James P. 1 ; Fekete, Balázs M. 2 ; De Groeve, Tom 31. CSDMS, INSTAAR, University of Colorado, Boulder, CO,USA2. CUNY Environmental CrossRoads Initiative, NOAA-CREST Center, The City College of New York, CityUniversity of New York, New York, NY, USA3. Joint Research Centre of the European Commission,Ispra, ItalyReliable and continuous measurement of river dischargeis crucial for calculating terrestrial water cycle budgets(including surface water storage) and flux of water andsediment to the oceans. It also has numerous practicalapplications in addressing the increasingly urgent waterneeds for the expanding global population. Previous workdemonstrates that orbital passive microwave instruments(such as AMSR-E – now out of operation – and TMI) havethe capability to measure river discharge variation on a dailybasis, and thereby help address major limitations in groundbasedgaging of global rivers. Its potential is largelyuntapped. While future satellite missions are being plannedto retrieve less frequent discharge measurements, viaaltimetry, on an experimental basis, for a limited missionduration, the data from the present internationalconstellation of sensors that provide sustained observationshould be more fully utilized. Our strategy is to use existingdata streams that directly monitor discharge, and to couplesuch data to increasingly sophisticated global runoff models.This allows the needed calibration of remote sensing signalto (m3/s) discharge units (or catchment runoff in mm), andalso the possibility to improve the models. In many regions,ground-based discharge data are non-existing, or not freelyshared, or have only intermittent periods of record. Inothers, abundant ground-based data are available to providerigorous tests of the accuracy and precision of orbitalmeasurements and our calibration methods. In the latterlocations (e.g. within the U.S.), the use of modeling tocalibrate remote sensing discharge measurements is47

underway and its utility can be assessed. Then we can alsoapply such methods to regions where in-situ data are largelylacking. Here we use a well-established global dischargeprediction model (WBM) to obtain estimated discharge timeseries for calibrating remote sensing measurements (usingthe Advanced Microwave Scanning Radiometer (AMSR-E)band at 36.5 GHz processed in the Global Flood DetectionSystem at the Joint Research Centre of the EuropeanCommission). We evaluate this methodology on a suite ofriver measurement sites in the U.S. for which we have in-situgaged discharge (from co-located USGS gaging stations) andalso for the Indus River, in Pakistan, where such data aremuch more limited. The preliminary results are promising;they show that model-predicted discharge can provide localrating equations for river measurement sites monitored onlyvia remote sensing. This allows immediate translation ofincoming remote sensing to discharge estimates, and furthertesting of the WBM model. The results also show thatmonthly or yearly discharge statistics (means, maximums,and minimums) are as useful as the daily time-series inproviding a first-order calibration to discharge.Collins, William D.A Comparison of the Scale Invariance of the WaterVapor Field Observed by the Atmospheric InfraredSounder to the Scale Invariance of In SituObservations from a Very Tall TowerPressel, Kyle G. 1, 2 ; Collins, William D. 1, 2 ; Desai, Ankur R. 31. Earth and Planetary Sciences, University of California,Berkeley, Berkeley, CA, USA2. Lawrence Berkeley National Laboratory, Berkeley, CA,USA3. Atmospheric and Oceanic Sciences Department,University of Wisconsin, Madison, Madison, WI, USAIt has recently been shown that the water vapor fieldobserved by the Atmospheric Infrared Sounder exhibitswidespread scale invariance at spatial scales ranging from50km to 500km. The lower length scale is determined by theresolution of the AIRS instrument. There is no a priorireason to expect that a scale break would occur until scalesthat are well below 50km. Observational support for anextension of the AIRS observed scale invariance to smallerscales would provide a basis for including the observed scaleinvariance of the water vapor field in the formulation ofsubgrid scale parameterizations in global climate models(GCMs). There are very few observations of the water vaporfield amenable to studying scale invariance at scales below50km. In this presentation we report results of an analysis ofscale invariance in time series of high frequency (10Hz)measurements of water vapor mixing ratio from the 396mlevel of the WLEF tower located near Park Falls, Wisconsin.In particular, we compute the first order structure functionof the WLEF water vapor time series. The first orderstructure function of the time series relates the mean oftemporal fluctuations, also know as increments, to timescale. If the first order structure function exhibits power lawdependence on scale then the field is said to be scaleinvariant. Taylor’s frozen turbulence hypothesis is used totransform the time scales of the structure functions toapproximate spatial scales. In this study we have computedpower law exponents for the first structure function ofdetrended 4 hour time series sampled from June, July, andAugust of 2006 through June 2011. The 4 hour time seriesroutinely allow computation of the structure function toscales in excess of 16km. It is found that while not allstructure functions suggest scale invariance of the watervapor field, those that do exhibit scale invariance showevidence of a diurnal cycle in power law exponents that isremarkably consistent with the diurnal variation of AIRSobserved exponents.Connor, WilliamStrategies for validating Vegetation IndexEnvironmental Data Records from Visible InfraredImaging Radiometer Suite using tower reflectancemeasurementsConnor, William 1 ; Miura, Tomoaki 11. Natural Resources and Environmental Management,University of Hawaii at Manoa, Honolulu, HI, USASpectral vegetation indices (VIs) from satellite remotesensing have been shown useful to derive inputs tolandscape-scale modeling of Earth’s hydrological cycle, suchas fractional vegetation cover and evapotranspiration (ET).For example, the vegetation index – surface temperatureapproach is a popular approach for quantifying surface ETresistance. Realized ET from land surfaces are a function ofsurface properties, where physiological activity of vegetationis especially important as it limits evapotranspiration belowpotential level. The National Polar-orbiting OperationalEnvironmental Satellite System Preparatory Project (NPP) isthe first step in building the next-generation Earthobserving satellite. Onboard the NPP is the Visible InfraredImaging Radiometer Suite (VIIRS), a key component of theNPP spacecraft, which will provide detailed imagery, orEnvironmental Data Records (EDRs), of vegetation andother geophysical parameters. Two VIs, the normalizeddifference vegetation index (NDVI) and enhanced vegetationindex (EVI), collected daily at 375 m resolution have beenincluded as one of VIIRS EDRs. In order to ensure accuraterepresentation, validation is one critical component of theVIIRS EDR development. One planned validation activity forVIIRS Vegetation Index EDRs is to use tower-basedreflectance measurements to continuously assess accuracy ofVI EDRs and their time series, aimed at anchoring satellitedata to the ground. In tower-based reflectancemeasurements, a spectrometer is typically mounted at thetop of a tower, acquiring bi-hemispherical reflectancecontinuously at set intervals. Footprints of these tower-basedreflectance measurements are typically smaller than thespatial resolution of VIIRS VI EDRs. Therefore, it is arequirement to evaluate spatial representativeness of thetower measurements for the VIIRS spatial resolution. In thisstudy, we developed a protocol to evaluate spatialrepresentativeness of a site for VI validation and applied it to48

a few planned sites. They included Table Mountain(Colorado, USA) and Mase flux site (Ibaraki, Japan) amongothers which encompass a wide variety of vegetative coverand topographic variation. For determining the relativehomogeneity of the candidate sites, we evaluated scalingdependency in the area surrounding the viewing footprint ofeach tower radiometer. High resolution Landsat images ofthe research sites were used to simulate NDVI and EVI valuesat several different satellite footprints via spatialaggregation. These simulated coarse resolution VIs werecompared against the tower-footprint VIs and differencesand variation in these measurements assessed. In general,mean NDVI and EVI values varied with footprint size, butthey matched with the tower-footprint values with 95%confidence level over a growing season. The developedprotocol was not only useful for evaluating siterepresentativeness, but also for understanding a bias due tosite heterogeneity. High resolution imagery should beincorporated into the tower reflectance-based validation forheterogeneous sites.Cooper, StevenOn the limitations of satellite passive remotesensing for climate process studiesCooper, Steven 1 ; Mace, Gerald 1 ; Lebsock, Matthew 2 ;Johnston, Marston 3, 41. Atmospheric Sciences, University of Utah, Salt Lake City,UT, USA2. JPL, Pasadena, CA, USA3. Swedish Meteorological and Hydrological Institute,Norrkoping, Sweden4. Chalmers University of Technology, Gothenburg, SwedenGiven the uncertain future of next generation satellitemissions such as ACE and the possibility that space-basedactive sensors such as radar or lidar may be unavailable inthe relatively near future, we examine the ability of passivemeasurements (visible, near-infrared, infrared, microwave) todiscriminate critical atmospheric processes necessary for theunderstanding of climate. In this work, we exploit anunderstanding of both vertical sensitivities and retrievaluncertainties associated with these passive measurements todetermine their ability to uniquely differentiate between keycloud and precipitation property states. We perform such ananalysis for each ice clouds, low-latitude shallow marineclouds, and high-latitude mixed-phase clouds scenarios. 1)We first examine our ability to define the partitioning ofcloud ice mass between ‘suspended’ and ‘precipitating’particle modes and examine these results in context of cloudice representation in the European EC-Earth climate model.2) We then examine our ability to define the vertical profileof the partitioning of rain and cloud water properties in lowlatitudeshallow marine clouds, which are believed to play amajor role in potential climate cloud feedbacks. 3) Finally,we examine our ability to determine the vertical profiles ofhigh-latitude mixed phase cloud properties, which play a keyrole in high-latitude feedbacks. For these vertically definedcloud scenarios, we find that we cannot confidentlydiscriminate between key cloud and precipitation states (e.g.how big are the ice particles? is it drizzling?) due to theinherent non-uniqueness of the passive retrieval approach.Although we do not deny the important contribution ofpassive remote sensing techniques to our currentunderstanding of climate, our findings suggest the need forthe continued employment and advancement of space-borneactive measurements (used in co-incidence with passivemeasurements) as we work towards an improvedunderstanding of climate.Cosh, Michael H.Validating the BERMS in Situ Soil MoistureNetwork with a Large Scale Temporary NetworkCosh, Michael H. 1 ; Jackson, Thomas J. 1 ; Smith, Craig 2 ; Toth,Brenda 31. U. S. Dept. of Agriculture, Beltsville, MD, USA2. Climate Research Division, Science and TechnologyBranch, Environment Canada, Saskatoon, SK, Canada3. Hydrometeorological and Arctic Lab, EnvironmentCanada, Saskatoon, SK, CanadaCalibration and validation of soil moisture satelliteproducts requires data records of large spatial and temporalextent, but obtaining this data can be challenging. Thesechallenges can include remote locations, and expense ofequipment. One location with a long record of soil moisturedata is the Boreal Ecosystem Research and Monitoring Sites(BERMS) in Saskatchewan Canada. In and around theBERMS study area, there are five long term soil moistureprofile stations. These stations provide a critical butincomplete view of the soil moisture patterns across thedomain of study of 10, 000 square kilometers. Incoordination with the Canadian Experiment-Soil Moisture2010 (CANEX-SM10), a temporary network of surface soilmoisture sensors was installed during the summer of 2010to enhance the data resources of the BERMS network.During the 3-month deployment, 20 stations recordedsurface information for use in validating the network andthe recently launched Soil Moisture Ocean Salinity (SMOS)Satellite. Using temporal stability analysis, this network wasable to scale the BERMS network to a satellite scale footprintwhich can be extrapolated beyond the time period of theinstallation. The accuracy of the network as compared togravimetric sampling is evaluated during the summermonths also.49

Courault, DominiqueAssessment of modelling uncertainties over aMediterranean agricultural region usingevapotranspiration models based on LANDSATthermal dataCourault, Dominique 1 ; Mira, Maria 1 ; Hagolle, Olivier 2 ;Marloie, Olivier 1 ; Gallego, Belen 1 ; Olioso, Albert 1 ; Castillo,Sergio 11. UMR EMMAH, INRA, Avignon, France2. CNES-CESBIO, Toulouse, FranceThe Crau-Camargue region located in Southern Franceoffers an important diversity of natural and agriculturalecosystems. As in many other Mediterranean coastal regions,the human influence has strongly modified the water cycleand an important impact of future global changes isexpected: modifications of precipitation and runoff regimes,sea level rise, and modification of soil and water usesassociated to the decrease of water resource availability. It’stherefore crucial to estimate with accuracy the real cropwater requirements for a better management of waterresources. Since several years, various research projects basedon the use of remote sensing data were conducted on thisarea with the main objectives to retrieve evapotranspiration(ET) and the main biophysical properties of theseecosystems. Different algorithms were proposed foroperational applications, among them, two models S-SEBI(Roerink et al. 2000) and SEBAL (Bastiaanssen et al.1998). Albedo and Land Surface Temperature (LST),computed from multi-spectral data, are key variables forthese two approaches. They are obtained from severalprocessing, including atmospheric corrections whichrepresent an important step particularly for thermal images.Works presented here evaluate uncertainties associated withthese different steps to estimate ET. The dataset used isbased on both multi-temporal LANDSAT7 data and groundmeasurements. Various surfaces including dry and irrigatedgrasslands, natural and cultivated areas were studied sinceseveral years, with continuous measurements of albedo andsurface temperature, surface fluxes with eddy correlationlinked with a description of the vegetation evolution. Thestudy focused on the following issues concerning theimpacts of inputs on ET mapping: - accuracy of theatmospheric profiles used for atsmopheric corrections of thethermal bands. Radiosoundings were compared to outputsof climatic models (ECMWF and NCEP) in order to quantifythe error made on LST when applying the radiative transfermodel MODTRAN. - use of various algorithms proposed inliterature to compute albedo from LANDSAT data. Fourmodels most frequently used, were compared to our grounddataset. - use of different formulations to compute surfaceemissivity and soil heat flux. We analysed two emissivitymodels:(Vandegriend and Owe 1993; Francois,et al. 1997),and four soil heat flux equations requiring different inputs. -the forcing of atmospheric variables was also analyseddepending on whether ones considers homogeneous orheterogeneous climate over the studied area. The resultsshow the large variability obtained on the sensible heat fluxsimulated from S-SEBI and SEBAL models and underlinealso the critical step to quantify with accuracy theuncertainties associated with land surface models(parametrization, processes) and the data used in thesemodels (atmospheric forcing, vegetation and soilcharacteristics, crop management practices...) Bastiaanssenet al. (1998). J Hydrology 213(1-4): 198-212. Francois et al.(1997).I J Remote Sens 18(12): 2587-2621. Roerink et al.(2000). Physics Chem Earth P B-Hyd Oceans Atmos 25(2):147-157. Vandegriend A., Owe (1993).I J Remote Sens 14(6):1119-1131.Cristobal, JordiHourly and Daily Regional Scale Validation of aMeteosat Second Generation Solar RadiationProductCristobal, Jordi 1 ; Anderson, Martha 21. Geophysical Institute, University of Alaska Fairbanks,Fairbanks, AK, USA2. Hydrology and Remote Sensing Laboratory, UnitedStates Department of Agriculture, Beltsville, MD, USASolar radiation is essential for evapotranspiration, bothactual and potential, variable of high importance to monitorand understand the properties of terrestrial ecosystems andthe hydrological cycle. Nowadays, there are a wide variety ofsatellites, both geostationary and-synchronous, from whichsolar radiation can be retrieved on a regional or global scalessuch as TERRA/AQUA, NOAA, GOES or MSG. Unlikesynchronoussensors, geostationary sensors are especiallyinteresting because of its high temporal resolution, thatallows retrieving solar radiation at intervals of 15 minutesand also their ability to cover large areas of territory, as is thecase of MSG SEVIRI. Since 2007, the Land Surface AnalysisSatellite Applications Facility (LSA SAF –http://landsaf.meteo.pt) offers an operative product of solarradiation (Down-welling Surface Short-wave radiation Flux -DSSF) obtained by means of the SEVIRI sensor. Thisproduct is generated in a 30-minute time resolution basisand 1 km spatial resolution at the Ecuador through thethree solar spectrum channels of the SEVIRI sensor (VIS0.6µm, NIR 0.8µm, SWIR 1.6µm). In this work, an hourlyand daily regional scale validation of the DSSF product overCatalonia (NE Iberian Peninsula, approximately 32 000km2) during 2008-2009 period is presented. For thevalidation, a total of 140 meteorological stations of theMeteorological Service of Catalonia (www.meteocat.com),located in different covers and different altitudinal range,were used. In order to evaluate the performance of theproduct in different terrain conditions we created twosubsets depending on slope: 100 stations in flat conditionsand 40 in hilly conditions. In the case of the hourlyvalidation in flat conditions we obtained a mean R2 andRMSE for the 2008-2009 period of 0.91 and 89 W m-2,respectively; and in the daily case of 0.97 and 1.3 day MJ m-2,respectively. In the case of the hourly validation in hillyconditions we obtained a mean R2 and RMSE of 0.86 and112 W m-2, respectively; and in the daily case of 0.90 and 2.750

day MJ m-2, respectively. Validation results in the case of flatconditions show a good performance, especially in the dailycase, and offer better results than those obtained in the caseof the hilly conditions. This suggests the algorithm thatDSSF uses is operative for obtaining both hourly and dailysolar radiation in flat conditions and that it can be used as areliable input variable in evapotranspiration models. On theother hand, in hilly conditions further research in the DSSFproduct is needed.Cristobal, JordiJuniper Tree Actual Evapotranspiration Estimationby Means of Landsat-5 TM Imagery and the TSEBModel in the Doñana Biological ReserveCristobal, Jordi 1 ; Kustas, William P. 2 ; Anderson, Martha 2 ;Infante, Juan Manuel 3 ; Díaz-Delgado, Ricardo 31. Geophysical Institute, University of Alaska Fairbanks,Fairbanks, AK, USA2. Hydrology and Remote Sensing Laboratory, UnitedStates Department of Agriculture, Beltsville, MD, USA3. Equipo de Seguimiento de Procesos Naturales. SingularScientific and Technological Infrastructure of theDoñana Biological Reserve., Consejo Superior deInvestigaciones Científicas, Sevilla, SpainMonitoring of evapotranspiration (ET) has importantimplications because plays a key role in global and regionalclimate modeling, the knowledge of the hydrological cycle aswell as to assess the water stress that affects agricultural andnatural ecosystems. Nowadays, remote sensing is the onlytechnology capable of providing the necessary radiometricmeasurements for the calculation of the evapotranspirationat global scales and in a feasible economic way. Currently,most of the algorithms developed for evapotranspirationmodeling have been developed and validated in crop areas,and its implementation in natural vegetation areas is still amajor challenge, especially in areas of Mediterraneanvegetation. To this effect, the Doñana Biological Reserve(DBR) as Singular Scientific and TechnologicalInfrastructure (ICTS), has started a long-term ecologicalmonitoring plots to carry out the validation and monitoringof evapotranspiration and other energy flux in a juniper treearea (Juniperus turbinata ssp phoenicea); area that presentsboth high heterogeneity and coverage in the Reserve and inthe Doñana National Park. In this work we present the firstresults of energy flux modeling and validation, includingevapotranspiration, net radiation, sensible heat flux and soilheat flux, at satellite pass in the experimental plot of “elOjillo” in 2010. The methodology used in evapotranspirationmodeling is based on the algorithm TSEB developed byKustas and Norman (1999). To carry out this research a totalof 5 Landsat-5 TM images for the following dates:06/02/2010, 16/07/2010, 01/08/2010, 25/08/2010 and10/09/2010 have been used. The validation was performedusing data from a flux tower located on the juniper tree plot.TSEB method showed acceptable results for the differentenergy flux modeled taking into account the highheterogeneity of this type of cover. RMSE obtained in thecase of the evapotranspiration, net radiation, sensible heatflux and soil heat flux were 60, 42, 60 and 53 W m-2,respectively. This work has been the first of a larger projectto map evapotranspiration, not only over the juniper treearea but throughout the PND using the currently availableLandsat archive. Future research will be focused in dailyenergy fluxes integration as well as their estimation bymeans of ALEXI/DisALEXI methodology (Anderson et al.,2007) in order to avoid meteorological data from fluxstations.Cristobal, JordiTundra Energy Fluxes Retrieval on the AlaskanNorth Slope by Means of Landsat and ModisImagery and the Tseb Method: Preliminary ResultsCristobal, Jordi 1 ; Prakash, Anupma 1 ; Fochesatto, Javier 1 ;Anderson, Martha 2 ; Kustas, William P. 2 ; Alfieri, Joseph 2 ;Gens, Rudi 3 ; Kane, Douglas L. 41. Geophysical Institute, University of Alaska Fairbanks,Fairbanks, AK, USA2. Hydrology and Remote Sensing Laboratory, UnitedStates Department of Agriculture, Beltsville, MD, USA3. Alaska Satellite Facility. Geophysical Institute, Universityof Alaska Fairbanks, Fairbanks, AK, USA4. Water and Environmental Research Center, University ofAlaska Fairbanks, Fairbanks, AK, USAEvapotranspiration (ET) plays a significant role in thehydrologic cycle of Arctic basins. Surface-atmosphereexchanges due to ET in the Imnavait Creek Basin areestimated from water balance computations to be about 74%of summer precipitation or 50% of annual precipitation.Even though ET is a significant component of thehydrologic cycle in this region, the bulk estimates don’taccurately account for spatial and temporal variability due tovegetation type, topography, etc. (Kane and Yang, 2004).Nowadays, remote sensing is the only technology capable ofproviding the necessary radiometric measurements for thecalculation of the ET at global scales and in a feasibleeconomic way, especially in Arctic basins with a very sparsenetwork of both meteorological and flux towers. In thiswork we present the validation of the TSEB model (Kustasand Norman, 1999) to retrieve energy fluxes (ET, sensibleheat flux, net radiation and soil heat flux) in a tundrahabitat. Our test site is Imnaviat Creek Basin, Alaska, whichis one of the few well studied areas in the Alaska NorthSlope. To validate the model we used data from anexperiment carried out in summer 2009 to characterize theturbulent fluxes (i.e. buoyancy fluxes) at two levels of 1 and3 m AGL and the heat fluxes in an integrated horizontalpath covering about 80% of the basin (Wyatt et al., 2009). Inaddition, we also used three energy flux towers of the ArcticObservatory Network(http://aon.iab.uaf.edu/AON_Home.html) located close tothe summer 2009 experiment site (about 1 km). TSEB modelmainly requires meteorological inputs coming from fluxtower stations as well as land surface temperature (LST) andleaf area index (LAI) both coming from satellite imagery. We51

used three Landsat-5 TM images (05/07/2009, 21/07/2009and 06/08/2009) and MODIS LAI product to retrieve ETestimates. To provide LST data, Landsat-5 TM images weredownloaded through the USGS Earth Explorer gateway in1T level. In the case of solar bands, radiometric correctionwas carried out following the methodology proposed byPons and Solé-Sugrañes (1995); and we used the methoddeveloped by Cristóbal et al. (2009) to atmosphericallycorrect the thermal band. MODIS LAI product (MOD15)was downloaded from the NASA-WIST gateway. Preliminaryresults show an acceptable agreement between TSEB modeland flux tower data. RMSE obtained in the case of atsatellite pass ET, net radiation, sensible heat flux and soilheat flux were 72, 41.5, 40.8 and 50.8 Wm-2, respectively.Further efforts will be focused on the daily energy fluxintegration by means of the implementation of theALEXi/DisALEXI model (Anderson et al., 2007) as well asthe energy balance computation in snow conditions. Finally,due to the importance of LAI input in TSEB model, LAI willbe directly estimate by means of field sampling and thenmodeled using Landsat-5 TM images.Cunha, LucianaExploring the Potential of Space-Based RemoteSensing in Flood PredictionCunha, Luciana 1 ; Krajewski, Witold 1 ; Mantilla, Ricardo 11. Civil and Env Eng, IIHR - Hydroscience & Engineering,Iowa City, IA, USAAdvances in remote sensing techniques to monitorhydro-meteorological and land surface variables from spacemade it possible to monitor and predict floods on a nearglobalbasis. However, the use of calibration-basedhydrological models prevents the implementation of suchglobal systems since it requires data that are unavailable inmany parts of the world. In this study we present progresstowards development of a calibration-free multi-scalehydrological model based entirely on space-based remotesensing data. The model is based on a faithfuldecomposition of the landscape into hillslopes and riverchannel links, and on the solution of the mass andmomentum equations for each control volume. We avoidcalibration through the use of equations and parametersthat can be directly related to measurable physical propertiesof the landscape. As a research strategy to explore thepotential of space-based products in flood forecasting, wefirst force the model with high-resolution data, whenavailable (i.e. NEXRAD radar rainfall, LIDAR and USGS-NED DEMs, and NLCD land cover). We then investigatehow predictions are degraded by the use of coarserresolution and higher uncertainty products provided bysatellites (PERSIANN, 3B42, and CMOHPH rainfall, ASTERand SRTM DEMs, and MODIS-MOD15A2 land cover).Other datasets used in the model implementation are:potential evapotranspiration (MODIS – MOD16), soilproperties (SURGO), soil initial moisture conditions (LandData Assimilation System-NLDAS 2), leaf area index(MODIS – MOD12Q2), snow cover, and snow melt (AMSR-L3). We demonstrate, for example, that accurate floodpredictions based on satellite rainfall products can be obtainat certain scales if retrieval uncertainties are limited torandom components (no significant bias). In this case,uncertainties on the rainfall field are filtered out by theaggregation effect of the river network. We performedsimulations for two watersheds in Iowa for which highresolutiondata is available: Cedar River (16,800 km2), IowaRiver (7,200 km2). We simulate 7 years of data (2002 to2009) including different hydrological conditions for wetand dry years. Streamflow predictions are validated for 32nested sites with drainage areas ranging from 22 to 16,800km2. Our results demonstrate the feasibility of usingcalibration-free hydrological models to simulate alldominant hydrological processes responsible for floodsacross multiple scales. It is evident, however, that simulationduring dry periods is less accurate due to complex and nonlinearsoil dynamics that are not captured by the currentmodel.Das, NarendraPast, Present and Future of Satellite-based RemoteSensing to Measure Surface Soil Moisture: WithEmphasis on Soil Moisture Active Passive Mission(SMAP) MissionDas, Narendra 1 ; Entekhabi, Dara 2 ; Njoku, Eni G. 11. Water and Carbon Cycle Group, Jet Propulsion Lab,Pasadena, CA, USA2. Department of Earth, Atmospheric and PlanetarySciences, MIT, Cambridge, MA, USADuring the last three decades, remote sensingmeasurements, especially soil moisture has played anincreasing role in the fields of hydrology, ecology,climate/weather studies, agronomy and water managementat regional/global scale. Microwave remote sensing providesa unique capability for direct observation of soil moisture.Passive (radiometer) and active (radar) remote sensingmeasurements using satellite-based sensors from spaceafford the possibility of obtaining frequent, global samplingof soil moisture over a large fraction of the Earth’s landsurface. These capabilities render the satellite-based remotesensing of soil moisture very attractive. In past, most of thesatellite-based sensors operated at C- and X-band including,SSM/I, SMMR, and AMSR-E in passive mode, andRADARSAT, ERS, ENVISAT and JERS in active mode.Currently, the SMOS mission of ESA provides soil moisturemeasurements at L-band that has more sensitivity for soilmoisture. All these past and current satellite-based sensorshave limitation either with spatial resolution or withtemporal resolution, and also with retrieved soil moistureaccuracy over different geophysical conditions. Moreover,most of the current land-based applications like weatherforecast, watershed management and agricultureproductivity need high spatiotemporal resolution soilmoisture measurements with high accuracy. To meet theserequirements, the Soil Moisture Active Passive (SMAP)mission is recommended by the U.S. National Research52

Council Committee on Earth Science and Applications fromSpace. The SMAP mission is under development with atarget launch date in late 2014. The SMAP mission willprovide high resolution (~9 km) soil moisture product at aglobal extent. The SMAP instrument architectureincorporates an L-band (1.26 GHz) radar and an L-band(1.41 GHz) radiometer that share a single feedhorn andparabolic mesh reflector. The SMAP radiometer and radarinstruments are capable of measuring surface soil moistureunder moderate vegetation cover individually, however, theinstruments suffer from limitations on spatial resolution(radiometer) and sensitivity (radar), respectively. Toovercome the limitations of the individual passive and activeapproaches, the SMAP mission will combine the two datastreams to generate an active/passive intermediate resolutionand accuracy soil moisture product. The baselineactive/passive algorithm disaggregates the coarse resolution(~36 km) radiometer brightness temperature (TB)measurements using the spatial pattern within theradiometer footprint as inferred from the high resolutioncoincident radar co-pol backscatter measurements, and theninverts the disaggregated TB to retrieve soil moisture. Thebaseline active/passive algorithm is implemented at a globalscale using data from the SMAP global simulation for oneyear period. Soil moisture retrieval results from global-extentstudy area demonstrate that the mission will meet itsrequirements of global coverage with an accuracy of

storage change solutions in the form of monthly Stokescoefficients, post-processing including decorrelation,filtering, signal leakage corrections, corrections for the effectof glacial isostatic adjustment and geocenter motions, andreplacement of the 2nd degree zonal coefficients, have beenused. Other solution techniques such as mascons or otherregional solutions presumably have higher spatial resolution,may suffer from errors in the long wavelength component ofthe hydrologic storage change. The recent availability of datafrom the Gravity Field and Steady-State Ocean CirculationExplorer (GOCE) spaceborne gradiometry has significantlyimproved the mean gravity field of the Earth, which could beused to be the reference model or combined with GRACEdata for temporal gravity field solutions. GRACE hydrologicstorage change data products are also computed with scaledseasonal amplitudes in various water basins assuming thatthe numerical hydrologic models have the truth amplitude.In this study, we attempt to validate various GRACEhydrologic storage change solutions using surface watermeasurements from contemporary satellite altimetry and insitu gage and boreholes (ground water), to assess eachsolution’s respective accuracy over selected hydrologicbasins, including Manus and Belem in the Amazons,Columbian River, Ganges, Ghaghara, Brahmaputra andother basins.Durand, Michael T.Optimal interpolation of spaceborne heightmeasurements of river height to support SWOTdischarge algorithmsDurand, Michael T. 1, 2 ; Yoon, Yeosang 3 ; Rodriguez, Ernesto 4 ;Biancamaria, Sylvain 5 ; Alsdorf, Doug 1, 2 ; Andreadis, Kostas 51. School of Earth Sciences, The Ohio State University,Columbus, OH, USA2. Byrd Polar Research Center, The Ohio State University,Columbus, OH, USA3. Department of Civil and Environmental Engineering andGeodetic Science, The Ohio State University, Columbus,OH, USA4. NASA Jet Propulsion Laboratory, Pasadena, CA, USA5. Centre National d’Etudes Spatiales, Toulouse, FranceThe global stream gage network is highly non-uniformspatially, limiting the scientific ability to constrain waterbalance to large spatial scales. The upcoming Surface Waterand Ocean Topography (SWOT) mission will measure riverwater surface elevation and inundated extent, along withlake height and area and global ocean topography. For rivers,the timeseries of SWOT measurements will enableestimation of river discharge via Manning’s equation. Thekey to this algorithm is the simultaneous application ofcontinuity and momentum in one-dimension (i.e. the StVenant equations) with repeated measurements of riverslope, width, and temporal height changes (SWOTmeasurables), which provides adequate information toestimate both the Manning friction coefficient and thebathymetry or the cross-sectional flow area beneath thelowest height measurement (see poster by Rodríguez andDurand, this conference). The key to this dischargealgorithm is a timeseries of SWOT measurements. Amongother things, this algorithm exploits the fact that thecontinuity equation specifies that the spatial derivative indischarge is equal to the temporal derivative in height. The22-day SWOT orbit will measure each point on the Earthsurface a minimum of twice per cycle. For mid-latituderivers, most pixels are measured two or three times, andsome four times per 22-day cycle. Thus, for a given riverreach, some hydrologic events (i.e. increase in river heightdue to precipitation and subsequent runoff) may not besampled. Here, we can exploit the fact that rivers areinterconnected: thus, a hydrologic event that is unobservedon part of the river network is likely to be observeddownstream or upstream. The simplest method toaccomplish this is a simple data assimilation strategy knownas Optimal Interpolation (OI). In our OI approach,spatiotemporal autocorrelation functions are used to exploitthe fact that rivers are interconnected. At a given reach, waterelevations at unobserved times are estimated by a priorestimate of water height, and the observations of the riverupstream and downstream at observed times. The priorestimate comes from a simple linear interpolation of thewater elevation in between observation times. Here, weexplore several questions: 1) What is the prior error in waterelevation due to simple interpolation between observedtimes? 2) What fraction of the prior error can be correctedusing the OI? 3) What is the expected impact on dischargeaccuracy if the OI heights are used in the dischargealgorithms? In this study, we first evaluate the OIperformance using hydraulic model output for the OhioRiver basin. Second, we examine OI performance using aseries of gages within the basin. The former study produceswater elevations that are more compatible with the SWOTspatial measurement, while the latter study includes theeffects of un-modeled phenomena, such as lateral inflows.55

Entin, JaredTerrestrial Hydrology in the Context of NASA’sEarth Science Program INVITEDFreilich, Michael H. 1 ; Entin, Jared 11. 300 E St. SW, NASA Headquarters, Washington, DC, USANASA supports a vigorous Earth Science research andapplications program, with the aims of advancing EarthSystem Science and developing a broad range of informationproducts for applications. This presentation will address thescope of NASA-supported activities focused on TerrestrialHydrology, including on-orbit and planned flight missions,competitive mission opportunities, research opportunities,and applications development investigations. Specialemphasis will be placed on the roles of Terrestrial Hydrologyactivities within the larger NASA Earth Science program.Esteban Fernandez, DanielKARIN: THE KA-BAND RADAR INTERFEROMERFOR THE SWOT MISSIONEsteban Fernandez, Daniel 1 ; Fu, Lee L. 1 ; Rodriguez, Ernesto 1 ;Pollard, Brian 1 ; Peral, Eva 1 ; McWatters, Dalia 1 ; Hughes,Richard 1 ; Callahan, Phil 11. NASA/JPL, Pasadena, CA, USAThe primary objective of the National Research Council(NRC) Decadal Survey recommended SWOT (Surface Waterand Ocean Topography) Mission is to measure the waterelevation of the global oceans, as well as terrestrial waterbodies (such as rivers, lakes, reservoirs, and wetlands), toanswer key scientific questions on the kinetic energy ofocean circulation, the spatial and temporal variability of theworld’s surface freshwater storage and discharge, and toprovide societal benefits on predicting climate change,coastal zone management, flood prediction, and waterresources management. Radar altimetry has been a majorachievement in the study of the Earth. Through the missionsof TOPEX/Poseidon (1992-2005), and its follow-on Jason(2001-present), and the Ocean Surface Topography Mission(OSTM)/Jason-2 (2008- ), a 15+ year data record of theglobal ocean surface topography has been obtained, whichwill extend into the future. However, the spatial resolutionsof these missions are not sufficient to address fundamentalscientific questions such as: (1) the eddy currents of theocean that contains 90% of the kinetic energy of oceancirculation, and (2) the variability of water storage anddischarge over land. SWOT will use a new technique tomeasure water elevation that will provide an order-ofmagnitudeimprovement in resolution and accuracy that isrequired to address these scientific questions. The SWOTmission is a partnership between NASA, CNES (CentreNational d’Etudes Spaciales) and the Canadian SpaceAgency. The core technology for the SWOT concept is theKaRIn instrument, a Ka-band radar interferometer,originally developed from the efforts of the Wide SwathOcean Altimeter (WSOA). The interferometer’s concept is asfollows: radar pulses are transmitted by each antenna, andthe radar echoes from each pulse are received by both. The57interferometric phase difference between the coherentsignals received by both antennas is essentially related to thegeometric path length or range difference to the imagepoint, which depends on the topography. Therefore, theknowledge of the range and the phase difference can beconverted into an altitude for each image point. KaRInimplements two Synthetic Aperture Radar (SAR) antennas,each one providing two separate beams at Ka-band (35.75GHz). As a result, the total swath coverage provided by theinterferometer is 100 km (50 km on each side of the nadirtrack, with a gap of 20 km in the center which is covered bythe nadir altimeter), at an unprecedented resolution of 1 kmfor the ocean (after on-board processing), and 100 m forland water, both with centimetric accuracy. In this paper, wepresent an overview of the KaRIn instrument, keyperformance requirements and the associated error budget.ACKNOLEDGEMENTS The research presented in the paperwas carried out at the Jet Propulsion Laboratory, CaliforniaInstitute of Technology, under contract with the NationalAeronautic and Space Administration. 2011 CaliforniaInstitute of Technology. Government sponsorshipacknowledged.Evans, Diane L.New Measurements for Understanding theTerrestrial Water CycleEvans, Diane L. 11. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USANASA satellites that are currently flying or planned forthe near future will provide significant improvements inunderstanding the terrestrial water cycle. Two of the threemissions recommended in the National Research Council’sEarth Science Decadal Survey by the Panel on WaterResources and the Global Hydrologic Cycle are planned forlaunch this decade. The Soil Moisture Active-Passive (SMAP)Mission has successfully completed its Preliminary DesignReview and is preparing for launch readiness in late 2014. Itsairborne predecessor, the Passive Active L-Band System(PALS) is already supporting pre-launch activities as well asmeasuring soil moisture and freeze-thaw in Alaska insupport of NASA’s Earth Ventures (EV-1) Carbon in ArcticReservoirs Vulnerability Experiment (CARVE). The SurfaceWater and Ocean Topography (SWOT) Mission, which willbe implemented with the French Space Agency, is preparingfor a Mission Concept Review in Spring of <strong>2012</strong> and a late2019 launch. An airborne precursor, AirSWOT has beendeveloped and data from this sensor will enable thehydrology community to mature the retrieval algorithmsand model assimilation well ahead of the actual SWOTmission. A third Decadal Survey mission, the HyperspectralInfrared Imager (HyspIRI), currently planned for after 2020,will provide measurements of contaminants and watertemperature, and improved estimates of run-off fromsnowpacks to help assess how global freshwater supplies areresponding to changes in climate and demand, and theimplications for sustainable management of water resources.

Famiglietti, James S.Getting Real About the State of HydrologicalModeling: Priorities for Advancing the NextGeneration of Integrated, Data-Assimilating WaterCycle SimulatorsFamiglietti, James S. 1, 21. UCCHM, Univ California Irvine, Irvine, CA, USA2. Dept Earth System Science, Univ California Irvine, Irvine,CA, USAWhile the development of hydrological and land surfacemodels has progressed rapidly over the last few decades, asignificant acceleration in model development is required inorder to address critical scientific and societal issues. Inparticular, major advances are needed in the areas of satelliteand in situ observations (e.g. of water cycle variability andchange, of subsurface soils and hydrogeology, and ofstreamflow and groundwater levels), model development(e.g. of models that integrate the major components of thehuman and managed water cycles), data assimilation (e.g. ofalgorithms that can readily incorporate in situ and remoteobservations of asynchronous space-time frequency) and of aframework for integrating models and data (e.g. for access todata and simulation results, for running models, and forperforming analyses). In this presentation these needs arediscussed in detail. Recent regional-to-global efforts arehighlighted, with a view towards a modeling and dataintegration framework that can be applied across scales upto continental and global scales. The responsibility of thehydrologic research community to convey such importantobservational and simulation needs to funding agencies,resource managers, environmental decision and policymakers, and to the general public, is underscored.http://ucchm.orgFarg, Eslam F.Estimation of Evapotranspiration and CropCoefficient Kc of Wheat, in south Nile Delta ofEgypt Using integrated FAO-56 approach andremote sensing dataFarg, Eslam F. 1 ; Arafat, Sayed M. 1 ; Abd El-Wahed, MohamedS. 2 ; El-Gindy, Abd El-Ghany M. 31. Agriculture applications, Soils and Marine Sciencesdevision, National Authority for Remote Sensing andSpace Sciences, Cairo, Egypt2. Soil department, Faculty of Agriculture, Ain ShamsUniversity, Cairo, Egypt3. Agriculture Engineering department, Faculty ofAgriculture, Ain Shams University, Cairo, EgyptCrop water requirements are represented by the actualcrop evapotranspiration. Estimation of cropevapotranspiration (ETc) using remote sensing data isessential for planning the irrigation water use in arid andsemiarid regions. This study focuses on estimating the cropcoefficient and crop evapotranspiration using SPOT-4satellite data integrated with the meteorological data and59FAO-56 approach. Reference evapotranspiration (ETo) wereestimated using FAO Penman-Monteith and tabled singlecrop coefficient values were adjusted to real values. SPOT-4images geometrically and radiometrically corrected wereused to drive the vegetation indices (NDVI and SAVI). Multilinear regression analysis was applied to develop the cropcoefficient (Kc) prediction equations for the differentgrowth stages from vegetation indices .The results showedR2 were for developing, mid-season and late season growthstages 0.82, 0.90 and 0.97, and adjusted R2 0.80, 0.86 and0.96 respectively.which indicates that estimation of cropcoefficient and water requirements using remote sensingdata is essentially significant.The analysis shows the vegetation indices derived from satelliteimages and both of calculated and predicted values of cropcoefficient Kc follow the same trend through the different growthstages.the prediction equations for different growth stagesFarr, Tom G.Remote Monitoring of Groundwater with OrbitalRadarFarr, Tom G. 11. Earth and Space Sciences Div., JPL, Pasadena, CA, USAGroundwater is a significant source of fresh water inarid and semi-arid regions, but one that is difficult tomonitor. In developed areas, wells can be drilled which areused both for extraction and for monitoring groundwaterlevels. However, the expansion and contraction of aquifersdue to recharge and withdrawal of water may causedeformation of the Earth’s surface which can be observedand measured from orbit by interferometric syntheticaperture radar, or InSAR. Repeat-pass InSAR has been shownto be highly sensitive to surface deformation related toearthquakes, volcanoes, and fluid movements including oiland water. In particular, several studies have shown inflationand deflation directly correlated to recharge and withdrawalof water in Las Vegas, Phoenix, and Los Angeles. Time seriesof these data show a clear seasonal signal which correlateswith groundwater levels in wells. Initial results from a studyof California’s Central Valley show that with currently

operating systems such as Europe’s Envisat and Canada’sRadarsat, it is possible to generate time series of surfacedeformation which show a clear seasonal signal whichcorrelates with groundwater levels in wells. Requirements forfuture work include measurements and maps obtained a fewtimes per year over a large area at a moderate resolution(~100 m). An important requirement is for continuingmeasurements for at least a decade. * work performed undercontract to NASAFeng, WeiEvaluation of groundwater depletion in NorthChina using the Gravity Recovery and ClimateExperiment (GRACE)Feng, Wei 1, 2 ; Zhong, Min 1 ; Lemoine, Jean-Michel 2 ; Xu, Hou-Ze 11. Institute of Geodesy and Geophysics, Chinese Academyof Sciences, Wuhan, China2. CNES/GRGS, Toulouse, FranceRegional groundwater storage changes in North Chinaare estimated from GRACE-derived total water storagechange data and simulated soil moisture data over 2003-2010. The study region includes Beijing, Tianjin, Hebeiprovince and Shanxi province (~370,000 km^2 area), whichare subjected to groundwater-based intensive irrigation.Depletion of groundwater resources in the region hasincreased substantially in the last several decades. Theobjective of this study is to estimate recent groundwaterdepletion rate in North China from GRACE satellites. Toincrease confidence in derived results, we adopt the monthlyGRACE products from CSR (Center for Space Research atthe University of Texas at Austin) and ten-day GRACEproducts from GRGS (Groupe de Recherche de GéodésieSpatiale), which use different processing strategies. Over2003-2010, the rates of groundwater depletion estimatedfrom two agencies’ GRACE products are 2.4±0.9 cm/yr(CSR) and 2.9±0.4 cm/yr (GRGS), which are equivalent to8.8±3.2 km^3/yr and 10.6±1.5 km^3/yr respectively.However, the estimate from Bulletin of Groundwater in theNorth China Plain (BGNCP) in the same time period is onlyabout 2.1 km^3/yr. The difference between two independentestimates could result from the contribution of deepgroundwater depletion, which is less studied before, and theuncertainty of simulated soil moisture data. Furthermore,the spatial pattern of groundwater depletion estimated fromGRACE shows a good agreement with the result estimatedfrom BGNCP data. Both of two independent results showhigh groundwater depletion in southwest of Hebei province.Our results indicate that the depletion of groundwaterresources in North China could be more serious than werealize.Fetzer, EricThe Water Vapor and Temperature Record fromthe NASA Atmospheric Infrared SounderFetzer, Eric 1 ; Pagano, Thomas S. 1 ; Teixeira, Joao 1 ;Lambrigtsen, Bjorn H. 1 ; Kahn, Brian H. 1 ; Tian, Baijun 1 ;Wong, Sun 11. JPL, Pasadena, CA, USAThe Atmospheric Infrared Sounder (AIRS) satelliteinstrument began taking hyperspectral infrared observationsin August 2002. AIRS continues operating, with an expectedlifetime of 15-20 years. The AIRS radiances, along withobservations from the companion Advanced MicrowaveSounder (AMSU), have been used to retrieve a detailedrecord of geophysical quantities relevant to climate, weather,atmospheric composition, and greenhouse gas forcing. Thistalk describes the variability in the 9+ year record ofAIRS/AMSU temperature and water vapor, and discusseshow those observations are being integrated into a completepicture of the climate system. We also describe how the AIRStemperature and water vapor observations can be used toconstrain important water vapor and temperature lapse ratefeedback mechanisms.Fisher, Joshua B.Global Terrestrial Evapotranspiration From RemoteSensing: The History and Progress of TwoMechanistic, Energy-balance, Dedicated ProductsFisher, Joshua B. 1 ; Mu, Qiaozhen 2 ; Jiménez, Carlos 3 ;Vinukollu, Raghuveer 4 ; Polhamus, Aaron 1 ; Badgley,Grayson 1 ; Tu, Kevin 51. NASA Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA2. Numerical Terradynamic Simulation Group, Departmentof Ecosystem and Conservation Sciences, University ofMontana, Missoula, MT, USA3. Laboratoire d’Etudes du Rayonnement et de la Matière enAstrophysique, Centre National de la RechercheScientifique, Observatoire de Paris, Paris, France4. Swiss Re, Armonk, NY, USA5. Theiss Research, Davis, CA, USAA few different approaches are available to estimateglobal terrestrial evapotranspiration (ET): I) modeled as partof larger climate or land surface models; II) dedicatedmechanistic models focused primarily on ET; and, III)empirical/statistical techniques that correlate groundobservations of ET against associated remote sensing orother globally gridded observations [Mueller et al., 2011]. Ofthese approaches, the dedicated mechanistic models may bethe most robust, containing less uncertainty than theclimate and land surface models due to tighter constraintsfrom fewer degrees of freedom, while able to represent a fullarray of ecosystems and climates, and their feedbacks,whereas empirical techniques are often limited in space andtime to where and when ground data were collected[Vinukollu et al., 2011]. The dedicated mechanistic models60

can be thought of as operating in two camps: one relying onobservations of land surface temperature as a response andconstraint variable to moisture and/or sensible heat status[Anderson et al., 1997; Su, 2002], and the other relying oncalculating potential ET from the Penman-Monteith[Monteith, 1965] and/or Priestley-Taylor [Priestley andTaylor, 1972] equations then reducing potential to actual ETbased on novel formulations of stomatal and aerodynamicconductances and/or plant ecophysiological response[Nishida et al., 2003; Mu et al., 2007; Fisher et al., 2008;Leuning et al., 2008; Mu et al., 2011]. We focus here ondescribing the development and progress of two of theleading potential-to-actual ET models—by Fisher et al. [2008]and Mu et al., [2011]—which have been used in a wide varietyof applications and intercomparisons [Fisher et al., 2009;Phillips et al., 2009; Jiménez et al., 2011; Mueller et al., 2011;Vinukollu et al., 2011]. They represent different ideas of howpotential ET should be reduced to actual ET. We shedinsight into why one model performs better than the otherunder some circumstances, and vice versa, against FLUXNETdata.Fluet Chouinard, EtienneTowards a High-Resolution Global InundationDelineation DatasetFluet Chouinard, Etienne 1 ; Lehner, Bernhard 11. McGill University, Montreal, QC, CanadaAlthough their importance for biodiversity, flowregulation and ecosystem service provision is widelyrecognized, wetlands and temporarily inundated landscapesremain poorly mapped globally because of their inherentelusive nature. Inventorying of wetland resources has beenidentified in international agreements as an essentialcomponent of appropriate conservation efforts andmanagement initiatives of these threatened ecosystems.However, despite recent advances in remote sensing surfacewater monitoring, current inventories of surface watervariations remain incomplete at the regional-to-global scaledue to methodological limitations restricting truly globalapplication. Remote sensing wetland applications such asSAR L-band are particularly constrained by imageavailability and heterogeneity of acquisition dates, whilecoarse resolution passive microwave and multi-sensormethods cannot discriminate distinct surface water bodies.As a result, the most popular global wetland dataset remainsto this day the Global Lake & Wetland Database (Lehner andDoll, 2004) a spatially inconsistent database assembled fromvarious existing data sources. The approach taken in thisproject circumvents the limitations of current global wetlandmonitoring methods by combining globally availabletopographic and hydrographic data to downscale coarseresolution global inundation data (Prigent et al., 2007) andthus create a superior inundation delineation map product.The developed procedure downscales inundation data fromthe coarse resolution (~27km) of current passive microwavesensors to the finer spatial resolution (~500m) of thetopographic and hydrographic layers of HydroSHEDS’ datasuite (Lehner et al., 2006), while retaining the high temporalresolution of the multi-sensor inundation dataset. From thedownscaling process emerges new information on thespecific location of inundation, but also on its frequency andduration. The downscaling algorithm employs a decisiontree classifier trained on regional remote sensing wetlandmaps, to derive inundation probability followed by a seededregion growing segmentation process to redistribute theinundated area at the finer resolution. Assessment of thealgorithm’s performance is accomplished by evaluating thelevel of agreement between its outputted downscaledinundation maps and existing regional remote sensinginundation delineation. Upon completion, this project’s willoffer a dynamic globally seamless inundation map at anunprecedented spatial and temporal scale, which will providethe baseline inventory long requested by the researchcommunity, and will open the door to a wide array ofpossible conservation and hydrological modelingapplications which were until now data-restricted. LiteratureLehner, B., K. Verdin, and A. Jarvis. 2008. New globalhydrography derived from spaceborne elevation data. Eos 89,no. 10. Lehner, B, and P Doll. 2004. Development andvalidation of a global database of lakes, reservoirs andwetlands. Journal of Hydrology 296, no. 1-4: 1-22. Prigent,C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews. 2007.Global inundation dynamics inferred from multiple satelliteobservations, 1993–2000. Journal of Geophysical Research112, no. D12: 1-13.Fortin, VincentImproving the Canadian Precipitation Analysis(CaPA) Over the Laurentian Great Lakes ThroughData Assimilation of Radar Reflectivity and GOESImageryFortin, Vincent 1 ; Roy, Guy 2 ; Deacu, Daniel 11. Meteorological Research Division, Environment Canada,Dorval, QC, Canada2. Meteorological Service of Canada, Environment Canada,Montréal, QC, CanadaThe Canadian Precipitation Analysis (CaPA) is theprecipitation analysis system of the Meteorological Serviceof Canada (MSC). It is currently used to obtain a regionaldeterministic precipitation analysis (RDPA) covering all ofNorth America on a 15 km grid. It has a 6h time step and isavailable one hour after time valid. This precipitationanalysis became operational in April 2011. In most ofCanada, the density of the precipitation network isinsufficient to provide an adequate quantitativeprecipitation estimate (QPE) on this temporal and spatialscale. For this reason, CaPA relies on a background fieldprovided by MSC’s regional deterministic prediction system(RDPS), which is based on the Global EnvironmentalMultiscale (GEM) model. In the Laurentian Great Lakesregion, lake-effect precipitation is an important process,especially in late fall and early winter. The lack of reliableprecipitation gauges on the lakes and along the shoreline, aswell as limited skill of the GEM model at predicting lake-61

effect precipitation make it difficult to trust CaPA over theGreat Lakes region. An experimental version of CaPA is ableto assimilate radar reflectivity and GOES imagery, mergingthese informations which are available over the Great Lakeswith gauge data and the GEM model background, but thisproduct is difficult to verify, as there are no gauges over thelakes themselves. We show how hydrological observationscan help assess the skill of the precipitation analysis,through a water balance analysis of each lake.http://www.weatheroffice.gc.ca/analysis/Frankenstein, SusanUsing microwave remote sensing to determinepatterns of swe and melt timing in remoteenvironmentsFrankenstein, Susan 1 ; Deeb, Elias 11. ERDC-CRREL, Hanover, NH, USASatellite microwave data have the ability to provide neardailysnow hydrology predictions in remote areas. Lackingground observations in denied regions, the Army relies onthese satellites to predict seasonal water resources, mobilityimpacts, and flood hazard mitigation. Moreover, a broadapplication of these data is limited by melt heterogeneity incomplex mountain catchments. This research uses a wellinstrumentedmountain test basin in the United States toestablish the relationship between terrain characteristics,satellite-derived snow hydrology parameters, modeling,ground-based observations and snow and water resources.We currently use, data from two passive microwave sensorsto provide near-daily estimates of snow water equivalent(SWE) and snowmelt timing, both vital parameters inmodeling the hydrology of snow-dominated basins. Theseare the Special Sensor Microwave/Imager (SSM/I, ~ 25kmspatial resolution) and the Advanced Microwave ScanningRadiometer (AMSR-E, ~ 12.5km spatial resolution). Bothplatforms have historical periods of record (SSM/I 1987-present; AMSR-E 2002-2011) which are used to establishpatterns of SWE accumulation/ablation and snowmelttiming. The mountainous regions of southwesternColorado, serve as a corollary test basin for the Hindu KushMountains of Afghanistan based on the region havingsimilar topographic relief, elevation, and relatively dryclimatology. The Senator Beck Basin Study Area, San JuanMountains, Colorado is identified as a test case for thisresearch. Since 2003 a full suite of ground-basedmeteorological and energy budget observations have beencollected at two distinct elevation zones in this alpineheadwater catchment. Nearby stream gage data also providerelationships between springtime changes in solar radiation,timing of snowmelt, and influx of water into the system. Thethird component of our investigation is model runs usingthe land surface model FASST (Fast All-season soilSTrength). FASST is a one-dimensional ground andvegetation model developed as part of an Army program toprovide the dynamic terrain response to predictive weatherforcing. Using a full physics mass and energy balanceapproach, FASST calculates the ground’s moisture (liquid +vapor) and ice content, temperature, and freeze/thawprofiles, as well as soil strength and surface ice and snowaccumulation/ depletion. It also calculates the vegetationtemperature profile and vegetation intercepted precipitation.With the historical records of satellite-derived snowhydrology parameters, ground-based observations andaccompanying model runs, a predictive algorithm will beestablished for snowmelt timing in the basin including theeffects of vegetation and terrain complexity.Freeman, AnthonyThe EV-1 Airborne Microwave Observatory ofSubcanopy and Subsurface (AirMOSS)InvestigationFreeman, Anthony 1 ; Moghaddam, Mahta 9 ; Lou, Yunling 1 ;Crow, Wade 2 ; Cuenca, Richard 4 ; Entekhabi, Dara 5 ; Hensley,Scott 1 ; Hollinger, Dave 6 ; Reichle, Rolf 7 ; Saatchi, Sassan 1 ;Shepson, Paul 8 ; Wofsy, Steve 31. Earth Sciences, Jet Propulsion Laboratory, Pasadena, CA,USA2. Hydrology and Remote Sensing Laboratory, USDA,Beltsville, MD, USA3. Harvard University, Cambridge, MA, USA4. Department of Biological & Ecological Engineering,Oregon State University, Corvallis, OR, USA5. Earth, Atmospheric and Planetary Sciences,Massachusetts Institute of Technology, Cambridge, MA,USA6. Forest Service, USDA, Durham, NH, USA7. GSFC, Greenbelt, MD, USA8. Chemistry, Purdue University, West Lafayette, IN, USA9. Electrical Engineering and Computer Science, Universityof Michigan, Ann Arbor, MI, USAAirMOSS is one of the five Earth Venture-1investigations selected in May 2010, with the goal ofimproving the estimates of the North American netecosystem exchange (NEE) through high-resolutionobservations of root zone soil moisture (RZSM). The 5-yearAirMOSS investigation is deigned to overlap with the SMAP62

mission and will address the following science questions: 1.Quantitatively, what are the local-, regional-, andcontinental-scale heterogeneities of RZSM in NorthAmerica? 2. Quantitatively, how does RZSM controlecosystem carbon fluxes at each of these scales? 3. By howmuch will the estimates of North American NEE improvewith the accurate knowledge of both the mean and thevariance of RZSM? To obtain estimates of RZSM and assessits heterogeneities, AirMOSS will fly a newly developedNASA P-band (430 MHz) synthetic aperture radar (SAR) over2500 km2 areas within nine major biomes of north America,from <strong>2012</strong> to 2014. The flights will cover areas containingflux tower sites in regions from the boreal forests in centralCanada to the tropical forests in Costa Rica. The radarsnapshots will be used to generate 100-m resolutionestimates of RZSM via inversion of scattering models ofvegetated surfaces. These retrievals will in turn beassimilated or otherwise used to estimate land modelhydrological parameters over the nine biomes, generating afine-grained time record of soil moisture evolution in theroot zone, and integrated with an ecosystem demographymodel to predict component carbon fluxes. The sensitivityof carbon flux components to RZSM uncertainties andheterogeneity will be quantified. In-situ soil moisture andatmospheric carbon measurements are planned forvalidation of the AirMOSS product suite. The AirMOSSradar is currently under construction at JPL, with firstscience flights expected in June <strong>2012</strong>. In-situ soil sensingprofiles are currently being deployed at the AirMOSS sites,and test flights for atmospheric carbon measurements arealso planned in the next several months. The entire dataprocessing chain, including SAR data processing, radarRZSM retrievals, land surface hydrology modeling, andecosystem demography modeling are being implementedand tested prior to the first science flights. This paper willprovide an overview of the investigation, campaign design,and development status. Part of the research described inthis paper was carried out by the Jet Propulsion Laboratory,California Institute of Technology, under a contract with theNational Aeronautics and Space Administration.French, Andrew N.Evapotranspiration Estimation with SimulatedHyspIRI ObservationsFrench, Andrew N. 1 ; Sanchez, Juan M. 2 ; Valor, Enric 3 ; Coll,Cesar 3 ; Schmugge, Tom 4 ; Thorp, Kelly 1 ; Garcia-Santos,Vicente 31. U.S. ALARC, USDA/ARS, Maricopa, AZ, USA2. Univ. Castilla-La Mancha, Albacete, Spain3. Univ. Valencia, Valencia, Spain4. New Mexico State Univ, Las Cruces, NM, USAAvailability of frequent and high-moderate spatialresolution remote sensing data is important for developingreliable maps of evapotranspiration (ET). These attributesare needed because changes in ET patterns at daily to weeklytime steps and at

models (e.g., 30-100 m). A downscaling and data-mergingalgorithm uses the RFPI maps to map flood extent fromlower-resolution areal flooded fraction (FF) retrieved fromremote sensing observations. The algorithm takes intoaccount retrieval uncertainties, sensor footprint sampling,and prior flood maps to produce a flood extent estimate andan associated error model. In this presentation wedemonstrate the method with simulated future SMAP dataand lower-resolution AMSR-E data. PALSAR scenes fromfour test regions were used to simulate SMAP L-band SARobservations at 1- to 10-km spatial resolution, providingdata on the dependence of inundation mapping errors onbiome type and the trade-offs between resolution and errorin the retrieval process. AMSR-E brightness temperaturetime series were used to exercise the inundation-mappingframework with frequent, lower-resolution FF observations.Flood maps derived from Landsat (30-m resolution) andModerate-resolution Imaging Spectroradiometer (MODIS,500-m) scenes were used for AMSR-E flood map validationbut may in the future be incorporated into the floodmapping process. We discuss the limits of the method forreconstruction of historical flood events from the passivemicrowave data record.Gan, Thian Y.Modeling Gross Primary Production Of DeciduousForest Using Remotely Sensed Radiation AndEcosystem VariablesGan, Thian Y. 1 ; Nasreen, Jahan 11. Dept Civil & Enviro Engineerin, Univ Alberta, Edmonton,AB, CanadaWe explored the potential application of two remotelysensed (RS) variables, the Global Vegetation Moisture Index(GVMI) and the near-infrared albedo (AlbedoNIR), inmodeling the gross primary production (GPP) of threedeciduous forests. For the Harvard Forest (deciduous) ofMassachusetts, it was found that GPP is strongly correlatedwith GVMI (coefficient of determination, R2 = 0.60) duringthe growing season, and with AlbedoNIR (R2 = 0.82)throughout the year. Subsequently, a statistical model calledthe Remotely Sensed GPP (R-GPP) model was developed toestimate GPP using remotely sensed radiation (land surfacetemperature (LST), AlbedoNIR) and ecosystem variables(enhanced vegetation index (EVI) and GVMI). The R-GPPmodel, calibrated and validated against the GPP estimatesderived from the eddy covariance flux tower of the HarvardForest, could explain 95% and 92% of the observed GPPvariability for the study site during the calibration (2000–2003) and the validation (2004–2005) periods, respectively. Itoutperformed the primary RS-based GPP algorithm ofModerate Resolution Imaging Spectroradiometer (MODIS),which explained 80% and 77% of the GPP variability during2000–2003 and 2004–2005, respectively. The calibrated R-GPP model also explained 93% and 94% of the observed GPPvariation for two other independent validation sites, theMorgan Monroe State Forest and the University of MichiganBiological Station, respectively, which demonstrates itstransferability to other deciduous ecoregions of northeasternUnited States.Gan, Thian Y.Changes in North American Snow packs for 1979-2004 Detected from the Snow Water Equivalentdata of SMMR and SSM/I Passive Microwave andrelated Climatic FactorsGan, Thian Y. 1 ; Barry, Roger 2 ; Gobena, Adam 1 ; Rajagopalan,Balaji 31. Dept Civil & Enviro Engineerin, Univ Alberta, Edmonton,AB, Canada2. National Snow and Ice Data Center, University ofColorado-Boulder, Boulder, CO, USA3. Department of Civil & Architectural Engineering,University of Colorado-Boulder, Boulder, CO, USAChanges to the North American (NA) snow packs for1979-2004 were detected from snow water equivalent (SWE)retrieved from SMMR and SSM/I passive microwave datausing the non-parametric Kendall’s test, which agrees withpredominantly negative anomalies in both snow cover andSWE observed in the Northern Hemisphere since the 1980sand significant increase in the surface temperature of NorthAmerica (NA) observed since the 1970s. About 30% ofdetected decreasing trends of SWE for 1979-2004 arestatistically significant, which is about 3 times more thansignificant increasing trends of SWE detected in NA.Significant decreasing trends in SWE are more extensive inCanada (mainly east of the Canadian Rocky Mountains)than in the US, where such decreasing trends are mainlyfound along the American Rockies. The overall mean trendmagnitudes are about -0.4 to -0.5 mm/year which means anoverall reduction of snow depth of about 10 to 13 cm in 26years (assuming an average snowpack density of 0.1) whichcan significantly impact regions relying on spring snowmeltfor water supply. From detected increasing (decreasing)trends of gridded temperature (precipitation) based on theNorth American Regional Reanalysis (NARR) dataset andthe University of Delaware dataset for NA, their respectivecorrelations with SWE data, and other findings such asglobal-scale decline of snow cover and warming temperaturetrends, longer rainfall seasons, etc., it seems the extensivedecreasing trends in SWE detected mainly in Canada aremore caused by increasing temperatures than by decreasingprecipitation. However, climate anomalies could also play aminor role to part of the detected trends, such as PC1 ofNA’s SWE is found to be correlated to the Pacific DecadalOscillation (PDO) index, and marginally correlated to thePacific North American (PNA) pattern.64

Gan, Thian Y.Soil Moisture Retrieval From Microwave andOptical Remotely Sensed DataGan, Thian Y. 1 ; Nasreen, Jahan 11. Dept Civil & Enviro Engineerin, Univ Alberta, Edmonton,AB, CanadaThe objective of this research is to investigate thepotential of using the newly available, quad-polarized,RADARSAT-2 synthetic Aperture Radar (SAR) data in nearsurface soil moisture retrieval. 11 Radarsat-2 images have sofar been acquired over the Paddle River Basin (PRB), Alberta,Canada and 1575 soil samples, from 9 sites (agricultural,herbaceous and pasture land sites) have been collectedwithin the basin on those days when the RADARSAT-2satellite flew over the study site to obtain actual soilmoisture information. The popular theoretical IntegralEquation model (IEM), linear and nonlinear regressions wereused to retrieve soil moisture from the RADARSAT-2 SARdata. Normalized Difference Vegetation Index (NDVI) andLand Surface temperature (LST) from the optical sensor ofthe Moderate resolution Imaging Spectroradiometer(MODIS) have also been used as additional predictors in theregression algorithms. The combined use of HH, VV, and HVradar backscatters, LST and NDVI as the predictorsproduced more accurate soil moisture retrievals than usingonly individual/multiple radar backscatters as thepredictors. This is probably because the HH polarizedbackscatters can penetrate more than the VV counterpartsand hence together they provide more information about thesoil moisture. On the other hand the VV polarizedbackscatters are useful in determining vegetation growthstage, height, type and health while HV and VH polarizedbackscatters provide complementary information aboutvegetation structure. Therefore radar and optical datatogether could provide more information about the surfacecharacteristics and the effects of vegetation on soil moisturethan individual radar backscatters alone. Compared to fieldmeasurements, soil moisture retrieved from RADARSAT-2SAR data by the best regression and the IEM modelsachieved correlation coefficients of 0.89 and 0.91,respectively, at the watershed-scale when soil moisture wasaveraged over all 9 sites. . Retrieve soil moisture usingArtificial Neural Network and Support Vector Machine gavebetter results than that using regression and IEM models.Garg, R. D.Estimating Snow Water Equivalent (SWE) in thePart of North West Himalayan Catchment of BeasRiver, using Synthetic Aperture Radar (SAR) dataThakur, Praveen K. 1 ; Aggarwal, S. P. 1 ; Garg, P. K. 2 ; Garg, R.D. 2 ; Mani, Sneh 31. Water Resources Division, Indian Institute of RemoteSesning (IIRS), Dehradun, India2. Geomatics Eng., Indian Institute of Technolgy (IIT),Roorkee, India3. Avalanche forecasting group, Snow and AvalancheEstablishment SASE), Chandigarh, IndiaThe Snow Water Equivalent (SWE) of the seasonal snowcover can be an important component of the water cycle inmountainous areas, and the knowledge of this temporarystorage term may for example be very valuable for predictingseasonal discharge, for making short-range dischargeforecasts and also for assessing water quality aspects (Braun1991). The present study has been done to estimate the SWEby thermal inertia approach by using ENVISAT-ASAR data.The study area is the catchment area of Beas River up toManali, in part of North West Himalaya, with area of ~350km2. The algorithm used to recover the SWE from SAR datais made of two equations (Bernier and Fortin 1998, Bernieret al 1999). The first equation is the linear relationshipbetween the snow thermal resistance (R) and thebackscattering ratio between a winter image and a reference(snow-free) image. The second equation of the algorithminfers the SWE from the estimated snow thermal resistance(R) and a function of the mean density of the snow pack ().The current study has concludes that this approach can beused for bare soil and grassland land use class of study areaand the snow density is most important and sensitiveparameter for SWE estimation using thermal inertiaapproach.65

Gebregiorgis, Abebe S.Characterizing Satellite Rainfall Errors based onLand Use and Land Cover and Tracing Error Sourcein Hydrologic Model SimulationGebregiorgis, Abebe S. 1 ; Peters-Lidard, Christa D. 2 ; Tian,Yudong 2, 3 ; Hossain, Faisal 11. Civil and Environmental Eng’g, Tennessee TechnologicalUniversity, Cookeville, TN, USA2. Hydrological Science Branch, NASA Goddard SpaceFlight Center, Greenbelt, MD, USA3. Goddard Earth Sciences and Technology Center,University of Maryland Baltimore County, Greenbelt,MD, USAHydrologic modeling has benefited from operationalproduction of high resolution satellite rainfall products. Theglobal coverage, near-real time availability, spatial andtemporal sampling resolutions have advanced theapplication of physically based semi-distributed anddistributed hydrologic models for wide range ofenvironmental decision making processes. Despite thissuccess, the existence of uncertainties inherent in theindirect way of satellite rainfall estimation and hydrologicmodels pose a challenge in making meaningful and practicalpredictions. This study comprises breaking down of totalsatellite rainfall error into three independent components(hit bias, missed precipitation and false alarm),characterizing them as function of land use and land cover(LULC), and tracing back the source of simulated soilmoisture and runoff error in physically based distributedhydrologic model. Here, we asked “on what way the threeindependent total bias components, hit bias, missed, andfalse precipitation, affect the estimation of soil moisture andrunoff in a physically based hydrologic model?” Weimplemented a systematic approach by characterizing anddecomposing the total satellite rainfall error as a function ofland use and land cover of the Mississippi basin. Thisfacilitated the understanding of the major source of soilmoisture and runoff errors in hydrologic model simulationand tracing back of the information to algorithmdevelopment and sensor type. Consequently, we believe sucha forensic approach stands to improve algorithmdevelopment, application and data assimilation scheme forGlobal Precipitation Measurement (GPM) mission. Keywords: total bias, hit bias, missed precipitation, false alarm,soil moisture error, and runoff error, land use and land cover66Gebremichael, MekonnenEstimation of Daily Evapotranspiration over Africausing MODIS/Terra and SEVIRI/MSG dataGebremichael, Mekonnen 1 ; Sun, Zhigang 21. Civil and Env. Engineering, University of Connecticut,Storrs, CT, USA2. National Institute of Environmental Studies, Tsukuba,JapanMost existing remote sensing-based evapotranspiration(ET) algorithms rely exclusively on polar-orbiting satelliteswith thermal infrared sensors, and therefore the resulting ETvalues represent only “instantaneous or snapshot” values.However, daily ET is more meaningful and useful inapplications. In this study, daily ET estimates are obtainedby combining data from the MODIS sensor aboard thepolar-orbiting Terra satellite and the SEVIRI sensor aboardthe geostationary-orbiting MSG satellite. The procedureconsists of estimating the instantaneous evaporative fraction(EF) based on the MODIS/Terra land data products, andestimating the daily net radiation and daily available energybased on the 30-min SEVIRI/MSG data products. Assumingconstant EF during the daytime, daily ET is estimated as theproduct of the SEVIRI/MSG-based daily available energy andMODIS/Terra-based instantaneous EF. The daily ETestimates are evaluated against flux tower measurements atfour validation sites in Africa. Results indicate that thesynergistic use of SEVIRI/MSG and MODIS/Terra has thepotential to provide reliable estimates of daily ET during wetperiods when daily ET exceeds 1 mm/day. The satellite-baseddaily ET estimates however tend to underestimate ET by 13%to 35%. The daily ET estimation algorithm can further beimproved by incorporating a temporal data-fillinginterpolation technique to estimate the unavailable netradiation information during cloudy sky conditions, and byimproving the accuracy of the instantaneous EF. Theassumption of constant evaporative fraction during the dayis reasonable, and does not result in substantial errors in thedaily ET estimates.Gebremichael, MekonnenError Model and Tuning Extremes for SatelliteRainfall EstimatesGebremichael, Mekonnen 11. Civil and Env. Engineering, University of Connecticut,Storrs, CT, USAA new model is developed that generates thedistribution of actual rainfall values for any given satelliterainfall estimate. The model handles the conditionaldistribution as the mixture of a positive continuousdistribution and a point mass at zero. A method is alsopresented to probabilistically transform a set of satelliterainfall estimates into the more accurate rainfall estimates.As our concern lies with extreme precipitation, a peaks overthreshold extreme value approach is adopted that fits aPareto distribution to the large precipitation estimates. Asimple distributional transformation result is then used to

match the two sets of estimates. The method can generallybe used to transform one set of rainfall values to another.The model development and transformation techniqueshave been performed using rain gauge-adjusted groundbasedradar rainfall representing actual rainfall andCMORPH satellite rainfall estimates, available at aresolution of 0.25 degrees x 0.25 degrees and 3-hourly, over adomain of 6.25 degrees x 6.25 degrees in the southernUnited States. The approaches can be replicated in otherregions.Geli, Hatim M.Evapotranspiration of Natural Vegetation usingLandsat and Airborne Remote SensingGeli, Hatim M. 1 ; Neale, Christopher M. 11. Civil and Environmental Engineering, Utah StateUniversity, Logan, UT, USAAreas with natural vegetation are an importantcomponent of the Earth’s ecosystem. Estimates ofevapotranspiration (ET) over such areas are vital forunderstading these systems behavior and water balance.However, the inherent heterogeneity of such land cover inarid and semi-arid areas imposes some modeling challengeswith respect to estimating ET. This analysis is an effort toimprove accuracy of ET estimates over naturally vegetatedsurfaces. We applied the two source energy balance (TSEB)approach of Norman et al. (1995). The two types of theTSEB model formulations i.e. series and parallel resistanceswere examined. Remote sensing datasets from Landsat 5Thematic Mapper and the USU airborne multispectraldigital system were used. These data provide us with abilityto also examine the performance of the models with respectto pixel resolutions ranging from 1 to 30 m in the shortwavebands and 4 to 120 m in the thermal infrared. These areissues that need to be highlighted for future satellite sensorconfigurations. Surface energy fluxes (i.e. Rn, G, H, E) andET were estimated and compared with Bowen ratiomeasurements using 3D footprints analysis. The modelperformance were associated with surface featurescharacteristics including leaf area index (LAI), fraction ofcover (f c), canopy height (h c), radiometric temperature, soilmoisture content, and groundwater table. Such associationwill help in defining/ highlighting strengths and weaknessesof the model configurations. We also investigated theappropriateness and representativeness of the quasi-point BRmeasurements of H compared to those obtained using largeaperture scintillometer (LAS) at the kilometer scale. TheseLAS measurements of H were improved by incorporatingdetailed 1-m scale hc maps from LiDAR (Light Detectionand Ranging) following Geli et al. (2011). Issues regardingerrors when extrapolating instantaneous remote sensingbased estimates of E to daily values of ET were alsodiscussed. The analysis was carried over a riparian zone ofthe Lower Colorado River at the Cibola National WildlifeRefuge, California. The ecosystem comprises a saltcedar(Tamarix ramosissima) forest covers with varying density,arrowweed (Pulchea sericea) and Mesquite (Prosopis glandolusa)interspersed with bare soil over an area of about 4 km by 5km. References Geli, H. M. E., C. M. U. Neale, D. Watts, J.Osterberg, H. A. R. De Bruin, W. Kohsiek, R. T. Pack & L. E.Hipps, (2011). Scintillometer-Based Estimates of SensibleHeat Flux using LiDAR-Derived Surface Roughness, J.Hydromet., (accepted). Norman, J. M., W. P. Kustas, & K. S.Humes, (1995). A two-source approach for estimating soiland vegetation energy fluxes in observations of directionalradiometric surface temperature. Agric. Forest Mete., 77,263–293.Getirana, AugustoThe hydrological modeling and analysis platform(HyMAP): model results and automatic calibrationwith ENVISAT altimetric dataGetirana, Augusto 1, 2 ; Yamazaki, Dai 3 ; Boone, Aaron 4 ;Decharme, Bertrand 4 ; Mognard, Nelly 21. Hydrological Sciences Laboratory, NASA/GSFC,Greenbelt, MD, USA2. LEGOS/CNES, Toulouse, France3. University of Tokyo, Tokyo, Japan4. CNRM, Meteo-France, Toulouse, FranceRecent advances in radar altimetry in the last twentyyears have improved precision in the monitoring of waterheight variability of rivers and lakes located in ungauged orpoorly gauged regions. These advances have motivatedseveral applications of these data in hydrological studies.The next and most promising step for the spatial altimetrytechnology is the Surface Water and Ocean Topography(SWOT) mission, planned to be launched within the decade.In this sense, efforts have been made towards theimprovement of model parameter estimation techniquesbased on assimilation and optimization techniques. Theseefforts have mainly focused on meso and regional scalemodels. In addition, the combination of optimizationtechniques and radar altimetry has been very few exploredup to date, specially with global flow routing (GFR) schemes.As a general rule, GFR schemes are calibrated manuallybased on few available river geometry information and byevaluating maximum likelihood functions for measuring the“closeness” of model outputs and situ or satellite-basedobservations. This process guarantees, in most of cases, acompromise between model efficiency and realistic(physically-based) estimation of model parameters. However,the readily and massive availability of altimetric data and thesuccessful results obtained by previous studies using thesedata makes one ask if similar methodologies could be usedto drive GFR schemes and represent spatiotemporal surfacewater fluxes. This study presents the calibration andevaluation of a new GFR scheme (the Hydrological Modelingand Analysis Platform - HyMAP). HyMAP is a global flowrouting scheme composed of 0.25-degree grid cells over thecontinents and the runoff and baseflow generated by a landsurface model are routed using a kinematic waveformulation through a prescribed river network to oceans orinland seas. The model is composed of four modules: (1)surface runoff and groundwater drainage time delays; (2)67

iver-floodplain interface; (3) flow routing in river channelsand floodplains; and (4) evaporation from open watersurfaces.Also, the platform is equipped with themulti-criteria global optimization scheme MOCOM-UA.Here, results obtained with a manual calibration for theAmazon basin are presented and a sensitivity analysis ofmodel parameters is performed. In addition, an automaticcalibration is carried out in order to evaluate the potential ofretrieving model parameters with ENVISAT altimetry data.The model is capable of representing water discharge andlevel variations consistently. Results of the optimizationexperiments show the potential of using spatial altimetrydata in the automatic calibration of GFR schemes and theneed of integrating such data into parameter estimationprocedures.Gilbertson, LindsayAn Intercomparison of EvapotranspirationEstimation Methods for the Godomey Well Field inBenin, West AfricaGilbertson, Lindsay 1, 2 ; Pohll, Greg 1, 2 ; Huntington, Justin L. 1 ;Silliman, Stephen E. 31. Division of Hydrologic Sciences, Desert ResearchInstitute, Reno, NV, USA2. Graduate Program of Hydrologic Sciences, University ofNevada, Reno, Reno, NV, USA3. Department of Civil Engineering and GeologicalSciences, University of Notre Dame, Notre Dame, IN,USAThe Godomey well field supplies groundwater forCotonou, the largest city in Benin, West Africa. Due to theproximity of the wells to the Atlantic Ocean (5 km north ofthe ocean) and to Lake Nokoue, a shallow lake with highlevels of chloride, the wells are threatened by saltwaterintrusion. Ongoing efforts aim to characterize thisgroundwater system to provide management andsustainability information. As part of this effort, this studywill utilize three methods to estimate evapotranspiration(ET) and improve boundary conditions of an existinggroundwater model for the study area. ET methods include:remotely sensed Moderate Resolution ImagingSpectroradiometer (MODIS) products including theMOD16 Global Terrestrial Evapotranspiration Data Set,complementary relationship evapotranspiration, andevapotranspiration from the Global Land Data AssimilationSystem (GLDAS). Initial efforts demonstrate that ETestimates can be used in conjunction with GLDAS runoffdata to better constrain estimates of recharge for the model.Remote sensing and regional scale hydroclimatic modelingprovide a unique opportunity for improving hydrologicbudgets in developing communities that are data limited.Gladkova, IrinaSeasonal snow cover of Yellowstone estimated withrestored MODIS Aqua, and MODIS Terra snowcover mapsGladkova, Irina 1 ; Grossberg, Michael 1 ; Bonev, George 1 ;Romanov, Peter 3 ; Hall, Dorothy 2 ; Riggs, George 21. Computer Science, City College of New York, New York,NY, USA2. Cryospheric Sciences Branch, NASA Goddard SpaceFlight Center, Greenbelt, MD, USA3. Satellite Meteorology and Climatology Division,NESDIS/STAR, Camp Springs, MD, USAThe area surrounding Yellowstone and Teton nationalparks is unique in many ways. By some measures it is thelargest remaining, nearly intact ecosystem in the Earth’snorthern temperate zone. There are mountains andsubalpine forests. Snow, a critical component of the areawater cycle, covers much of the parks from early winterthrough the spring. While there are a number of snowstations in and around the parks, during winter much of thearea is difficult to access. Remote sensing data such as thestandard snow maps from the NASA MODIS instruments,provide a way to study the buildup and depletion of thesnow cover. Forested regions present a particular challengefor snow cover estimation since the trees capture some of thefalling snow, and obscure much of the snow covering theground. The NASA standard MODIS snow algorithms useinformation from multiple bands of MODIS to mapfractional snow cover and snow albedo. The algorithm foraccomplishing that was designed for both Terra and Aqua.Unfortunately the Terra algorithm cannot be applied directlyto MODIS/Aqua since the algorithm relies on band 6 forwhich 3/4 of the detectors are dead or extremely noisy. As aresult the standard snow cover algorithm for Aqua has beenmodified to use band 7; though this works quite well, itproduces different results which are thought to be inferior toresults produced using the functioning band 6 on the Terra.Recently we have developed a quantitative image restorationtechnique and applied it to MODIS/Aqua band 6 to producean improved Aqua snow mask. Because the algorithm we usefor the snow mask is the same as that used for Terra band 6we can now create two views per day helping mitigateobscuration by clouds and differences of lighting due toshadows from the mountains. We created a database ofrestored Aqua band 6 over the Yellowstone region for the2010-2011 snow season to evaluate the benefit of band 6restoration for snow products. Along with the restoredradiances, we are providing NDVI, thermal image and NDSIinputs along with a band 6 based snow map product. Inaddition, we have re-gridded the restored Aqua based onrestored band 6, and combined Terra data to produce aTerra-Aqua combined Cloud-Gap-Filled (CGF) snow covermap product over the snow season. We will present this CGFwith one that uses the previous Band 7 based snow productas well as validate against measurements from 96 groundstations in that area. The result of this local studydemonstrates the value of using restored band 6 for68

producing CGF snow cover products. The improved abilityusing both MODIS Terra and Aqua to monitor snow coverchange will enable analysis of snow cover variability overseasons and years and the study of changes in streamflowrelated to snow cover. Better evaluation of snow covervariability will contribute to better understanding of thecomplex relationship between snow cover and streamflow inthe context of climate change. Such information may beused to evaluate how changes in snow cover and snowmeltaffect the hydrologic cycle and ecosystem of the Yellowstoneregion.http://glasslab.org/QIRGoodrich, David C.TRMM-PR Satellite-Based Rainfall Retrievals overSemi-Arid Watersheds Using the USDA-ARSWalnut Gulch Gauge NetworkAmitai, Eyal 1, 2 ; Goodrich, David C. 3 ; Unkrich, Carl L. 3 ;Habib, Emad 4 ; Thill, Bryson 21. College of Science, <strong>Chapman</strong> University, Orange, CA,USA2. NASA Goddard Space Flight Center, Greenbelt, MD, USA3. USDA-ARS Southwest Watershed Research Center,Tucson, AZ, USA4. University of Louisiana at Lafayette, Lafayette, LA, USAThe rain gauge network associated with the USDA-ARSWalnut Gulch Experimental Watershed (WGEW) insoutheastern Arizona provides a unique opportunity fordirect comparisons of in-situ measurements and satellitebasedinstantaneous rain rate estimates like those from theTRMM’s Precipitation Radar (PR). The WGEW network isthe densest rain gauge network in the PR coverage area forwatersheds greater than 10 km2. It consists of 88 weighingrain gauges within a 149-km2 area. On average,approximately 10 gauges can be found in each PR field-ofview(~5-km diameter). All gauges are very well synchronized(within seconds with 1-minute reporting intervals). Thisallows generating very-high-temporal-resolution rain ratefields, and obtaining accurate estimates of the area-averagerain rate for the entire watershed and for a single PR field-ofview.In this study, instantaneous rain rate fields from thePR and the spatially interpolated gauge measurements (on a100-m x 100-m grid, updated every 1-min) are compared forall TRMM overpasses in which the PR recorded rain withinthe WGEW boundaries (25 overpasses during 1999-2010).The results indicate very good agreement between the fieldswith high-correlation and low-bias values ( 0.9). The correlation is high atoverpass time, but the peak occurs several minutes after theoverpass, which can be explained by the fact that it takesseveral minutes for the raindrops to reach the gauge fromthe time they are observed by the PR. The correlationimproves with the new version of the TRMM algorithm (V7).The study includes assessment of the accuracy of thereference products.69Goodrich, David C.TRMM-PR Satellite-Based Rainfall Retrievals overSemi-Arid Watersheds Using the USDA-ARSWalnut Gulch Gauge NetworkGoodrich, David C. 3 ; Amitai, Eyal 1, 2 ; Unkrich, Carl L. 3 ;Habib, Emad 4 ; Thill, Bryson 21. NASA Goddard Space Flight Center, Greenbelt, MD, USA2. <strong>Chapman</strong> University, Orange, CA, USA3. Southwest Watershed Research Center, USDA-ARS,Tucson, AZ, USA4. University of Louisiana at Lafayette, Lafayette, LA, USAThe rain gauge network associated with the USDA-ARSWalnut Gulch Experimental Watershed (WGEW) insoutheastern Arizona provides a unique opportunity fordirect comparisons of in-situ measurements and satellitebasedinstantaneous rain rate estimates like those from theTRMM’s Precipitation Radar (PR). The WGEW network isthe densest rain gauge network in the PR coverage area forwatersheds greater than 10 km2. It consists of 88 weighingrain gauges within a 149-km2 area. On average,approximately 10 gauges can be found in each PR field-ofview(~5-km diameter). All gauges are very well synchronized(within seconds with 1-minute reporting intervals). Thisallows generating very-high-temporal-resolution rain ratefields, and obtaining accurate estimates of the area-averagerain rate for the entire watershed and for a single PR field-ofview.In this study, instantaneous rain rate fields from thePR and the spatially interpolated gauge measurements (on a100-m x 100-m grid, updated every 1-min) are compared forall TRMM overpasses in which the PR recorded rain withinthe WGEW boundaries (25 overpasses during 1999-2010).The results indicate very good agreement between the fieldswith high-correlation and low-bias values ( 0.9). The correlation is high atoverpass time, but the peak occurs several minutes after theoverpass, which can be explained by the fact that it takesseveral minutes for the raindrops to reach the gauge fromthe time they are observed by the PR. The correlationimproves with the new version of the TRMM algorithm (V7).The study includes assessment of the accuracy of thereference products.Gosset, MarielleThe Megha-Tropiques MissionGosset, Marielle 1 ; Roca, Remy 21. GET-IRD, Toulouse, France2. LMD-IPSL, Paris, FranceThe Megha-Tropiques mission is an Indo-Frenchmission built by the Centre National d’Études Spatiales(CNES) and the Indian Space Research Organisation (ISRO)and was succesfully launched from India the 12 of october2011. Megha means cloud in Sanskrit and Tropiques is theFrench for tropics. The major innovation of MT is to bringtogether a suite of complementary instruments on adedicated orbit that strongly improves the sampling of thewater cycle elements. The low inclination on the equator

(20°) combined to the elevated height of the orbit (865km)provides unique observing capabilities with up to 6 overpassesper day. The scientific objective of the missionconcerns i) Atmospheric energy and water budget in theinter-tropical zone and at system scale (radiation, latent heat,. . . ) ii) Life cycle of Mesoscale Convective Complexes in theTropics (over Oceans and Continents) and iii) Monitoringand assimilation for Cyclones, Monsoons, Meso-scaleConvective Systems forecasting. These scientific objectivesare achieved thanks to the following payload: SCARAB : wideband instrument for inferring longwave and shortwaveoutgoing fluxes at the top of the atmosphere (cross trackscanning, 40 km resolution at nadir); SAPHIR: microwavesounder for water vapour sounding: 6 channels in the WVabsorption band at 183.31 GHz. (cross track, 10 km) andMADRAS: microwave imager for precipitation: channels at18, 23, 37, 89 and 157 GHz, H and V polarisations. (conicalswath,

performance of the AWRA-L model for estimatingstreamflow and Leaf Area Index (LAI) and investigates itssensitivity to two alternative methods for determining HRUfractions. The analysis is performed using observedstreamflow in 719 unimpaired catchments across Australiaand LAI derived from the Moderate Resolution ImagingSpectroradiometer (MODIS) sensor. The two methods usedto map HRU fractions were derived under different mappingprinciples: the first estimates the fraction cover from timeseriesof greenness from satellite data and assumes that thestable persistent signal is attributable to tall, deep rootedvegetation (trees) and the seasonally varying recurrent signalis attributable to low, shallow rooted vegetation (grasses).The second method to determine HRU fractions is based onlinear discriminant analysis of Landsat Thematic Mappertrained on the basis of time series forested areas with morethan 20% tree cover. The main discrepancy between the tworesulting maps in terms of HRU fractions mapping are inforested areas with sparse canopy cover with highly seasonalunderstorey and in high rainfall and irrigated pastures orcrops. The resulting variations in HRU fractions producedifferences in the streamflow estimated by AWRA-L butthose differences vary across the continent. In some cases,most notably in high and seasonal rainfall areas, streamflowis relatively insensitive to land cover. Comparison of the LAIgenerated by AWRA-L with MODIS data show that themodel produces good estimates of LAI in grassy ecosystems,but poor estimates in heavily forested regions, with both themagnitude and change over time of the modelled LAI signalover exaggerated. Streamflow estimates for these heavilyforested regions can be improved by using MODIS seasonalaverage LAI data to directly drive the model. Futureenhancements to the AWRA-L model, including assimilatingMODIS observations of LAI, spatially explicit vegetationheight, improved soils descriptions and using remotelysensed albedo are further discussed.Guerschman, JuanAn operational actual ET product for AustraliaKing, Edward 1 ; Guerschman, Juan 2 ; van Niel, Tom 3 ; vanDijk, Albert 2 ; Paget, Matthew 4 ; Wang, Ziyuan 4 ; Raupach,Tim 2 ; Haverd, Vanessa 4 ; Raupach, Michael 4 ; Zhang,Yongqiang 2 ; McVicar, Tim 2 ; Miltenburg, Ivo 5 ; Renzullo,Luigi 21. Marine & Atmospheric Reseaerch, CSIRO, Hobart, TAS,Australia2. Land and Water, CSIRO, Canberra, ACT, Australia3. Land and Water, CSIRO, Perth, WA, Australia4. Marine & Atmospheric Research, CSIRO, Canberra, ACT,Australia5. Waterwatch, Wageningen, NetherlandsEight methods for estimating actual evapotranspiration(AET) at monthly or better time step have been assessed overa period of up to six years to identify those most suitable fordeveloping an operational product across all Australianconditions. Sample AET products were solicited fromdevelopers with the specification that they should provideestimates for the whole of Australia at a minimum frequency71of monthly, and at a spatial resolution of at least 5km. Thesetime series were then evaluated against independentestimates of AET from flux measurement sites and multiyearcatchment water balances. The products were alsointer-compared to establish relative differences. It was foundthat for the large areas of Australia where ET is dependentmostly upon precipitation the estimates based on waterbalance modelling approaches performed best. In lateralinflow receiving areas however, only methods that includedan explicit dependence on dynamic remotely sensed inputswere able to adequately capture the additional phenomenacontributing to AET, such as open water evaporation fromwetlands, enhanced ET in irrigated areas and floodplains.Beyond the basic accuracy of any given method, practicalconsiderations such as computational load and robustness,reliability of data sources, and the degree of automation allimpose additional constraints on particular methods thatwere taken into account in assessing suitability forincorporation within an operational product. A method thatappropriately combines the best characteristics of both thewater balance models and the remote sensing methods ismost likely able to meet the goal of improving operationalproduction of AET estimates across the range of Australianconditions. A new product has been developed that blendsthe output of the leading water balance and remote sensingmodels in a trial operational production system. Theevaluation of this product is now underway.Hahn, SebastianImprovements and Challenges in the METOPASCAT Surface Soil Moisture Retrieval SchemeHahn, Sebastian 1 ; Wagner, Wolfgang 1 ; Kidd, Richard 1 ;Hasenauer, Stefan 1 ; Melzer, Thomas 1 ; Paulik, Christoph 1 ;Gruber, Alexander 1 ; Reimer, Christoph 11. Institute of Photogrammetry and Remote Sensing,Vienna University of Technology, Vienna, AustriaThe origin of the METOP ASCAT surface soil moistureretrieval scheme goes back to the mid nineties. At that timethe surface soil moisture retrieval had only been applied inspecific regions and was based on scatterometermeasurements from the Active Microwave Instrument (AMI)onboard the ERS 1 and ERS 2 satellites. A first globalutilisation of the retrieval scheme was implemented in 2002based on a stream of scatterometer data available from thetwo ERS missions between 1991 and 2002. The softwareimplementation of the retrieval algorithm, developed forAMI measurements, is the so-called Water Retrieval Package(WARP). However, it has been successfully adapted for thesuccessor instrument, the Advanced SCATterometer(ASCAT) on board METOP-A, taking advantage of thestrong similarities in the design and configuration of thetwo sensors. The soil moisture retrieval model is basically aphysical motivated change detection method, which hasbeen developed at, and supported by TU Wien (ViennaUniversity of Technology) for the last 15 years. During thedifferent stages of development problems and shortcomingsin the TU Wien model were identified and methods to

correct or account for these issues (e.g. correction forazimuthal anisotropy, wet correction, surface state flag) havebeen developed and implemented. Nevertheless someunresolved problems still persist (e.g. volume scatteringeffects in arid regions) and further research is required inorder to fully understand all effects. Thus, validating andcomparing the METOP ASCAT surface soil moistureretrieval results with field measurements, modelled soilmoisture or other satellite-based products is an importantstep to identify the strengths and weaknesses of the TUWien model. This study presents recent improvements withthe model, current challenges, as well as comparisons withcurrent satellite derived SMOS, AMSR-E and SMALT soilmoisture products.www.ipf.tuwien.ac.atHall, Amanda C.Observing the Amazon Floodplain with RemoteSensing: ICESat, Radar Altimetry and DGPSHall, Amanda C. 1 ; Schumann, Guy 1 ; Bamber, Jonathan 1 ;Baugh, Calum 1 ; Bates, Paul 11. Geographical Sciences, University of Bristol, Bristol,United KingdomThe behaviour of water fluxes in the Amazon floodplainis still poorly understood. With few in-situ gauging stations,and with the ones that are present being on the mainchannel, understanding the flow dynamics of the floodplainis difficult. This study uses the ICESat (Ice, Cloud and landElevation Satellite) sensor GLAS (Geoscience Laser AltimeterSystem) to observe changes in water levels in the floodplain.Complementing this data with radar altimetry, such asTOPEX/Poseidon, will enable us to gain an insight into thecomplex connectivity of the floodplain and its water fluxes.Using DGPS and flow data collected in the field during thesummer of this year will also provide in-situ data to groundtruth these satellite observations. Upon completing this, theresults will be used to assess the results of hydrodynamicsimulations in this area. From comparison with the sparseobservations presently available within the floodplain,current modelling efforts are still unable to simulatefloodplain flow complexity. By using remote sensing acomprehensive data set of floodplain water dynamics can bebuilt up. Investigating lake water levels over several years andcomparing this with nearby lakes, floodplain channels andthe main channel will provide us with unprecedented detail,aiding us in understanding the dynamics of the Amazonfloodplain inundation process.Hauzenberger, Barbara M.Recent glacier changes in the Trans-Alai Mountains(Kyrgyzstan/Tajikistan) derived from remotesensing dataHauzenberger, Barbara M. 1 ; Naz, Bibi S. 2 ; Crawford, MelbaM. 3 ; Bowling, Laura C. 4 ; Harbor, Jonathan M. 11. Earth and Atmosperic Sciences, Purdue University, WestLafayette, IN, USA2. Civil and Environmental Engineering, University ofWashington, Seattle, WA, USA3. College of Agriculture Administration, Purdue University,West Lafayette, IN, USA4. Agronomy, Purdue University, West Lafayette, IN, USAMountain glacier meltwater runoff is an importantwater source in parts of Central Asia that experienceseasonal summer drying. Changes in glacial meltwatersupply may lead to reduced water availability that will havesignificant societal and ecological impacts. Monitoringrecent glacier changes is a powerful tool to provide data thatare important for modeling and assessing future wateravailability. In this study, we focus on the Trans-AlaiMountains which are located at the Kyrgyz and Tajik borderand are part of the northern Pamir. Glacial meltwaterstreams from the Trans-Alai Mountains drain bothnorthwards to Kyrgyzstan and southwards to Tajikistan. Fewdetailed studies have been carried out for this remote area todate. For glacier delineation monitoring, we use Landsatimages from the end of melting season 1975, 1998, 2006 and2011. The dataset is completed by ASTER images and adigital elevation model based on Shuttle Radar TopographyMission (SRTM data). The aim is not only to map changes inglacier terminus extent, but also to quantify the proportionof debris covered ice, bare ice and snow cover for each glacierand period. Future work will use these results as a keycomponent for hydrological modeling. Initial results revealthe presence of surging glaciers in the study area, whichprovides an additional important component to glacierbehavior that needs to be included in estimates of thehydrologic impacts of future glacier changes.Hinkelman, Laura M.Use of Satellite-Based Surface Radiative Fluxes toImprove Snowmelt ModelingHinkelman, Laura M. 1 ; Lundquist, Jessica 2 ; Pinker, Rachel T. 31. Joint Institute for the Study of the Atmosphere andOcean, University of Washington, Seattle, WA, USA2. Department of Civil and Environmental Engineering,University of Washington, Seattle, WA, USA3. Department of Atmospheric and Oceanic Science,University of Maryland, College Park, MD, USASnow processes are important to streamflow, surfacewater availability, groundwater recharge, evapotranspiration,and other aspects of the water cycle. Models that accuratelyrepresent both the timing and spatial distribution ofsnowmelt are essential for improving our understanding of72

oth local and regional hydrology. The greatest potentialsources of error in simulating snowmelt rates and timing areinaccurate solar and longwave radiation inputs. Becauseground-based measurements of radiation are not widelyavailable, many hydrologic models estimate solar inputsfrom the position of the sun and the local diurnaltemperature range. This can lead to errors of up to 50% insnowmelt rates.Hirpa, Feyera A.Assimilation of Satellite Soil Moisture observationsin a Hydrologic Model for Improving StreamflowForecast AccuracyHirpa, Feyera A. 1 ; Gebremichael, Mekonnen 2 ; Hopson,Thomas 3 ; Wojcik, Rafal 41. Civil & Env Engineering, University of Connecticut,Storrs, CT, USA2. Civil & Environmental Engineering, University ofConnecticut, Storrs, CT, USA3. Research Application Laboratory, National Center forAtmospheric Research, Boulder, CO, USA4. Civil & Environmental Engineering, MIT, Boston, MA,USARiver flow forecasts and flood warnings in the UnitesStates are produced by the National Weather Service (NWS)using Sacramento Soil Moisture Accounting (SAC-SMA)model. The forecasts like other common hydrologicsimulations, are subject to uncertainties from differentsources, such as, error in model structure, model input(primarily precipitation), and model state (primarily soilwater content). In this work, simulation experiments havebeen performed by assimilating satellite soil moistureestimates into the SAC-SAM model using the EnsembleKalman Filter (EnKF). The Root River basin, with an area of1593 km2 in Minnesota, is the study watershed. Our resultsdemonstrate the potential and value of assimilating satellitesoil moisture observations in hydrological modeling. Soilmoisture data from SMAP (Soil Moisture Active Passive) cansimilarly be assimilated, when they are made available.Hong, YangHyDAS: A GPM-era Hydrological Data AssimilationSystem for Evaluating the Water Cycle andHydrological Extremes at Global and RegionalScalesHong, Yang 1 ; Xue, Xianwu 1 ; Gourley, Jonathan 21. School of Civil Engineering and Environmental Sciences;Atmospheric Radar Research Center, University ofOklahoma, Norman, OK, USA2. NOAA/NSSL, Norman, OK, USABetter understanding of the spatial and temporaldistribution of precipitation, soil moisture, andevapotranspiration (ET) is critical to hydrologicalapplications. In this talk, we will present a HydrologicalData Assimilation System (HyDAS) that employs theCoupled Routing and Excess STorage (CREST) distributedhydrological model driven by the TRMM/GPM-basedprecipitation, embedded with the Ensemble Square RootKalman Filter (EnSRF) to assimilate AQUA/AMSR-E soilmoisture streamflow signal data and global daily ET, formodeling the spatial and temporal distribution ofhydrological fluxes and storages. The HyDAS can operate inreanalysis mode and in near real-time mode with asimplified data assimilation scheme. A 12+yearTRMM/GPM-era simulation (at 1/8th degree 3-hourresolution) using the HyDAS has been performed andanalyzed at various temporal (climatology, inter-annual,season) and spatial (global, regional, zonal, catchment)scales. This includes comparisons with GLDAS runoff,GRDC discharge data, and MODIS inundation imagery.Performance of the high-resolution HyDAS (~4km) will alsobe evaluated on basins where high-quality groundobservations are available to anticipate GPM-eraprecipitation and SMAP-era soil moisture products.http://hydro.ou.eduHook, Simon J.Warming Trends in Inland Water SurfaceTemperatures from Thermal Infrared SatelliteImageryHook, Simon J. 1 ; Schneider, Philipp 2 ; Hulley, Glynn C. 1 ;Wilson, Robert C. 11. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA2. Norwegian Institute for Air Research, Oslo, NorwaySeveral in-situ studies have recognized that thetemperature of lakes and other inland water bodies are agood indicator of climate variability and more recent studies73

have observed that certain inland waters appear to bewarming more rapidly than nearby air temperatures. We willpresent results from utilizing spaceborne thermal infraredimagery to generate multi-decadal time series of inlandwater surface temperature for approximately 200 of thelargest inland waters in the world. The data used for thispurpose includes imagery from the Advanced Very HighResolution Radiometers (AVHRR), the series of (Advanced)Along-Track Scanning Radiometers ((A)ATSR), and theModerate Resolution Imaging Spectroradiometer (MODIS).Used in combination, these data sets offer a continuous timeseries of daily to near-daily thermal infrared retrievals from1985 through present. We present results of an extendedglobal study of worldwide trends in inland watertemperatures, indicating that the majority of inland watersstudied have warmed significantly over the last few decades.We further discuss distinct regional patterns in these trendsand how they relate to spatial patterns in recently observedglobal air temperature increase. The research provides aunique, global-scale, and consistent perspective on thetemporal thermal properties of large inland water bodiesworldwide. We also identify future research directions andhighlight the potential of new sensors such as theHyperspectral Infrared Imager (HyspIRI) for understandingthe impact of the warming at the local scale.http://largelakes.jpl.nasa.govvalidation must show can be overcome, changes dramaticallyfrom the beginning to the end of the growing season. Andthe significance of improved water cycle predictions in thisregion of the country could have an enormous impactconsidering the annual value of the U.S. maize and soybeancrop (over $80 billion) and its relevance to feeding theworld’s population. Recently the state legislature has createdthe Iowa Flood Center in response to the devastating 1993and 2008 floods. Based at the University of Iowa, the goal ofthe Flood Center is to understand where and why floodingoccurs, improve flood prediction, and mitigate the impactsof flooding in the future. As a result the Flood Center has amajor interest in satellite measurements of soil moisture andprecipitation. In addition, land surface hydrology field siteshave been established by scientists at the USDA ARS (SouthFork of the Iowa River), Iowa State University (IowaValidation Site), and the University of Iowa (Clear CreekObservatory). Finally, a large EPSCoR grant has beenawarded to Iowa State University to study energy flows inthe biosphere. The thrust in wind energy will examine theimpact of wind turbines on local land-atmosphereinteractions, while the plant-based biofuel thrust willinvestigate water and energy cycle impacts. This poster willreview these research activities and propose appropriatesynergy that could lead to better science and the applicationsof that science to benefit society.Hornbuckle, Brian K.Iowa: Field (Experiment) of Dreams?Hornbuckle, Brian K. 1 ; Kaleita, Amy 1 ; Hatfield, Jerry 2 ;Prueger, John 2 ; Logsdon, Sally 2 ; Krajewski, Witold 3 ; Kruger,Anton 3 ; Takle, Gene 1 ; Franz, Kristie 1 ; Linderman, Marc 3 ;Basu, Nandita 31. Iowa State University, Ames, IA, USA2. USDA ARS, Ames, IA, USA3. The University of Iowa, Iowa City, IA, USATwo major NASA satellite remote sensing instrumentsare scheduled to launch within the next three years: the SoilMoisture Active Passive (SMAP) mission in late 2014; and theGlobal Precipitation Mission (GPM) in 2014. Since bothmissions examine aspects of land surface hydrology that arestrongly related to each other (soil moisture andprecipitation) and each will require extensive groundvalidation, it makes sense to think about whether a singleintegrated field experiment in 2015 could meet the needs forground validation, result in more science, and lead to a widerarray of applications research, especially in light of NASA’sbudget and the nation’s economic situation. There areseveral factors that point to Iowa as the place to hold amajor SMAP validation field experiment. There is a majorUSDA ARS laboratory with the prerequisite expertise inplace (National Laboratory for Agriculture and theEnvironment). There is a history of large field experiments(SMEX02 and SMEX05). The landscape is nearlyhomogeneous (nearly 90% of the land area in many Iowacounties consists of maize and soybean row crops). Theamount of vegetation, which has a negative effect on the soilmoisture remote sensing signal and hence is a challenge that74Hosseini, Seyed Z.Relationship between terrestrial vegetationdynamic and precipitation using remote sensingand geostatistics in an arid ecosystemHosseini, Seyed Z. 1 ; Propastin, Pavel 1 ; Kappas, Martin 1 ;Shahriary, Eahsan 11. Cartography, GIS and Remote Sensing Department,University of Goettingen, Goettingen, GermanyThe aim of this study is to find the relationshipsbetween precipitation and terrestrial vegetation dynamics inan arid ecosystem of Yazd province, Iran. The analysis wasbuilt upon a monthly time series of Normalized DifferenceVegetation Index (NDVI) derived from the Advanced VeryHigh Resolution Radiometer (AVHRR) onboard themeteorological satellite of National Oceanic andAtmospheric Administration (NOAA), precipitation datafrom meteorological stations across the study area duringthe period of 1996-2008, groundwater and soil moisturedata. Monthly, seasonal and annual precipitation maps wereproduced using the co-kriging interpolation approach incombination with a digital elevation model (DEM). Interannualand intra-annual relationship between precipitationvariations and vegetation dynamics were examined by meansof linear and non-linear regressions. Results showed that thestrength of the relationship between precipitation and NDVIis depended on species combination of vegetation cover, soilmoisture and level of ground water. High response ofvegetation to precipitation was observed in the northern andeastern parts of the study area where forbs and grasses suchas Scariola orientalis, Launaea acanthodes, Stipa barbata,

Euphorbia heterandena, and Echinops orientalis areconsiderably exist. On the other hand, the correlation is low(non significant) in the southwestern parts of the area thatcould be due to the existence of some shrubs and bushessuch as Tamarix ramosissima, Cornulaca monacantha,Seidlitzia rosmarinus, Ephedra strobilacea, Haloxylonaphyllum and Calligonum comosum are not sensitive toprecipitation.Howington, Stacy E.High-Fidelity Numerical Simulation to SupportInterpretation of Electro-optical and InfraredImageryHowington, Stacy E. 1 ; Ballard, Jr., Jerrell R. 1 ; Peters, John F. 1 ;Eslinger, Owen J. 1 ; Fairley, Josh R. 1 ; Kala, Raju V. 1 ; Goodson,Ricky A. 1 ; Hines, Amanda M. 1 ; Price, Stephanie J. 11. US Army, Vicksburg, MS, USAA high-resolution modeling suite was constructed tocreate synthetic sensor imagery like that produced byinfrared and optical sensors aboard unmanned aerialvehicles or ground-based vehicles. This system was built toexplore the interaction of sensors and the environment byincluding physics-based models that simulate threedimensional,partially-saturated fluid flow and heattransport in soils, structures, and some vegetation usingfinite elements[1]. The computed scene is sampled using anenergy-based ray caster to create an idealized, near-groundradiance image. Atmospheric effects are imposed and theimage is passed through a sensor model to produce asynthetic image as seen by the particular sensor. Because themodels are three dimensional, they include lateral flow ofheat and moisture. This permits the simulation ofheterogeneous soils, variable surface soil moisture, and theaccurate representation of transient thermal shadows.Because, for these platforms, the sensor position ranges fromnear ground level to only a few thousand feet, the imageresolution is quite good and even small features are visible.While this tool was built to improve the interpretation ofsensor imagery collected by aerial and ground-based sensingplatforms, it also helps understand how to compare imagescollected at other resolutions, by other remote sensing assets.For example, it permits straightforward upscaling ofradiance from complex scenes to a scale typical of satellitedata. The tool also may help in disaggregating coarse scaleobservations. Downscaling from the scale of satelliteimagery to finer resolution is non-unique, but is open tostatistical comparison when coupled with simulation on arealistic, representative sub-pixel scene. If the simulatedphysics are credible, numerical approximation offers a way toexplore cause-and-effect and sensitivities in satellite imageryby offering exact knowledge of the system being sampled. Italso allows for comparing orientation and time-of-dayeffects with absolute confidence that no other parameterschanged between sampling events. The numerical approacheliminates georegistration issues, making it ideal forexploring sensor fusion concepts. This presentation willdescribe the computational framework and the physicsrepresented in the high-fidelity modeling tool and exploreupscaling of radiance for varying soil moisture distributionsand three-dimensional thermal shadows. [1] Howington, S.E., Peters, J. F., Ballard, Jr., J. R., Eslinger, O. J., Fairley, J. R.,Kala, R. V., Goodson, R. A., Hines, A. M., and L. D. Wakeley, “Using Computer Simulation to Explore the Importance ofHydrogeology in Remote Sensing for Explosive ThreatDetection”, book chapter accepted for publication in:Mather, J. D. and Rose, E. P. F. (eds.) 200 Years of BritishHydrogeology: Military Uses of Hydrogeology, GeologicalSociety of London, Special Publications, to appear in <strong>2012</strong>.Hsu, Nai-Yung C.Satellite Remote Sensing of Snow/Ice Albedo overthe HimalayasHsu, Nai-Yung C. 1 ; Tsay, Si-Chee 1 ; Gautam, Ritesh 2, 11. NASA Goddard SFC, Greenbelt, MD, USA2. Universities Space Research Association, Columbia, MD,USAThe Himalayan glaciers and snowpacks play animportant role in the hydrological cycle over Asia. Theseasonal snow melt from the Himalayan glaciers andsnowpacks is one of the key elements to the livelihood of thedownstream densely populated regions of South Asia.During the pre-monsoon season (April-May-June), SouthAsia not only experiences the reversal of the regionalmeridional tropospheric temperature gradient (i.e., the onsetof the summer monsoon), but also is being bombarded bydry westerly airmass that transports mineral dust fromvarious Southwest Asian desert and arid regions into theIndo-Gangetic Plains in northern India. Mixed with heavyanthropogenic pollution, mineral dust constitutes the bulkof regional aerosol loading and forms an extensive andvertically extended brown haze lapping against the southernslopes of the Himalayas. Episodic dust plumes are advectedover the Himalayas, and are discernible in satellite imagery,resulting in dust-capped snow surface. Motivated by thepotential implications of accelerated snowmelt, we examinethe changes in radiative energetics induced by aerosoltransport over the Himalayan snow cover by utilizing spaceborne observations. Our objective lies in the investigation ofpotential impacts of aerosol solar absorption on the Top-of-Atmosphere (TOA) spectral reflectivity and the broadbandalbedo, and hence the accelerated snowmelt, particularly inthe western Himalayas. Lambertian Equivalent Reflectivity(LER) in the visible and near-infrared wavelengths, derivedfrom Moderate Resolution Imaging Spectroradiometerradiances, is used to generate statistics for determiningperturbation caused due to dust layer over snow surface inover ten years of continuous observations. Case studiesindicate significant reduction of LER ranging from 5 to 8%in the 412-860nm spectra. Broadband flux observations,from the Clouds and the Earth’s Radiant Energy System, arealso used to investigate changes in shortwave TOA flux overdust-laden and dust-free snow covered regions. Additionally,spatio-temporal and intra-seasonal variations of LER, alongwith snow cover information, are used to characterize the75

seasonal melt pattern and thus to distinguish theoutstanding aerosol-induced snowmelt signal. Results fromthis observational work are expected to provide betterunderstanding of the radiative impact of aerosols over snowsurface, especially its role in the Himalayan hydroglacialogicalvariability.Huete, Alfredo R.Shifts in Rainfall Use Efficiency and PrimaryProduction along a Savanna Aridity GradientAssessed Using Satellite and Flux Tower Time SeriesDataHuete, Alfredo R. 1 ; Eamus, Derek 1 ; Ponce, Guillermo E. 3 ;Moran, M. S. 2 ; McVicar, Tim R. 4 ; Donohue, Randall 4 ;Restrepo-Coupe, Natalia 1 ; Davies, Kevin 1 ; Glenn, Edward P. 3 ;Cleverly, James 1 ; Boulain, Nicolas 1 ; Beringer, Jason 5 ; Hutley,Lindsay 61. Univ of Technology, Sydney, NSW, Australia2. USDA-ARS, Tucson, AZ, USA3. University of Arizona, Tucson, AZ, USA4. CSIRO Land and Water, Canberra, ACT, Australia5. Monash University, Clayton, VIC, Australia6. Charles Darwin University, Darwin, NT, AustraliaAustralia’s climate is extremely variable with interannualrainfall at any location varying up to eight-fold. In thenorthern tropical savannas there is also significantmonsoonal rainfall variability with pronounced seasonal dryperiods. Understanding water and productivity relationshipsrepresent key issues in climate change models that aim topredict how carbon and water relationships will shift withprojected changes in the frequency, timing, amount andintensity of rainfall. The goal of this study was to investigatethe relationships of above-ground net primary production(ANPP) with rainfall variability along the Northern AustraliaTropical Transect (NATT). We combined 11 years of MODISenhanced vegetation index (EVI) with rainfall data from theTropical Rainfall Monitoring Mission (TRMM) to assesslarge area spatial and temporal patterns in above-groundvegetation productivity (ANPP) and rainfall use efficiency(RUE), defined as ANPP divided by annual rainfall. ANPPvalues were retrieved by (1) coupling seasonal EVI values at16-day increments with tower flux measurements of grossprimary production (GPP) at 3 tower sites along the ariditygradient, followed by (2) annual integration of EVI values(iEVI) from baseline values with zero GPP fluxes, and (3)adjustments for ecosystem respiration. Rainfall useefficiencies were computed for each year as the slope of theiEVI by the annual rainfall. We found strong cross-siteconvergence of seasonal and interannual satellite EVI valueswith tower GPP fluxes at the three sites. Baseline EVI valuesenabled separation of tree and grass ANPP. As expected,positive curvilinear relationships were found between iEVIand annual rainfall with decreasing sensitivity of iEVI toadditional rainfall at the more humid regions of thetransect. We found ANPP values decreased from the humidnorthern savannas to the more southern arid portions,however, RUE increased along the same transect from north76to south resulting in the highest levels of ANPP per unitrainfall in the more arid savannas. Overall, the wet and drysavannas converged to a common and maximum RUE, orRUEmax, when plotted using the driest year at each pixel.However, the most humid northern tropical savannasyielded unexpectedly lower RUE and ANPP values, partlyattributed to a deficiency in tree leaf area to capture light forphotosynthesis. Rainfall and ANPP variability across thetransect were highest over the more grassland dominatedregions of the savanna, or lowest tree-grass ratiosdemonstrating a higher sensitivity of grassland biomes toclimate change relative to the more woody dominatedsavanna and forest biomes. The results of this study suggestthat commonly accepted patterns of ANPP response torainfall may not apply in tropical wet-dry savannas underpredicted climate change.Huffman, George J.Upgrades to the Real-Time TMPAHuffman, George J. 2, 1 ; Bolvin, David T. 2, 1 ; Nelkin, Eric J. 2, 1 ;Adler, Robert F. 3 ; Stocker, Erich F. 11. ESD, NASA GSFC, Greenbelt, MD, USA2. Science Systems and Applications, Inc., Lanham, MD,USA3. ESSIC, Univ. of Maryland, College Park, College Park,MD, USAThe TRMM Multi-satellite Precipitation Analysis(TMPA) provides 0.25°x0.25° 3-hourly estimates ofprecipitation in the latitude band 50°N-50°S in two productsets. First, it is computed 6-9 hours after real time usingprecipitation estimates from imager and sounder passivemicrowavesatellite instruments, and geosynchronous-orbitIR (geo-IR) data, all intercalibrated to a single TRMM-basedstandard, the TMI-GPROF product. Second, the TMPA iscomputed about two months after the end of each calendarmonth (in the current Version 7) using the same satellitedata as in the real time, but calibrated to the TRMMCombined Instrument (TCI) product, with input frommonthly rain gauge analyses. Respectively, these two versionsare referred to as the real-time TMPA-RT (3B42RT) andresearch TMPA (3B42) products. Recently, these productshave been revised to Version 7 (after a lengthy delay due toinput data issues). One key change is that we have developeda computationally feasible scheme for reprocessing theTMPA-RT for the entire TRMM record. Users stronglyadvocated this innovation, and early results will be shown.The reprocessing is important not only for providing alonger record, but also for incorporating more-consistentarchives of input data. The time series of the RT andresearch products are similar, although the research productperforms better both in terms of bias and random error.Over land, this improvement is due to both the TCIcalibration and the use of gauges, while over ocean it is theresult of TCI calibration alone. Climatological calibration forthese factors was instituted in the RT processing duringVersion 6 and it has been continued in Version 7, with thenecessary recalibrations to the Version 7 production data.The second part of the study will summarize early results on

the effectiveness of this calibration over the entire datarecord.Hur, YoomiSerious Radio Frequency Interference from SMOS:Case study in East AsiaHur, Yoomi 1 ; Choi, Minha 11. Civil and Environmental Engineering, Hanyanguniversity, Seoul, Republic of KoreaSoil moisture is important for the global hydrologiccycle. The ground based soil moisture measurements cannotbe used as representative data at regional scale. To overcomethis situation, soil moisture is measured by remote sensingtechnology which has a remarkable advantage with spatialextent. The soil moisture and ocean salinity (SMOS) missionhas provided land surface factors for soil moisture and seasurface factors for a salinity sensing. It was launched onNovember 1, 2009 as European Space Agency`s (ESA) EarthExplorer series. SMOS is the apparatus observing soilmoisture every 1 to 3 days at 43km spatial resolution. It usesL-band (1.4GHz) to measure brightness temperature (Tb).The SMOS retrieval algorithm is backward model. If thecalculated Tb from assumed soil moisture is equal toobserved Tb, the corresponding soil moisture is chosen as anadequate value. However acquisition rates from SMOSretrieval algorithm system are too low because L-bandobservation was corrupted by Radio Frequency Interference(RFI) in East Asia. The main objective of this study isdeveloping improved soil moisture retrieval algorithm whichcopes with RFI problems thereby comparing retrieved soilmoisture and ground based soil moisture. Keywords: SoilMoisture, SMOS, Retrieval Algorithm, East AsiaIndu, JayaluxmiRAIN/NO RAIN CLASSIFICATION OVERTROPICAL REGIONS USING TRMM TMIIndu, Jayaluxmi 1 ; Kumar, D Nagesh 11. Civil Engineering, Indian Institute of Science, Bangalore,IndiaThis study focalizes on the comparative assessment ofexisting “rain” or “no rain” classification (RNC)methodologies over land surface. Using the data productsfrom Tropical Rainfall Measuring Mission’s PrecipitationRadar (PR) and Microwave Imager (TMI), this work revealsthe shortcomings of existing overland RNC methods hingedon scattering signatures from 85 GHz high frequencychannel with special reference to the Indian subcontinent.Overland RNC of microwave radiometer brightnesstemperatures (Tb) offers a myriad of complications as landsurface presents itself as a radiometrically warm and highlyvariable background. Hence, sensitivity analysis of Tbcaptured at different microwave frequencies to near surfacerain (NSR) rate is of considerable importance. Variability ofTb to NSR is investigated using exploratory data analysis(EDA), together with probability density functions (pdfs).Results indicate that the inclusion of 37 GHz verticalpolarization channel for the computation of estimated85GHz Tb is essential, due to its prominent correlation withNSR. Also relevant, were the contributions from 19 GHzchannels (both horizontal and vertical). A novel attempt hasbeen made to assess the performance of some statisticaldescriptors to increase the accuracy of RNC. Thecomparative results are presented extensively in the form ofcontingency tables and kappa values. The descriptor givingbest results from the analysis was used to formulate aregression relation with the rain rate (RR). Furthermore, adetailed examination on the use of Empirical OrthogonalFunctions (EOF) to improve rain retrieval accuracy is made.Analysis reveals that, for TMI, the first three EOFs weredeemed sufficient to fully explain the variability offered bythe 9 channels. A regression based relationship wasestablished between RR and EOF. A comparative analysis wasconducted between the regression relation of RR with EOFand RR with “best RNC descriptor”. Results reveal that theuse of efficient methodologies for overland RNC doesimprove the classification accuracy (upto less than 10%).Irmak, AyseRequirements for Evapotranspiration at Field-Scaleusing Landsat-scale Remote Sensing-Based EnergyBalance in the Central Platte and Sand Hills ofNebraska, USAIrmak, Ayse 1 ; Ratcliffe, Ian 1 ; Healey, Nathan 1 ; Ranade,Pariskit 1 ; Allen, Richard 21. School of Natural Resources, University of Nebraska,Lincoln, NE, USA2. University of Idaho, Kimberly, ID, USAWater is the most important constraint in most of theCentral High Plains of the U.S.A.. Local, state and federalwater management regulatory agencies need good qualitywater use estimates for different land surfaces to assess shortand long-term water management, planning, and allocationson a field scale and watershed scale. Land surface energybalance models are routinely used to produceevapotranspiration (ET) maps using satellite remote sensingdata and weather measurements. High resolution thermalimagery from satellites such as Landsat make it possible tomap within field ET variability. The main objective ofresearch was to understand the surface energy fluxes mainlyevapotranspiration using ground-based observations andremote sensing technique in Nebraska (NE) and todetermine dependable means to estimate time-integrated ET,including that occurring between satellite image dates. Weused measured ET in the Sand Hills of NE using BowenRatio Energy Balance System (BREBS), which provided ET ata footprint scale. The Sand Hills region of NE is one of thelargest grass-stabilized sand dune formations in the world,with an area of roughly 50,000 - 60,000 km2 that supports asystem of five major land cover types: (1) lakes, (2) wetlands(with lakes, ~5%), (3) subirrigated meadows (water table iswithin ~1 m of surface; ~10%), (4) dry valleys (water table is1-10 m below surface; ~20%), and (5) upland dunes (watertable is more than 10 m below surface; ~65%). We applied77

the METRIC (Mapping Evapotranspiration at highResolution using Internalized Calibration) model with andwithout slope-aspect based radiation algorithms and withand without terrain-roughness-related aerodynamicalgorithms to map ET for the study area. METRIC modelpredictions were compared with measurements from BREBSto evaluate generic model accuracy for estimating daily ET.Ishimoto, HiroshiMicrowave Scattering Properties of ComplexShaped SnowflakesIshimoto, Hiroshi 1 ; Aonashi, Kazumasa 11. Meteorological Research Institute, Tsukuba, JapanIn the algorithm of precipitation retrieval by multichannelsatellite microwave radiometer, forward calculationsthat estimate microwave brightness temperatures in thegiven liquid and ice water profiles are crucial. Within someassumptions related to radiative transfer calculations, singlescattering property of snow particles is an important factor.We have investigated the microwave scattering properties ofsnowflakes for the purposes of improving the accuracy offorward calculation in the precipitation retrieval algorithmof the GSMaP (Global Satellite Mapping of PrecipitationProject). Since the shapes of snowflakes are highly complex,simple models of their shapes, such as equivalent volumespheres and soft spheres/spheroids, may cause large errors inestimating ice water contents. In this work, we proposed amodel of complex shaped snowflakes. The modeledsnowflakes were the aggregates of planar crystals and theshape of the crystals were determined from sampled images.Furthermore, the overall shapes and masses of the modeledaggregates were chosen to be consistent with the measuredgeometries of the snowflakes. By using this shape model andusing Finite-Difference Time-Domain (FDTD) method,electromagnetic scattering properties of snowflakes atfrequencies 89GHz and 36GHz were estimated. The resultsof some scattering properties were compared with those ofour previously proposed fractal snowflake models as well asthose of volume equivalent spheres. It is found that ournewly developed snowflake model shows similar sizedependences for scattering cross sections and asymmetryfactors to those of fractal models with fractal dimensions1.8~2.1. For the next step, we are planning to investigate theeffect of ice melting in microwave radiative properties. Anapproach by using numerical simulations of hydrodynamicsfor the deformation of ice particles is briefly discussed.78Numerically created aggregate for a model of snowflakes.Jackson, Thomas J.Advances in the Validation of Satellite SoilMoisture Products with In Situ ObservationsINVITEDJackson, Thomas J. 11. Hydrology & Remote Sensing Lab, USDA ARS, Beltsville,MD, USASatellite-based remote sensing of soil moisture has comea long way in the past decade with regard to providing anaccurate and reliable product. In the early years (1970s) suboptimalsensors designed for other applications were used toexplore the concept without having a planned groundvalidation component. Beginning with the AdvancedMicrowave Scanning Radiometer (AMSR and AMSR-E) in2002, better sensors became available and soil moistureremote sensing was supported as a standard product with adedicated validation program. With the launch of the SoilMoisture Ocean Salinity (SMOS) mission in 2009 and theplanned Soil Moisture Active Passive (SMAP) satellite in2014, we now enter an era of dedicated soil moisturemissions. SMAP, as well as other soil moisture missions, havespecific requirements for validation that include accuracy, aswell as a defined timeline (~15 months after launch forSMAP). One of the most important methodologies availablefor validating satellite soil moisture is data from in situobserving networks. The technology of in situ soil moistureremote sensing has also advanced over the same period thatsatellite sensing progressed. Prior to 2000, the majority ofthe routine measurements available were made using eithergravimetric or neutron probes on an infrequent basis. As aresult of more reliable sensors and improved data acquisitionsystems, the number of in situ soil moisture networksavailable has increased. Satellite missions produce globalproducts; therefore, it is desirable we continue the expansionof the number and geographical distribution of thesenetworks. Unfortunately, these networks have evolvedwithout national or international standardization, which

presents challenges to the validation of satellite-based soilmoisture remote sensing, which requires the integration ofnumerous networks. In addition to the issues of a limitednumber of sites and their standardization, the validation ofsatellite-based soil moisture products faces the challenge ofresolving the disparate scales of the sensor footprints (~10-40 km) and the in situ sensors (several centimeters).Background on the evolution of satellite-based soil moistureremote sensing validation, the status and expected advancesin both the satellite and in situ resources, and approachesthat are bring used to address the issues will be presented.USDA is an Equal Opportunity Employer.Johnson, Shawana P.Geospatial Intelligence and Biomass Research forFreshwater, Food, Feed and EnergyJohnson, Shawana P. 1 ; Hendricks, Robert C. 2 ; Venners, JohnP. 3 ; Thomas, Anna E. 41. Global Marketing Insights, Inc, Independence, OH, USA2. Glenn Research Center, NASA, Cleveland, OH, USA3. Bio Fuel, BioEcoTek-Hawaii, Honolulu, HI, USA4. Georgia Institute of Technology, Atlanta, GA, USAWe are a planet in transition, and as freshwater resourcesmelt away or “dry up,” severe conflicts between agriculturaland domestic water rights will place high demands forremediation of brackish waters and restricted usage.Suchclimatic changes and demands call for “Green PlanetArchitecture,” creating symbiotic relations betweenecological systems and geospatial intelligence (based onsatellite surveillance and ground sources data). Thearchitecture can provide predictive and preventive modelingnetworks that reflect global needs and induce the possibilityof corrective action. Global distributed network connectedsources of food, feed, freshwater, waste-recovery and energyin closed ecological cycle climate adaptive systems arerequired to provide environmentally neutral- to-positivebenefits (returning more to the environment than takingfrom it). “Green Planet Architecture” provides for theintroduction and development of new climatic adaptivebiomass sources for feed and food that displace the intensedemand for energy, as well as those already known but littledeveloped. Currently, some energy forms can be diverted foraviation or other fuels; safe, high energy-density, sustainable,secure, and economically viable fuels are a premium in theaviation industry. Biomass residuals provide land-basedpower plants for general power and transportation. Thispaper will demonstrate the application of geospatialintelligence and the ways in which it is synergistic with thedevelopment of salicornia, seashore mallow, castor, moringa,and other plants that can off-load energy sources for use aspremium fuels, such as those required for aviation and themanagement of freshwater. Biomass fuel research anddevelopment will benefit fueling and energy in the nearterm,but freshwater food and feed in the far-term. Theopportunities are of enormous proportions to providehumanity with freshwater, food, feed and energy. Geospatialintelligence data are being used globally for virtuallythousands of unique and complementary agriculture, watermanagement, carbon management and applications. NASAsatellite data in particular is of high value in these projectssince it is those sensors such as MODIS which provide themost frequent global coverage. There is much work beingdone both within NASA and with external companies tofurther the potential of geospatial intelligence. The Decadalearth science survey brings together the work of manydifferent agencies such as NASA and NOAA (NationalOceanographic and atmospheric Administration) to studyan effective approach of space-observation systems. Over 15datasets will be reviewed to determine their application andimpact to the model of Green Planet Architecture. Advancesin technology further enable data collection and have beenproven for water and snow distribution, ocean salinity, andwind patterns and data ingest. Combining thesetechnologies with results from the Decadal missions willexpand current information capabilities to learn about soilcondition, moisture, and nutrients, pathogen and otherinvasive species, and more.www.globalinsights.comJung, Hahn ChulImproved calibration of modeled discharge andstorage change in the Atchafalaya Floodplain usingSAR interferometryJung, Hahn Chul 1 ; Michael, Jasinski 1 ; Kim, Jin-Woo 2 ; Shum,C.k. 2 ; Bates, Paul 3 ; Neal, Jeffrey 3 ; Lee, Hyongki 4 ; Alsdorf,Doug 21. Hydrological Sciences, NASA GSFC, Greenbelt, MD, USA2. School of Earth Sciences, The Ohio State University,Columbus, OH, USA3. School of Geographical Sciences, University of Bristol,Bristol, United Kingdom4. Department of Civil and Environmental Engineering,University of Houston, Houston, TX, USAThis study focuses on the feasibility of using SARinterferometry to support 2D hydrodynamic modelcalibration and provide water storage change in thefloodplain. Two-dimensional (2D) flood inundationmodeling has been widely studied using storage cellapproaches with the availability of high resolution, remotelysensed floodplain topography. The development of coupled1D/2D flood modeling has shown improved calculation of2D floodplain inundation as well as channel water elevation.Most floodplain model results have been validated usingremote sensing methods for inundation extent. However, fewstudies show the quantitative validation of spatial variationsin floodplain water elevations in the 2D modeling sincemost of the gauges are located along main river channelsand traditional single track satellite altimetry over thefloodplain are limited.. Synthetic Aperture Radar (SAR)interferometry recently has been proven to be useful formeasuring centimeter-scale water elevation changes over thefloodplain. In the current study, we apply the LISFLOODhydrodynamic model to the central Atchafalaya River Basin,Louisiana, during a 62 day period from 1 April to 1 June79

2008 using two different calibration schemes for Manning’sn. First, the model is calibrated in terms of water elevationsfrom a single in situ gauge that represents a more traditionalapproach. Due to the gauge location in the channel, thecalibration shows more sensitivity to channel roughnessrelative to floodplain roughness. Second, the model iscalibrated in terms of water elevation changes calculatedfrom ALOS PALSAR interferometry during 46 days of theimage acquisition interval from 16 April 2008 to 1 June2009. Since SAR interferometry receives strongly scatters infloodplain due to double bounce effect as compared tospecular scattering of open water, the calibration showsmore dependency to floodplain roughness. An iterativeapproach is used to determine the best-fit Manning’s n forthe two different calibration approaches. Results suggestsimilar floodplain roughness but slightly different channelroughness. However, application of SAR interferometryprovides a unique view of the floodplain flow gradients, notpossible with a single gauge calibration. These gradients,allow improved computation of water storage change overthe 46-day simulation period. Overall, the results suggestthat the use of 2D SAR water elevation changes in theAtchafalaya basin offers improved understanding andmodeling of floodplain hydrodynamics.Kahime, KholoudWater Vulnerability, Agriculture and EnergyImpacts of Climate Change in Morocco: A CaseStudy the Region of AgadirKahime, Kholoud 1 ; Messouli, Mohammed 11. University of Marrakech, Marrakech, MoroccoOver Morocco, the Intergovernmental Panel on ClimateChange models predict a warming between of 0.6 C to 1.1 Cand a 4% reduction in rainfall by 2020. These climatechanges will have adverse effects on ecosystems and waterresources. Marine ecosystems, vegetation cover and inparticular agriculture will be severely affected. This study,performed over the region Agadir, is aimed at assessing thevulnerability of this region to climate change, and thisthrough a survey of 240 people including policy makers,farmers, employees of the tourism sector, youth anddifferent social actors representing the entire region. Thestudy shows that water and agriculture sectors are highlyvulnerable and unless some measures are taken, predictableconsequences will ensue. The study also shows that there isno engagement from citizens, which make the situation evenunsustainable and no real communication between policymakers and the public. The study also stresses theimmediate need to learn and include the remote sensing ofterrestrial water in the water management in Morocco.Keywords: vulnerability, water, Water remote sensing,agriculture, climate change, Morocco, adaptation.Kappas, MartinSimulation of water balance components in awatershed located in central drainage basin of IranRafiei Emam, Ammar 1 ; Kappas, Martin 11. Cartography, GIS and Remote Sensing, University ofGoettingen, Goettingen, GermanyKnowledge of water balance components is useful forwater resources analysis and the management of watersheds,the rehabilitation of an area, the prevention of landdegradation, the estimation of water availability forirrigation or the calculation of sustainable groundwaterwithdrawal. In this study, simulation of the hydrologicalsituation in the catchment has been performed by SWAT(Soil and Water Assessment Tool). The model calibration bySWAT is time consuming, so in this study SUFI-2(Sequential Uncertainly Fitting Ver. 2) was used to evaluateSWAT by performing calibration and uncertainly analysisbased on river discharge. SUFI-2 is a semi-automated inversemodeling procedure for combined calibration-uncertainlyanalysis. For this aim, meteorological data measured duringa long period time (1976-2010) were collected. A landuse/land cover map was created by supervised classificationmethod from satellite images dated in 2009. A soil map wasgenerated using soil profile information for each land type.All data were integrated in a geographical informationsystem (GIS). In order to study the water balancecomponents, the watershed was divided into 87 subcatchmentaccording to digital elevation, flow direction andflow accumulation in the entire watershed. Then in eachsub-catchment water components such as surface runoff,percolation, evapotranspiration and soil moisture wasestimated. The final results show the spatial and temporaldistribution of water balance components in the watershed.With this information a future management of thewatershed in the direction of an optimized water utilizationis possible. For the future, of course it is possible to estimatewater balance components with remotely sensed data andcompare it with our hydrological model.Kappas, MartinSimulation of water balance components in awatershed located in central drainage basin of Iranby A. Rafiei Emam and Martin W. KappasKappas, Martin 1 ; Rafiei, Ammar 11. Geography, University of Goettingen, Goettingen,GermanyAbstract Knowledge of water balance components isuseful for water resources analysis and management ofwatershed, rehabilitation of area, prevention of landdegradation, estimation of water availability for irrigation,calculation amount of groundwater withdrawal and etc. Inthis study for simulation of hydrological model we used Soiland Water Assessment Tools (SWAT) and then SUFI-2 wasused to calibrate and validate a model based on riverdischarge. For this aim measured of meteorological data in80

long period time (1976-2010) was collected. Land use/landcover map was created with a supervised classificationmethod with satellite images dated in 2009. Soil map weregenerated using soil profile information in each land types.Slope was mapping in geographical information system. Inorder to study the water balance components, watershed wasdivided to 87 sub catchment according to digital elevationmodel and flow direction and flow accumulation. Then ineach sub catchment water components such as surfacerunoff, percolation, evapotranspiration and soil moisturewas estimated. The final results show the spatial andtemporal distribution of water balance components inwatershed. With this information we can planning andmanagement of watershed in order to optimized utilizationof water. For the future, of course it is possible to estimatewater balance components with remotely sensed data andcompare it with hydrological model. Keywords: Hydrologicalmodel, SWAT, SUFI-2http://www.uni-goettingen.de/de/sh/36647.htmlKarimi, PooladRemote sensing application to support wateraccounting in the transboundary Indus BasinKarimi, Poolad 1, 2 ; Bastiaanssen, Wim 2, 3 ; Cheema,Muhammad J. 2 ; Molden, David 41. International Water Management Institute, Battaramulla,Sri Lanka2. Water management, TU Delft, Delft, Netherlands3. WaterWatch, Wageningen, Netherlands4. International Centre for Integrated MountainDevelopment, Kathmandu, NepalOver the last 50 years the world has changed from asituation where water appeared abundant, to a situation ofwater scarcity. Changes in population, changing diets,economic growth, are behind the increase in water use.Hence, the water sector calls for a better management so thatthe growing demands can be met in future. Paramount tobetter management is an appropriate understanding of theactual river basin conditions, based on factual datacombined with a way to recognize opportunities forimplementing and improving integrated water resourcesmanagement. Water accounting provides such an insightinto water flows in river basins. However, availability of dataon water flows, and consumptions is a major constraint forreliable water accounting in many river basins around theworld. In this paper we show how remote sensing can beemployed to fill the data gaps and to provide acomprehensive picture on water balance and watershedprocesses in a basin. The study focuses on the Indus which isone of the most densely-populated and hydrologicallycomplex river basins of the world. Information onevaporation (E) and transpiration (T), estimated usingETLook remote sensing model, together with calibratedTRMM rainfall and land use land cover map (LULC) wereused to prepare water accounts for 2007. For the purpose theWater accounting plus framework (WA+) was introduced.The WA+ is a tool that provides explicit information onwater flows and consumptions in a basin with a strong linkto land use management and has been essentially designedto allow use of satellite measurement. The results of theaccounting exercise show that the gross inflow to the basinwas 442 billion cubic meter (bcm). The net inflow, grossinflow plus storage changes, was 523 bcm of which 96%, 502bcm, is depleted. Landscape ET, ET that occurs directly fromrainfall, was 343 bcm. Incremental ET, or net withdrawals,was 158 bcm. Incremental ET is the abstracted water that isconsumed through ET and does not return to the systems.Surface and groundwater storages declined by 6.4 and 74bcm respectively in the accounting period. This implies howthe basin is dependent to the groundwater and how the fastdecline of groundwater can lead to food security issues if thesituation remains unchanged. The annual outflow of 21.3bcm is more than the required environmental flow of 12.3bcm. However, seasonal water accounts show that majorityof the outflow, 17.1 bcm happens during Kharif (wetsummer) and in Rabi (winter) the outflow is 2 bcm less thanrequired flow. The difference between outflows and theenvironmental flow, Utilizable flow, is 8 bcm which can beutilized by increasing surface storage. This will not onlylessen the pressure on groundwater resources but also willhelp to maintain the required environmental flowthroughout the year. However with future growth indemand, and questions about supply given climate changeimpact on glacial and snowmelt and resulting patterns ofwater availability, the Indus will continue to face waterscarcity problems. These results provide an importantbaseline from which better strategies for the future can bedeveloped.Kelly, Jacque L.Practical applications of infrared imagery forinvestigating submarine groundwater dischargeand other thermal anomalies in coastal zonesKelly, Jacque L. 1 ; Glenn, Craig R. 1 ; Lucey, Paul G. 21. Geology and Geophysics, University of Hawaii at Manoa,Honolulu, HI, USA2. Hawaii Institute of Geophysics and Planetology,University of Hawaii at Manoa, Honolulu, HI, USAAirborne thermal infrared remote sensing is a highlyeffective tool for mapping locations, surface distributions,and mixing characteristics of terrestrial groundwaterdischarge to the coastal ocean where even subtle temperaturedifferences exist between the receiving waters and thedischarging water. The spatially and temporally variablenature of submarine groundwater discharge (SGD) and itsmixing with seawater necessitates rapid, high-resolutiondata acquisition techniques, of which airborne thermalinfrared remote sensing is uniquely qualified. We have usedthermal infrared images acquired at 762 m – 2743 m altitudeto generate 0.5 m – 3.2 m resolution sea-surface temperaturemaps with

sourced groundwater and stream flow discharges notresolvable at the 60 m resolution afforded by Landsat 7infrared images. These much higher resolutions alsominimize contamination effects imparted by land thermalsignatures in pixels immediately adjacent to coasts. Basicinformation about prevailing coastal currents andgroundwater mixing with seawater are clearly evident in theimages. By establishing several transects across eachgroundwater plume, the highly precise temperatures in theimagery allow for unique quantification of each dischargeplume’s boundary. The surface area of each discharge canthen be easily calculated and subsequently up-scaled, orcombined with ground-based flow rates to determine timespatialvariations of volumetric flow. This mappingtechnique is the preferred method for rapid assessment andprecise identification of natural and anthropogenicallyintroduced coastal groundwater and stream flow, at scalesboth large and small. It is highly desirable for many aspectsof ecosystems, pollution and coastal-zone planning andmanagement, as well as a prerequisite for the best use ofsubsequent and time-consuming in-situ field study efforts.Sea surface temperature map of Aina Haina, Oahu, Hawaii inperspective view. Darker water hues represent colder temperaturegroundwater and lighter hues approach seawater temperatures. Theprevailing current direction can be seen as groundwater mixes withseawater.Kerr, Yann H.SMOS and Hydrology: First Lessons LearntINVITEDKerr, Yann H. 1 ; Pauwels, Valentijn 5 ; Wood, Eric 4 ; Walker,Jeff 3 ; Al Bitar, Ahmad 1 ; Merlin, Olivier 1 ; Rudiger, Chris 3 ;Wigneron, Jean Pierre 21. Cesbio, Toulouse, France2. EPHYSE, INRA, Bordeaux, France3. Monash University, Melbourne, VIC, Australia4. Princeton University, Princeton, NJ, USA5. Ghent University, Ghent, BelgiumSMOS, a L Band radiometer using aperture synthesis toachieve a good spatial resolution, was successfully launchedon November 2, 2009. It was developed and made under theleadership of the European Space Agency (ESA) as an EarthExplorer Opportunity mission. It is a joint program with theCentre National d’Etudes Spatiales (CNES) in France andthe Centro para el Desarrollo Teccnologico Industrial(CDTI) in Spain. SMOS carries a single payload, an L band2D interferometric,radiometer in the 1400-1427 MHz hprotected band. This wavelength penetrates well through thevegetation and the atmosphere is almost transparentenabling to infer both soil moisture and vegetation watercontent. SMOS achieves an unprecedented spatial resolutionof 50 km at L-band maximum (43 km on average) withmulti angular-dual polarized (or fully polarized) brightnesstemperatures over the globe and with a revisit time smallerthan 3 days. SMOS has been now acquiring data for twoyears. The data quality exceeds what was expected, showingvery good sensitivity and stability. The data is however verymuch impaired by man made emission in the protectedband, leading to degraded measurements in several areasincluding parts of Europe and of China. However, manydifferent international teams are now addressing cal valactivities in various parts of the world, with notably largefield campaigns either on the long time scale or over specifictargets to address the specific issues. In parallel differentteams are now starting addressing data use in various fieldsincluding hydrology. We have now acquired data over anumber of significant “extreme events” such as droughtsand floods giving useful information of potentialapplications. We are now working on the coupling withother models and or disaggregation to address soil moisturedistribution over watersheds. We are also concentratingefforts on water budget and regional impacts. From all thosestudies, it is now possible to express the “lessons learned”and derive a possible way forward. This paper thus gives anoverview of the science goals of the SMOS mission, adescription of its main elements, and a taste of the firstresults including performances at brightness temperature aswell as at geophysical parameters level and how they arebeing put in good use for hydrological applications.Kim, DaeunSpatio-Temporal Patterns of Hydro-Meteorologicalvariables produced from SVAT model incorporatedwith KLDAS in East AsiaKim, Daeun 1 ; Choi, Minha 11. civil and enviromental eng., hanyang university, Seoul,Republic of KoreaFor adaptation of radical environmental changes,various researches using Land Surface Model (LSM) havebeen made to identify interaction between surface andatmosphere as a parameterizing physical process of energyand substances exchange. Especially, the recent naturaldisasters such as floods and typhoons are caused by climatechange, thus, we can see the necessity of these studies forresponding to the alterations. In this study, hydrometeorologicalvariables were calculated using CommonLand Model (CLM). The models’ forcing data as initial datawas provided by Korea Land Data Assimilation System(KLDAS). The KLDAS is data assimilation methods based onLand Data Assimilation System (LDAS). The KLDAS system82

has more improved resolution ( ) to compare with LDASresolution ( ) and produces optimized observation data,satellite data, and model’s results. This dataset is anattractive alternative to estimate for constrained land fluxesand variables due to strong heterogeneous land. Throughthese processes, the CLM calculate hydro-meteorologicalvariables such as net radiation, latent, sensible, and groundheat fluxes. For this study, the comparison of observationdata and models’ results should be verified for model’sapplicability in the East Asia.Kim, EdwardMultilayer Snow Microwave ModelIntercomparisons and Scale Implications for FutureSnow MissionsKim, Edward 1 ; DURAND, Michael 2 ; MARGULIS, Steven 3 ;MOLOTCH, Noah 4 ; Lemmetyinen, Juha 5 ; Picard, Ghislain 61. NASA GSFC, Greenbelt, MD, USA2. Ohio State University, Columbus, OH, USA3. UCLA, Los Angeles, CA, USA4. Univ. of Colorado, Boulder, CO, USA5. Finnish Meteorological Institute, Helsinki, Finland6. LGGE, Grenoble, FranceAbstract: Microwaves are well-suited to the task of snowremote sensing with their high sensitivity to snow extent andsnow water equivalent, and particularly since, unlike visiblesensors, microwave sensors do not require solar illuminationand can see through cloud cover. But the same highsensitivity also creates more stringent requirements onknowledge of snow pack characteristics or other constraints,as the signal is a path-integrated quantity and so it ispossible for multiple conditions to produce the samesignature. e sensitivity has been investigated by numerousresearchers, and the corresponding requirements onknowledge of snow characteristics is the topic of relatedabstracts. Snow is also a complex structure from a microwaveradiative transfer point of view. The natural episodic arrivalof snow, snow grain metamorphism, and melt/refreeze cyclescan create layering and other microstructural variations thatare easily seen by microwave sensors. Understanding thesesignatures usually requires a radiative transfer models withmultiple layers and within each layer a means of representingthe size and/or distribution of snow grains or correlationlength. Over the past few years, several groups have collectedin situ snow and microwave brightness temperaturemeasurements to aid in the improvement of microwaveradiative transfer models of snow. In this paper, fieldmeasurements from the US, Canada, and Finland will beused to drive a number of multilayer snow microwaveradiative transfer models, including MEMLS, multilayerHUT, and others. The outputs will be compared to exploreeach model’s response to the different snow conditions.Most importantly, we are interested in ascertaining themodel complexity required to achieve a given accuracy (e..g, 5K), and the corresponding requirements on accuracy of theinput parameters. For retrievals based on model inversion ordata assimilation approaches, this is a key question. Theanswers directly impact the sensitivity and accuracyrequirements of sensors on future snow missions. Intimatelyconnected to this is the spatial resolution of theobservations and retrievals. For the same snow conditionsand same radiative transfer model or retrieval scheme, therequirements on sensors and knowledge of snow conditionscan vary significantly as a function of spatial resolution.This is perhaps more so for snow than for other hydrologicalretrievals, such as for soil moisture. We will present theresults of scaling tests, using the above models and snowmeasurements to help understand the implications forfuture snow missions.Kirchner, Peter B.Measuring under-canopy snow accumulation withairborne scanning LiDAR altimetry and in-situinstrumental measurements, southern SierraNevada, CaliforniaKirchner, Peter B. 1 ; Bales, Roger C. 1 ; Molotch, Noah P. 21. Sierra Nevada Research Institute, University of California,Merced, Merced, CA, USA2. Institute of Arctic and Alpine Research, University ofColorado at Boulder, Boulder, CO, USASnow distribution Estimates in forested environmentsdemonstrate a high level of uncertainty due to the inabilityof remote sensing platforms to observe reflectance underdense vegetation and the limited availability of spatial andtemporal in-situ measurements. Thus measuring snowunder forest canopies remains an unresolved problem forremote sensing of snow cover in forested landscapes. In thisstudy we carefully analyzed filtered paired snow on and snowoff scanning LiDAR altimetry collected in the 2010 wateryear, from the Kaweah River watershed, Sierra Nevada,California, to establish snow depths over a 52.5 squarekilometer area covering a wide range of slopes aspects,elevations and forest types including Giant Sequoia groves,mixed conifer and sub alpine forests. Using 1 m 2 meanelevation grids produced from filtered first and last returnswe established a distinction between snow in open areas andthose under the canopies by selecting areas where meanground and canopy returns overlapped defining the canopyedges of mature trees and the under canopy of small treesand shrubs. In addition we analyzed in-situ time series dataof snow depth density precipitation, temperature, andupstream bright band radar data to establish a deeperprocess understanding of the dynamics between snowaccumulation in the open and under forest canopies. Resultsindicate a decrease in under canopy depth at all locations,but lower elevations demonstrate a greater decrease and a10% higher coefficient of variation in snow depth and an 8%increase in density. Upstream bright band radar and metdata from hydrologic observatory sites indicate the locationsof increased variability in depth and higher density receiveda greater percentage of precipitation as rain. Our findingsprovide a metric for estimating under canopy snowaccumulation where it cannot be directly observed directlywith remote sensing and suggest the elevation of the rain83

snow transition of individual storms has a strong influenceon the difference between snowdepth in the open and underforest canopy.Kosuth, PascalA method for river discharge estimate from satelliteobservation alone, without any in situmeasurementKosuth, Pascal 1 ; Négrel, Jean 1 ; Strauss, Olivier 2 ; Baume, Jean-Pierre 3 ; Faure, Jean-Baptiste 4 ; Litrico, Xavier 3, 5 ; Malaterre,Pierre-Olivier 31. TETIS, IRSTEA, Montpellier, France2. LIRMM, Université Montpellier 2, Montpellier, France3. GEAU, IRSTEA, Montpellier, France4. Hydrologie-Hydraulique, IRSTEA, Lyon, France5. LyRE, R&D Center, Lyonnaise des Eaux, Bordeaux,FranceIs it possible to estimate river discharge from satellitemeasurement of river surface variables (width L, water levelZ, surface slope Is, surface velocity Vs) without any in situmeasurement ? Current or planned satellite observationtechniques in the hydrology-hydraulic domain are limited tothe measurement of surface variables such as river width L(optical and SAR imagery), water level Z (radar and Lidaraltimetry), river surface longitudinal slope Is (cross-trackinterferometry) and surface velocity Vs (along-trackinterferometry). On the opposite, river bottom parameterssuch as river bottom height (Zb), river bottom longitudinalslope (Ib), Manning coefficient (n), vertical velocity profilecoefficient ( the ratio between mean water velocity andsurface velocity), that are key data for discharge estimate andmodeling, cannot be measured by satellite. They require insitu measurement (Zb, Ib, ) and model calibration (n). Wepresent here a method to derive river bottom parametersfrom satellite measured river surface variables in the absenceof any in situ measurement. This will then allow us toestimate river discharge for any set of surface variables. Themethod relies on a set of hydraulic hypothesis (for instancerectangular section, constant Manning coefficient n andconstant velocity profile coefficient ). It consists of solvingan equality constraint between two formulations linking theriver discharge Q to the surface variables and the unknownparameters (Q1 and Q2 obtained from the massconservation equation and the energy conservationequation): Q1=L..Vs.h Q2=L.h 5/3 .Is 1/2 .[n 2 +g -1 .h 1/3 .(Is-Ib)]where h=Z-Zb Given a river section, estimating the riverbottom parameters (, Zb, Ib, K) is achieved by using a set ofsurface variables (L, Z, Is, Vs) i=1 to N, measured on this sectionat various times ti throughout the hydrological cycle, and bydetermining the set of river bottom parameters thatminimizes a deviation criteria between (Q1)i and (Q2)i. Thisminimization is achieved by iterative or direct methods,depending on the type of criteria and on additionalhypothesis (ex. a uniform regime hypothesis leads to ananalytical solution). Several simulations have shown theefficiency of theses methods on exact simulated data set (i.e.for which (Q1)i=(Q2)i). We have assessed the robustness ofthese methods to measurement noise on river surfacevariables. We proposed several modifications to increase thisrobustness and the ability to provide acceptable riverdischarge estimates (error

in the flow over the floodplain arising from the scouring atthe O’Bryan Ridge in the Floodway. The presentation willshow the initial results from the study of these data andhighlight the value of using high resolution remote-sensingdata for the study of flood impacts.kumar A, JayaRole of El Niño in Modulating the Period ofPrecipitation Variability of Asian Summer MonsoonUsing Satellite Observationskumar A, Jaya 11. EOAS-Meteorology, Florida State University, Tallahassee,FL, USAActive-Break (AB) Cycle of the Asian Summer Monsoon(ASM) is one of the crucial factors in deciding the amount ofprecipitation received during ASM. During the AB Cycle, theatmosphere and the underlying ocean closely interact in thetime scale of about 40 days. Net heat flux at the oceansurface which is controlled by convective clouds (radiativeheating) and low-level winds (evaporative cooling) play animportant role in this interaction. This study addresseslength of monsoon rainfall variability between dry and wetperiods (AB cycle) especially in El Niño developing phaseusing remotely sensed wind data from QuikSCATscatterometer, Microwave SST image from Tropical RainfallMeasurement Microwave Image (TMI) and available Argodata of MLD. These data set aids in defining the moisturesupply to the monsoon environment especially from theoceanic areas. North Bay of Bengal and the Oceans to its eastand west have large amplitude Sea Surface Temperature(SST)variation in the AB cycle in response to the net heat fluxvariations as the Mixed layer Depth (MLD) there is shallow(typically 20 meters) during the months June to September,forced by the cyclonic wind stress curl north of the seasonalmonsoon westerlies. In an El Niño situation, the low levelmonsoon winds extend eastward beyond the date linecreating an area of shallow MLD between longitudes 120°Eand 160°W. This area then warms rapidly and causes thecycle of convection to shift there from North Indian Oceanbefore moving to the Equatorial Indian Ocean. This causes alengthening of the AB cycle from one month in a La Niña to2 months in an El Niño. Hence, propose that the long ABcycle in El Niño years (typically of 50-60 day period) is themain cause of the El Niño produced droughts in the Indianmonsoon. Key words: El Niño, Mixed layer Depth, Active-Break CycleKuo, Kwo-SenPrecipitation Characteristics of Tornado-ProducingMesoscale Convective Systems in the ContinentalUnited StatesKuo, Kwo-Sen 1 ; Hong, Yang 2 ; Clune, Thomas L. 31. GEST/Caelum, NASA Goddard SFC, Greenbelt, MD,USA2. School of Meteorology, University of Oklahoma,Norman, OK, USA3. Software Systems Support Office, NASA Goddard SpaceFlight, Greenbelt, MD, USAIn this study we report precipitation statistics, relevantto the terrestrial water cycle, obtained for tornado-producingmesoscale convective systems (MCSs) in the continentalUnited States (CONUS) . In a technology-demonstrationeffort, we have synergistically combined several datasets andbuilt an innovative system to automatically track tornadoproducingMCSs in CONUS and, at the same time, collectand record physical and morphological parameters for eachMCS. We perform the tracking in two datasets with highspatial (two horizontal dimensions) and temporalresolutions: the 1-km 5-minute Q2 surface precipitationdataset and the 4-km 30-minute GOES 10.8-µm brightnesstemperature dataset. First, we use a threshold to delineatepotential MCS regions in a temporal snapshot in each of thetwo datasets. We then apply segmentation and subsequentlyneighbor-enclosed area tracking (NEAT) method, bothforward and backward in time, to identify distinct tornadoproducingMCSs from their inception to eventualdissipation. Next, we use historical National Weather Service(NWS) tornado watches to locate the general area (countyand/or state) of a tornado and its associated MCS. Thisinformation is further complemented with the coarseresolution track data in the database of the Tornado HistoryProject (http://www.tornadohistoryproject.com/). Followingour automated tracking, an episode of a tornado-producingMCS becomes a three-dimensional entity, two in space andone in time. We can thus automatically obtain, from the Q2surface precipitation dataset, various precipitation andmorphological characteristics for each episode, such as thenumber of tornados produced by a system, the evolution ofits area coverage, its maximum rain rate, the time-integratedprecipitation volume of a system’s lifetime, etc. Finally,statistics are gathered for all the tornado-producing MCSsfor the years 2008(partial)-2011. These are correlated andcompared to those, i.e. per-system characteristics as well asannual and all-system statistics, obtained form GOES 10.8-µm brightness temperature datasets.85

Kuss, Amber Jean M.Tools for improving groundwater storage estimatesin the Sacramento River Basin: a comparison ofremote sensing techniques, a hydrological model,and in-situ groundwater elevationsKuss, Amber Jean M. 1, 2 ; Brant, William 3 ; Randall, Joshua 5 ;Floyd, Bridget 4 ; Bourai, Abdelwahab 6 ; Newcomer, MichelleE. 1, 2 ; Schmidt, Cynthia 1, 7 ; Skiles, Joseph 11. Earth Science, NASA Ames Research Center, MoffettField, CA, USA2. Geosciences, San Francisco State University, SanFrancisco, CA, USA3. California State University, Monterey Bay, Monterey, CA,USA4. University of California,Berkeley, Berkeley, CA, USA5. Arizona State University, Pheonix, AZ, USA6. Cupertino High School, Cupertino, CA, USA7. Bay Area Enviornmental Institute, Mountian View, CA,USATo effectively manage groundwater resources inCalifornia’s Central Valley managers require good estimatesof groundwater storage, and the ability to accurately assesschanges in groundwater storage over time. Here we usedthree different methods to assess groundwater storagechanges for California’s Sacramento River Basin betweenOctober 2002 and September 2009. The goals of this studywere to 1) assess the applicability of GRACE for small-scaleaquifer management; and 2) to validate existing hydrologicmodels and methods for estimating groundwater storage.The Gravity Recovery and Climate Experiment (GRACE) wasused in conjunction with other remotely sensed data sets tomeasure groundwater changes for the Sacramento RiverBasin. These observations were then compared togroundwater storage changes predicted by California’sDepartment of Water Resources (DWR) hydrologic model:Central Valley Groundwater-Surface Water Simulationmodel (C2VSIM) and to measured groundwater levels usedby the DWR’s Geographic Information Systems Change instorage tool (GIS CST). It was found that GRACE-derivedestimates of changes in groundwater storage provedcomparable to that of C2VSIM for the entire Central Valleyaquifer. However, for the Sacramento River Basin, GRACE,C2VSIM, and the GIS CST produced significantly differentresults (-5.10 ± 1.62 km3, -2.55 ± 0.38 km3, and 0.67± 0.1km3 for GRACE, C2VSIM, and the GIS CST, respectively).Differences between these estimates may be resolved withimprovements to individual components of these methods—specifically soil moisture estimates for GRACE and thestorage coefficient estimates utilized in the GIS CST. Inconclusion, while the three methods produced differentresults for the Sacramento River Basin, it is clear that withsome improvements these tools have the potential to aidwater resource managers in understanding changes ingroundwater in California’s Central Valley.86Kustas, William P.Utility of Thermal Remote Sensing for DeterminingEvapotranspirationKustas, William P. 1 ; Anderson, Martha 1 ; Hain, Christopher 2 ;Gao, Feng 1 ; Mecikalski, John 31. US Dept Agriculture, ARS Hydrology & Remote Sensing,Beltsville, MD, USA2. 2I.M. Systems Group, NOAA/NESDIS, Camp Springs,MD, USA3. Dept. Atmospheric Sciences, University of Alabama-Huntsville, Huntsville, AL, USALand surface temperature (LST) from thermal remotesensing is a surface boundary condition that is stronglylinked to the partitioning of the available energy betweenlatent (evapotranspiration) and sensible heat flux.Numerous modeling approaches have been developedranging in level of complexity from semi-empirical tonumerically-based soil-vegetation-atmosphere schemes.Many of the approaches require an accurate LST because theheat fluxes are related to the surface-air temperaturedifferences. There is also difficulty estimating appropriateexchange coefficients for heterogeneous landscapes having amixture of soil and vegetation temperatures influencing theLST observation and associated aerodynamic temperature.For regional applications this also means requiring anaccurate air temperature distribution over the area ofinterest. These requirements have rendered many of themodeling approaches unusable for routine applications overcomplex land surfaces. However a two-source energy balance(TSEB) modeling scheme using time differencing in LSTobservations coupled to an atmospheric boundary layergrowth model has been developed to adequately address themajor impediments to the application of LST in large scaleevapotranspiration determination. The modeling system,Atmospheric Land EXchange Inverse (ALEXI), usinggeostationary LST observations and the disaggregationmethodology (DisALEXI) together with data fusiontechniques will be described. This modeling system iscurrently providing regional and continental scaleevapotranspiration estimates in the U.S. and plans are todevelop a global product.L’Ecuyer, Tristan S.The Role of Spaceborne Cloud Radars in TerrestrialHydrologyL’Ecuyer, Tristan S. 1 ; Wood, Norman 2 ; Haynes, John 2 ;Lebsock, Matthew 31. Dept Atmospheric and Oceanic Sciences, University ofWisconsin-Madison, Madison, WI, USA2. Department of Atmospheric Science, Colorado StateUniversity, Fort Collins, CO, USA3. Jet Propulsion Laboratory, Pasadena, CA, USACentral to the problem of closing regional water cycles isan accurate assessment of the spatial and temporaldistribution of precipitation. At latitudes poleward of 30degrees, light rainfall and snowfall make up a significant

fraction of the fresh water resources for agricultural use andhuman consumption yet despite recent advances in globalprecipitation measurement, many contemporary satellitesensors inherently lack the required sensitivity to accuratelyquantify these light precipitation regimes. Millimeterwavelengthcloud radars, such as the Cloud Profiling Radar(CPR) aboard CloudSat, may provide a means of filling thisgap in current precipitation observing systems. Cloud radarsexhibit sensitivity to the full spectrum of atmosphericcondensed water phenomena providing a missing linkbetween optical sensors that are primarily sensitive to clouddroplets and centimeter-wavelength microwave sensors thatare best suited to measuring more intense rainfall. Thispresentation will review several key insights into the globaldistribution of light precipitation that have emerged fromthree new CloudSat precipitation algorithms. The physicalconsiderations for retrieving rain and snowfall frommillimeter-wavelength cloud radar will be discussed and newmulti-year climatologies of continental light rainfall andsnowfall will be presented. The results underscore the valueof using CloudSat and complementary A-Train observationsto quantify the contribution of light rainfall to theterrestrial water cycle and to better understand the factorsthat may modify its distribution in a changing climate.Lakshmi, VenkataramanClimate Studies of intertidal using MODIS surfacetemperaturesLakshmi, Venkataraman 1 ; Price, Jessica 11. Dept Earth and Ocean Sciences, Univ South Carolina,Columbia, SC, USAStudies have shown that the intertidal zones areenvironments are extremely vulnerable to changes intemperature due to periods of alternating aerial and marinesubmergence. MODIS Aqua and Terra satellites produceboth land surface temperatures (LST) and sea surfacetemperatures (SST) using calibrated algorithms. In thispaper, LST and Intertidal Surface Temperatures (IST) wereretrieved during clear-sky (non-cloudy) conditions at a 1square kilometer resolution (overpass time at 10:30 am and1:30 pm) whereas the SST are also retrieved during clear-skyconditions at approximately 4 square kilometer resolution(overpass time approximately at 10:30 am and 1:30 pm). Wehave studied 10 years of MODIS surface temperature datafor the intertidal as well as the sea surface temperature attwo locations on the rocky western coast of United States.This paper will attempt to study the trends in the IST, LSTand SST for these locations and their impact on theCalifornia mussel populations.Lakshmi, VenkataramanDownscaling of passive microwave soil moistureusing vegetation and surface temperatureLakshmi, Venkataraman 1 ; Fang, Bin 11. Dept Earth and Ocean Sciences, Univ South Carolina,Columbia, SC, USASoil moisture derived using passive microwave remotesensing is a reliable hydrological product that is used invarious aspects of hydrology, land-atmosphere interactions,meteorology and agricultural applications. However, thespatial scale of the radiometer derived soil moisture isinadequate for these and many other scientific applications.The following proposal will use vegetation and surfacetemperature data at a higher spatial resolution in order todisaggregate the soil moisture retrieved using a radiometer.This disaggregated soil moisture product will be at spatialresolutions of 1-10 km and help in applications as comparedto the 10s of kilometers (30-60km) as soil moisture derivedfrom radiometer data.In our proposal, we will use the theoryof thermal inertia and satellite sensor derived vegetation andsurface temperature data to downscale passive microwavesoil moisture retrievals over the contiguous United States.We will use existing MODIS vegetation and surfacetemperature data to downscale AMSR-E soil moistureretrievals.Landerer, Felix W.Assessing water storage, winter precipitation anddischarge of Arctic drainage basins using GRACEand Global Precipitation AnalysesLanderer, Felix W. 1 ; Swenson, Sean C. 21. Jet Propulsion Laboratory / Caltech, Pasadena, CA, USA2. NCAR - Climate and Global Dynamics Division, Boulder,CO, USAThe Gravity Recovery and Climate Experiment missionnow provides nearly 9 years of continuous, globalobservations of the total, aggregate terrestrial water storagevariations down to scales of about 300 km. While GRACEmeasures terrestrial water storage without respect to from(ice, snow or liquid) or position relative to the surface(surface, soil or ground water), it is uniquely suitable toestimate drainage-basin-wide terrestrial water balances, and -in combination with complementary information fromobservations or model data – can be used to identify relevanthydrological processes as well as potential biases in thebudget components. In one application of GRACEobservations, we have performed such an analysis for thePan-Arctic drainage basins by combining GRACE data withatmospheric moisture convergence estimates from reanalysisand observations of discharge from river gauges.The results show that river discharge can be calculated togood accuracy from the combination of GRACE andatmospheric moisture convergence, thus providing dischargeestimates from otherwise unobserved regions. The observedincreases from 2003 to 2007 of both gauged discharge and87

terrestrial water storage are consistent with increased netprecipitation over the Eurasian Pan-Arctic region. At finerspatial scales, in particular in the central Lena basin,terrestrial water storage change detected by GRACE showsincreases over regions of discontinuous permafrost,potentially indicating changes in the active layer thickness inthose areas. We also use GRACE total water storageanomalies to evaluate biases in the net precipitation fromthe re-analysis data, as well as the cold-season precipitationestimates from two global, merged satellite–gaugeprecipitation analyses—Global Precipitation ClimatologyProject (GPCP) and Climate Prediction Center MergedAnalysis of Precipitation (CMAP). In general, spatial patternsand interannual variability are highly correlated between thedatasets, although significant differences are also observed.Differences vary by region but typically increase at higherlatitudes. Furthermore, results indicate that the gaugeundercatch correction used by GPCP may be overestimated.These comparisons may be useful for assessing precipitationestimates over large regions, where in-situ gauge networksmay be sparse.Larson, Kristine M.GPS Snow SensingLarson, Kristine M. 1 ; Nievinski, Felipe 1 ; Gutmann, Ethan 2 ;Small, Eric 11. Aerospace Engineering Sciences, University of Colorado,Boulder, CO, USA2. NCAR, Boulder, CO, USAThe Global Positioning System continuously transmitsL-band signals to support real-time navigation users. Thesesame signals are being tracked by networks of high-precisionGPS instruments that were installed by geophysicists andgeodesists to measure plate motions. Many states andcounties also operate GPS networks to supporttransportation engineers and land surveyors. Over 2500 ofthese systems have been deployed in the United States. Theyoperate continuously, and data are made publicly availablewithin 24 hours. Geodesists model the direct signal betweeneach GPS satellite and the ground antenna to calculate theposition of each GPS site.Some of the signal reflects fromthe ground and arrives at the antenna late. The interferencebetween the direct and reflected GPS signal is what we use toinfer snow depth. For most sites the footprint of the methodis 30 meters in radius with a snow depth precision ofapproximately 3 cm. These data complement small-scale insitu snow depth sensors and satellite methods. We currentlyoperate 5 calibration sites in Utah, Idaho, and Colorado.Comparisons between GPS snow depth retrievals and otherin situ sensors will be discussed. We will also demonstratethe GPS snow sensing method at sites from the NSFEarthScope Plate Boundary Observatory (PBO). Thisnetwork consists of 1100 receivers in the western UnitedStates and Alaska.http://xenon.colorado.edu/reflections/GPS_reflections/Intro.htmlLebsock, Matthew D.The Complementary Role of Observations of LightRainfall from CloudSatLebsock, Matthew D. 1 ; Stephens, Graeme 1 ; L’Ecuyer, Tristan 21. Jet Propulsion Lab, Pasadena, CA, USA2. University of Wisconsin, Madison, WI, USAThe CloudSat rainfall algorithms are presented as auseful complementary data source to the more establishedPrecipitation Radar (PR) and passive microwaveprecipitation sensors. The specific strengths of the CloudSatinstrument including it’s excellent sensitivity and resolutionhighlight its ability to fill in the light end of Earth’s rainfallspectrum that escapes detection by other sensors. Todemonstrate the complementary nature of the CloudSatobservations, a comparison of warm rainfall from CloudSatwith AMSR-E shows the dramatic improvement of theGoddard Profiling algorithm (GPROF)-2010 algorithm overGPROF-2004 at quantifying warm rain. Despite thesignificant improvement of the passive microwave algorithmsubstantial regional biases in GPROF-2010 that are relatedto variations in Sea Surface Temperature (SST) and ColumnWater Vapor (CWV) persist. These regional biases are relatedto the fundamental detection capabilities of the PR, which isused to create the rainfall database employed by the passivemicrowave algorithm. A series of sensitivity calculationsindicate that the Dual-frequency Precipitation Radar (DPR)that will fly as part of the Global Precipitation Mission(GPM) will significantly mitigate these detection issues.Colocation of the DPR with the GPM Microwave Imager(GMI) will have the added benefit of improving the GPROFrainfall database and thus the climate data record providedby passive microwave instruments.Lee, HyongkiCharacterization of Terrestrial Water Dynamics inthe Congo Basin Using GRACE and Satellite RadarAltimetryLee, Hyongki 1 ; Beighley, R. Edward 2 ; Alsdorf, Douglas 3 ; Jung,Hahn Chul 4 ; Shum, C. k. 3 ; Duan, Jianbin 3 ; Guo, Junyi 3 ;Yamazaki, Dai 5 ; Andreadis, Konstantinos 61. University of Houston, Houston, TX, USA2. FM Global, Norwood, MA, USA3. Ohio State University, Columbus, OH, USA4. NASA Goddard Space Flight Center, Greenbelt, MD, USA5. University of Tokyo, Tokyo, Japan6. Jet Propulsion Laboratory, Pasadena, CA, USAThe Congo Basin is the world’s third largest in size (~3.7million km^2), and second only to the Amazon River indischarge (~40,200 cms annual average). However, thehydrological dynamics of seasonally flooded wetlands andfloodplains remains poorly quantified. Here, we separate theCongo wetland into four 3° 3° regions, and use remotesensing measurements (i.e., GRACE, satellite radar altimeter,GPCP, JERS-1, SRTM, and MODIS) to estimate the amountsof water filling and draining from the Congo wetland, and88

to determine the source of the water. We find that theamount of water annually filling and draining the Congowetlands is 111 km^3, which is about one-third the size ofthe water volumes found on the mainstem Amazonfloodplain. Based on amplitude comparisons among thewater volume changes and timing comparisons among theirfluxes, we conclude that the local upland runoff is the mainsource of the Congo wetland water, not the fluvial process ofriver-floodplain water exchange as in the Amazon. Ourhydraulic analysis using altimeter measurements alsosupports our conclusion by demonstrating that watersurface elevations in the wetlands are consistently higherthan the adjacent river water levels. Our research alsohighlights differences in the hydrology and hydrodynamicsbetween the Congo wetland and the mainstem AmazonfloodplainLemoine, Frank G.Monitoring Mass Change Using Global HighResolution GRACE Mascon SolutionsLemoine, Frank G. 1 ; Sabaka, Terence J. 1 ; Boy, Jean-Paul 2 ;Luthcke, Scott B. 1 ; Carabajal, Claudia C. 3, 1 ; Rowlands, DavidD. 11. Planetary Geodynamics Lab., NASA GSFC, Greenbelt,MD, USA2. EOST/IPGS, (UMR 7516 CNRS-UdS), Strasbourg, France3. Sigma Space Corp., Lanham, MD, USAThe Gravity Recovery And Climate Experiment(GRACE) mission has been launched in March 2002, and hasmeasured since the Earth’s time-variable gravity field at highspatial and temporal resolution. Among the applications hasbeen the monitoring of the changes in terrestrial waterstorage (TWS). The standard product developed by theGRACE project and various analysis centers has beenmonthly unconstrained spherical harmonic solutions, whichcan be converted to grids of surface water changes. Thesolutions are affected by strong correlated noise (striping),which can be removed by various filtering techniques. Thisfiltering reduces the amplitude of the retrieved TWS, whichis can be corrected by “re-scaling” the signal using hydrologymodels. At GSFC we have developed global solutions using alocalized mascon (mass concentrations) approach. Usingappropriate constraints, these global solutions allow bettertemporal (10 days) and spatial (2 degree) resolutions, thanthe classical spherical harmonic solutions and do not requireany post-processing. We have developed global solutionswith and without a priori forward-modeling of hydrology.We inter-compare these solutions on a continent and riverbasin basis to global hydrology models, as well as othergridded products derived from the GRACE mission.Lenters, JohnAn international collaboration to examine globallake temperature trends from in situ and remotesensing data: Project objectives and preliminaryresultsLenters, John 1 ; Adrian, Rita 2 ; Allan, Mathew 3 ; de Eyto,Elvira 4 ; Dong, Bo 1 ; Hamilton, David 3 ; Hook, Simon 12 ;Izmestyeva, Lyubov 5 ; Kraemer, Benjamin 6 ; Kratz, Tim 6 ;Livingstone, David 7 ; Mcintyre, Peter 6 ; Montz, Pam 6 ; Noges,Peeter 8 ; Noges, Tiina 8 ; O’Reilly, Catherine 14 ; Read, Jordan 6 ;Sandilands, Ken 9 ; Schindler, Daniel 10 ; Schneider, Philipp 11 ;Silow, Eugene 5 ; Straile, Dietmar 13 ; Van Cleave, Katherine 1 ;Zhdanov, Fedor 51. School of Natural Resources, Univ. of Nebraska-Lincoln,Lincoln, NE, USA2. Leibniz-Institute of Freshwater Ecology and InlandFisheries, Berlin, Germany3. The Univ. of Waikato, Hamilton, New Zealand4. Marine Institute, Newport, Ireland5. Irkutsk State Univ., Irkutsk, Russian Federation6. Univ. of Wisconsin-Madison, Madison, WI, USA7. Eawag, Dubendorf, Switzerland8. Estonian Univ. of Life Sciences, Tartu, Estonia9. Fisheries and Oceans Canada, Winnipeg, MB, Canada10. Univ. of Washington, Seattle, WA, USA11. Norwegian Institute for Air Research, Kjeller, Norway12.JPL, California Institute of Technology, Pasadena, CA,USA13.Univ. of Konstanz, Konstanz, Germany14. Illinois State Univ., Normal, IL, USARecent studies have revealed significant warming oflakes throughout the world, and the observed rate of lakewarming is – in many cases – more rapid than that of theambient air temperature. These large changes in laketemperature have profound implications for lakehydrodynamics, productivity, and biotic communities. Thescientific community is just beginning to understand theglobal extent, regional patterns, physical mechanisms, andecological consequences of lake warming. Although many insitu lake temperature records are available, only a fewencompass long time periods. Most datasets are collected byindividual investigators, have varying sampling protocols,and do not have extensive geographic or temporal coverage.Remote sensing methods, on the other hand, have beenincreasingly used to characterize global trends in lake surfacetemperature, and they provide an invaluable counterpart toin situ measurements. However, the existing satellite recordsdo not extend as far back in time as some of the longer insitu datasets, and remotely sensed measurements captureonly surface temperature, rather than vertical profiles. Inthis study, we present project objectives and preliminaryresults from an international collaborative effort tosynthesize global records of lake temperature from in situand satellite-based measurements. Surface watertemperature data are analyzed from over 120 lakesdistributed across 40 countries. Data from 20 of the lakesare based on in situ measurements, while the remaining89

100+ lake temperature records are obtained from satellitebasedmethods. We focus primarily on mean summer watertemperatures for the 25-year period 1985-2009, as thisprovides a common time period with the largest amount ofavailable data. Linear regression analysis reveals that 65% ofthe lakes in the database are experiencing significantsummertime warming (p < 0.1), with another 30% warmingat a rate that is not statistically significant. Only 5% of thelakes in the database show cooling trends (none of which aresignificant). The in situ and satellite-based measurementsshow a very similar distribution of water temperature trendsamong lakes, with a mean value of approximately +0.5°C/decade and standard deviation of +/-0.3 °C/decade(maximum = +1.0 °C/decade). We also examine a variety ofexternal controlling factors (climate, geography, lakemorphometry, etc.) to understand the physical mechanismsassociated with the global and regional patterns of lakewarming.Lenters, John D.Towards a Circum-Arctic Lakes ObservationNetwork (CALON)Jones, Benjamin M. 1 ; Hinkel, Kenneth M. 2 ; Lenters, John D. 3 ;Grosse, Guido 4 ; Arp, Christopher D. 5 ; Beck, Richard A. 2 ;Eisner, Wendy R. 2 ; Frey, Karen E. 6 ; Liu, Hongxing 2 ; Kim,Changjoo 2 ; Townsend-Small, Amy 21. Alaska Science Center, U.S. Geological Survey, Anchorage,AK, USA2. Department of Geography, University of Cincinnati,Cincinnati, OH, USA3. School of Natural Resources, University of Nebraska,Lincoln, NE, USA4. Geophysical Institute, University of Alaska Fairbanks,Fairbanks, AK, USA5. Institute of Northern Engineering, University of AlaskaFairbanks, Fairbanks, AK, USA6. Geography, Clark University, Worcester, MA, USARoughly one-quarter of the lakes on Earth are located inthe Arctic. To date, however, there has been no systematiccollection of key lake parameters or baseline data in theArctic to assess changes in lake water quality and quantity(e.g. due to the impacts of warmer temperatures, changes incloud cover and precipitation patterns, permafrostdegradation, and human water use). With funding from theNational Science Foundation’s Arctic Observing Network(AON) program we are working towards the establishmentof a Circum-Arctic Lakes Observation Network (CALON) byfocusing our initial efforts on a set of lakes located innorthern Alaska. Our team members have been working onlakes in Arctic Alaska for the past decade and are currentlymonitoring lake characteristics at a number of locations.The primary objectives of CALON are to expand andintegrate our existing lake monitoring network across ArcticAlaska as well as to further develop lake monitoringstrategies for Arctic conditions to provide data for keyindices using in situ measurements, field surveys, andremote sensing/GIS technologies. CALON will monitor keyindices such as lake temperature, water level, net radiation,ice cover, and numerous water quality and biophysicalparameters. In <strong>2012</strong>, we will enhance the existing in situnetwork by instrumenting lake monitoring sites to collectyear-round baseline data and assess physical, chemical, andbiological lake characteristics across environmentalgradients. This will be accomplished by implementing amulti-scale (hierarchical) lake instrumentation scheme with16 intensive and 35 basic monitored lakes. Regional scalingand extrapolation of key metrics will be accomplishedthrough calibration and validation of satellite imagery withground measurements. Thus, multi-sensor remote sensingwill be a key component in the development of CALON.Initially, we will focus on bathymetric mapping using highresolutionmultispectral satellite imagery, detection of waterquality parameters using spaceborne platforms, historic lakestage and ice surface elevation measurements using ICESatand comparable future laser altimetry missions, thedetection of surface water temperatures from spacebornethermal imagers, as well as changes in lake ice timing andthickness using SAR image time series. Through thecombination of in situ field sensors and continuous datalogging, field surveys, and spaceborne remote sensing weplan to standardize protocols that will enable inter-sitecomparison and to prepare for expansion towards a pan-Arctic network. All data acquired within CALON will bemade publicly available in a timely manner in accordancewith NSF AON goals of rapid data sharing. Further,measurements collected by the CALON project can be usedas validation sites for future airborne and spacebornemissions in the Arctic.https://sites.google.com/a/giesn.com/nsf-calon/Lettenmaier, Dennis P.Planning for the Next Generation of Water CycleMissions INVITEDLettenmaier, Dennis P. 11. Dept Civil Eng, Univ Washington, Seattle, WA, USARemote sensing has become an increasingly common, ifnot routine, source of observations for the hydrology andwater cycle community. In many parts of the globe where insitu observations are sparse, remote sensing is a criticalsource of information about precipitation, land cover,surface and subsurface storage, and snow, without whichmodern hydrologic predictions would be difficult orimpossible. In 2007, the U.S. National Research Councilissued the Decadal Review of Earth Science and Applicationsfrom Space (ESAS) – the first attempt to prioritize the nextgeneration of earth science missions. Missions were groupedinto three tiers – nominally on the basis of readiness,although the tiers de facto became priority levels. Of threemissions considered by the Decadal Review that wereprimarily related to hydrologic science and applications, onewas assigned to each of the three tiers – SMAP (SoilMoisture Active Passive) to tier 1, SWOT (Surface Water andOcean Topography) to tier 2, and SCLP (Snow and ColdLand Processes) to tier 3. GRACE-2, also of great interest to90

hydrologists, was initially assigned to tier 3, but since hasbeen assigned higher priority. In addition, the GlobalPrecipitation Measurement mission (GPM), which was onthe verge of cancellation at the time the Decadal Review wasinitiated, is now on track for launch in 2014. However, all hasnot gone smoothly in the five years since ESAS. Two socalled“foundational missions” (missions already indevelopment at the time of ESAS) were lost due to launchfailures – OCO (the Orbital Carbon Observatory) in early2009 and Glory (solar irradiance and aerosol observations)in 2011. Costs of the four tier 1 missions have escalatedrapidly, to the point that two of the four (DESDYNI –interferometric SAR and lidar for surface deformation andrelative surface process research) and CLAREO (solarirradiance) have been placed on indefinite hold. In addition,budget cuts make it almost certain that launch dates for theremaining tier 1 and tier 2 missions which nominally are “ontrack” will be extended, and the likelihood of launch of anytier 3 missions within the decade is essentially nil. Againstthis backdrop, I evaluate the outlook for the next generationof hydrology and water cycle missions, including the needand opportunity for international collaboration, and theopportunities for alternative (e.g. suborbital) remote sensingplatforms and their relevance to hydrologic problems.Lievens, HansAssimilation of SMOS data into a coupled landsurface and radiative transfer model for improvingsurface water managementPauwels, Valentijn R. 1 ; Lievens, Hans 1 ; Verhoest, Niko E. 1 ; DeLannoy, Gabrielle 1 ; Plaza Guingla, Douglas 1 ; van den Berg,Martinus J. 1 ; Kerr, Yann 2 ; Al Bitar, Ahmad 2 ; Merlin, Olivier 2 ;Cabot, Francois 2 ; Gascoin, Simon 2 ; Wood, Eric 3 ; Pan, Ming 3 ;Sahoo, Alok 3 ; Walker, Jeffrey 4 ; Dumedah, Gift 4 ; Drusch,Matthias 51. Laboratory of Hydrology and Water Management, GhentUniversity, Ghent, Belgium2. Centre d’Etudes Spatiales de la Biospehère, Toulouse,France3. Land Surface Hydrology Group, Princeton University,Princeton, NJ, USA4. Department of Civil Engineering, Monash University,Melbourne, VIC, Australia5. European Space Agency, Noordwijk, NetherlandsThe Soil Moisture and Ocean Salinity (SMOS) satellitemission is routinely providing novel accurate data with ahigh acquisition frequency at the global scale. However, theintegration of low resolution SMOS observations into finerresolution land surface models poses significant challenges,through which the potential of the satellite mission foroperational hydrology is at present poorly understood.Therefore, this study aims at developing a robust end-to-endmethodology that allows for the assimilation of SMOS data(either brightness temperature or soil moisture) into landsurface models and for assessing the usefulness of SMOSdata with respect to flood forecast. The assimilation systemis being set up for the Variable Infiltration Capacity (VIC)land surface model, coupled to a river routing scheme. TheVIC model will be run over two large river basins, the UpperMississippi Basin in central USA, and the Murray DarlingBasin in Eastern Australia, both of which are characterizedby a low contamination with radio frequency interference(RFI). A radiative transfer model, the Community MicrowaveEmission Model (CMEM), is being coupled to VIC in orderto assimilate the top of atmosphere (TOA) brightnesstemperatures from SMOS over both river basins, in additionto derived soil moisture. The data assimilation system to beused is the Ensemble Kalman filter. Finally, differentdisaggregation strategies will be explored to analyze theoptimal way for integrating low resolution SMOSobservations into higher resolution land surface models.http://www.hydro-smos.be/Lievens, HansSoil moisture retrieval from SAR over bare soil andwheat fields based on Water Cloud modeling, theIEM and effective roughness parametersLievens, Hans 1 ; Verhoest, Niko 11. Laboratory of Hydrology and Water Management, GhentUniversity, Ghent, BelgiumThe retrieval of the top surface soil moisture contentfrom Synthetic Aperture Radar (SAR) has been extensivelystudied during the past decades; nevertheless, it remains achallenging task. Particularly for bare soil fields, theparameterization of the surface roughness is veryambiguous. Field measurements of roughness parameters,such as the surface root mean square (RMS) height, show tobe highly variable even within one agricultural field, andmoreover strongly depend on the measurement techniqueapplied. Furthermore, the soil moisture retrieval ofagricultural fields is often hampered by varying vegetationeffects on the backscattered signal along the growing season.This study analyses the potential and limits of a soilmoisture retrieval methodology which is based on the IEMand calibrated or effective roughness parameters. Theretrieval technique is applied to a large number of bare soilagricultural fields in Flevoland, The Netherlands, over whicha series of C-band RADARSAT-2 HH- and VV-polarizedacquisitions have been collected in the frame of the AgriSAR2009 campaign, organized by the European Space Agency(ESA). The retrieval accuracy is found to be around 4 vol%,with slightly better performance for HH than VVpolarization. Furthermore, it is analyzed whether the soilmoisture retrieval methodology can be prolongedthroughout the growing season of wheat. Therefore, theretrieval technique developed for bare soil fields is extendedthrough including a vegetation backscatter model, i.e., thesemi-empirical Water Cloud Model (WCM). A number ofbulk vegetation parameters, involving LAI, VWC, and LWAI,are investigated with regard to the modeling of wheatcanopy and the retrieval of the underlying soil moisturecontent. For a series of L-band E-SAR acquisitions duringAgriSAR 2006, the use of LAI yields the highest soil moistureretrieval accuracy, i.e., RMSE = 5.5 vol%. These results91

demonstrate that effective roughness parameters are apromising tool for soil moisture retrieval, both for bare soilsand soils underlying wheat vegetation throughout the entiregrowth cycle.Lin, Yao-ChengRemote Sensing of Soil Moisture with Signals ofOpportunityLin, Yao-Cheng 1 ; Garrison, James 1 ; Cherkauer, Keith 11. Purdue university, West Lafayette, IN, USAAbstract Measurement of soil moisture is very essentialfor studying the hydrological cycle. Passive microwaveradiometry is the most mature technology for the remotesensing of soil moisture, as demonstrated on ESA’s SMOSsatellite and the upcoming SMAP mission from NASA. L-band (1.4GHz) is the frequency used for thesemeasurements, a compromise between the required antennasize and the sensitivity to soil moisture. The frequenciesselected for SMOS and SMAP also enjoy strong isolationfrom radio frequency interference (RFI) in bands protectedfor radio astronomy. L-band radiometry, however, onlysenses the moisture within the top few cm of the soil andrequires a relatively large antenna to meet requirements onsurface resolution. Recently, alternative approaches tomeasure soil moisture, through reflectometry of GlobalNavigation Satellite System (GNSS-R) signals have beendemonstrated, both from airborne receivers and groundbasedtowers. This paper will present a study on theextension of reflectometry techniques to other satellitetransmissions, so-called “signals of opportunity” (SoOp).Recent experiments in ocean remote sensing have shownthat the methods developed for GNSS-R can be applied tosome digital satellite transmission, demonstrated on the S-band (2.3 GHz) signals from the XM radio satellites.Presently, an experiment is being prepared to test the use ofSoOp for soil moisture sensing, making use of high-powersatellite transmissions on frequencies both above and belowthose protected in L-band. This combination of frequencieswould allow sensitivity at multiple soil depths. The crosscorrelationtechniques inherent in GNSS-R methods are alsovery robust against RFI. This experiment will obtain directand reflected measurements from a set of antennas installedon a tower at a height of 30-35 meters. In situ sensors will beinstalled in the soil, at the location of the specular reflectionpoint, at various depths to provide calibration as close aspossible to the reflectivity measurement. In thispresentation, we will present the theoretical background ofSoOp remote sensing of soil moisture, the expectedperformance of this technique, and the development of thefield experiment.Link, PercyVariability of oceanic and terrestrial water vaporsources in the Amazon Basin: An investigationusing TES satellite and MERRA reanalysis atvarying temporal resolutionsLink, Percy 1 ; Goldner, Aaron 2 ; Whadcoat, Siobhan 3 ; Fiorella,Rich 41. Earth and Planetary Science, UC Berkeley, Berkeley, CA,USA2. Earth and Atmospheric Sciences, Purdue University, WestLafayette, IN, USA3. Earth Sciences, Syracuse University, Syracuse, NY, USA4. Earth and Environmental Sciences, University ofMichigan, Ann Arbor, MI, USAPrecipitation in the Amazon region depends on both thelarge-scale circulation (Hadley and Walker cells) and local- toregional-scale dynamics of evapotranspiration, whichrecycles moisture from the land surface. We will use remotelysensed observations to investigate the sources ofatmospheric water vapor over the Amazon Basin and toexamine the relative contributions of oceanic and terrestrialwater vapor sources. By comparing isotopic data from theTropospheric Emission Spectrometer (TES) with ModernEra Retrospective Analysis for Research and Applications(MERRA) reanalysis data, we will investigate the spatial andtemporal variability of water vapor sources and the factorsthat drive the variability. We will focus on two timescales. Inthe first, we will analyze individual storm tracks as theymove west across the basin to study the impacts of waterrecycling on the isotopic signature of vapor of the air mass.In the second, we will analyze seasonal climatologies toconstrain interannual variability. From this perspective, wewill investigate the sources of variability, such as the El NiñoSouthern Oscillation (ENSO), shown by the climatologies.Using high resolution TES data, we will isolate isotopicshifts over the Amazon region in comparison to the MERRAreanalysis, which should describe the dynamics controllingthe flux of moisture into the region. This study will exploreat very high temporal resolution how precipitation andisotopic concentrations evolve during El Niño and La Niñaevents, and during years when equatorial Pacific sea surfacetemperatures are in their neutral mode. The use of highresolution observational data should help determine thesources of moisture in the Amazon region and how thesesources shift during El Niño and La Niña.Liston, Glen E.An Improved Global Snow Classification Datasetfor Hydrologic ApplicationsListon, Glen E. 1 ; Sturm, Matthew 21. Colorado State University, Fort Collins, CO, USA2. U. S. Army Cold Regions Research and EngineeringLaboratory, Ft. Wainwright, AK, USAOut of a need to improve our description andunderstanding of snow covers found around the world,92

Sturm et al. (1995) introduced a seasonal snow coverclassification system for local to global applications. It hasseen considerable use since its initial development, but theoriginal dataset describing the global distribution of snowclasses was limited by its ~50 km spatial resolution.Consequently, it could not be used in high-resolutionapplications. The latest available fine-scale atmosphericforcing, topography, and land cover datasets were used torecalculate the snow classes on a global ~1 km grid. Thisnew resolution greatly increases the accuracy of the systemand opens the door for additional uses. Here we provide asummary of the new dataset and example applications thatinclude: 1) defining snow parameter values for regional andglobal snow-process and climate modeling at fine spatialscales, 2) defining parameter values to enhance snow remotesensingalgorithms, 3) categorizing and/or stratifying fieldmeasurements and/or model outputs, and 4) definingparameter values for snow-property models such as depthdensityrelationships, again at real landscape scales. See theSnowNet website (www.ipysnow.net) for access to the newclassification system.Liu, HuidongValidation of modeled lake water level variationsdue to changing climate, thermal variations andhuman activities using satellite observationsLiu, Huidong 1 ; Famiglietti, James S. 1, 2 ; Subin, Zachary M. 3, 41. Earth System Science, Univ. of California, Irvine, Irvine,CA, USA2. UC Center for Hydrologic Modeling, University ofCalifornia, Irvine, CA, USA3. Energy & Resources Group, University of California,Berkeley, Berkeley, CA, USA4. Earth Sciences Division, Lawrence Berkeley NationalLaboratory, Berkeley, CA, USALake level variations are mainly driven by changingclimate, and can also be altered by human regulations suchas dams, diversions and dredging activities. In this study,lakes are included in a coupled routing model andcatchment-based land surface model (CHARMS), which ismodified from the land-surface component (CLM4) of anEarth system model (CESM1). In the routing scheme, lakesare connected with rivers using upstream/downstreamrelationships in a lake basin. Evaporation, precipitation, andriver runoff are modeled in order to close the lake waterbudget. However, the original lake model in CLM4 poorlypredicts the lake temperature, which highly affects theevaporation and surface energy fluxes. Using an improvedlake model (CLM4-LISSS) the lake water temperature andsurface energy flux are better predicted. This new version ofCHARMS is tested on several large lakes around the world(e.g., the Great Lakes, and Lake Victoria) to evaluate itsperformance in different climate zones. The impacts ofhuman regulation on lakes will be included as a term in theoutflow. Modeled lake level time series are compared withsatellite altimetry. In order to test the ability of CHARMS tosimulating the variations of lake temperature, we comparethe amount of thermal expansion calculated from modeledlake temperature with the amount of thermal expansiondetermined from Gravity Recovery and Climate Experiment(GRACE) and satellite altimetry data.Liu, ZhaoAn Explicit Representation of High Resolution RiverNetworks using a Catchment-based Land SurfaceModel with the NHDPlus dataset for CaliforniaRegionLiu, Zhao 2 ; Kim, HyungJun 1 ; Famiglietti, James 1, 21. UC Center for Hydrologic Modeling, Univ. of California,Irvine, Irvine, CA, USA2. Dept. of Earth System Science, Univ. of California, Irvine,Irvine, CA, USAThe main motivation of this study is to characterize howaccurately we can estimate river discharge, river depth andinundation extent using an explicit representation of theriver network with a catchment-based hydrological androuting modeling system (CHARMS) framework. Here wepresent a macroscale implementation of CHARMS overCalifornia. There are two main components in CHARMS: aland surface model based on National Center AtmosphericResearch Community Land Model (CLM) 4.0, which ismodified for implementation on a catchment template; anda river routing model that considers the water transport ofeach river reach. The river network is upscaled from theNational Hydrography Dataset Plus (NHDPlus) to theHydrologic Unit Code (HUC8) river basins. Both long-termmonthly and daily streamflow simulation are generated andshow reasonable results compared with gage observations.With river cross-section profile information derived fromempirical relationships between channel dimensions anddrainage area, river depth and floodplain extent associatedwith each river reach are also explicitly represented. Resultshave implications for assimilation of surface water altimetryand for implementation of the approach at the continentalscale.Lovejoy, ShaunThe Space-time variability of precipitation frommillimeters to planetary scales, from hours tocenturies: emergent laws and multifractal cascadesLovejoy, Shaun 1 ; Schertzer, Daniel 21. Dept Physics, McGill Univ, Montreal, QC, Canada2. LEESU, École des Ponts ParisTech, Université Paris-Est,Marne-la-Vallée, FrancePrecipitation is the key input field into hydrologicalsystems and models; it displays extreme variability withcomplex structures embedded within structures, from dropto planetary scales in space and from milliseconds tomillennia in time. Numerous applications including remotesensing require detailed hypotheses about its space-timevariability: commonly they assume (unrealistically) that thesubsensor structure is homogeneous. The only hope for93

ealistic models of the structure - i.e. to tame the variability -is the existence of some scale by scale regularity, the existenceof regimes which are in some sense scale invariant over wideranges of space-time scales. Over the past thirty years it hasbecome clear that scale invariance is a symmetry principle ofgreat generality; a system can scale invariant even when it ishighly anisotropic so that small and large structure arestatistically related by “zooms” followed by the squashingand rotation of structures. It is also known thatmultiplicative cascades are typically associated withnonlinear scale invariant dynamics. Today, technologicaladvances have permitted observations of precipitation overwide ranges of scales including the extreme small drop scales(using stereophotography) and the extreme large planetaryscales (using satellite borne radar) as well as meteorologicalreanalyses and to continental scale gridded raingageproducts. Below scales of roughly 30 - 50 cm (depending onthe rate) the rain decouples from the turbulence formingstatistically homogeneous “patches”. At larger scales, on thecontrary, the precipitation is strongly coupled with theturbulence so that the liquid water statistics are very nearlythose of passive scalars. Using in situ rain gage networks,ground and satellite radar data and meteorologicalreanalyses, we show that the precipitation has amultiplicative cascade structure up to planetary scales inspace and up to w 5- 10 days in time. At times longer thanw - the lifetime of planetary scale structures – the statisticsof atmospheric fields (including precipitation) becomemuch “calmer”, the spatial degrees of freedom are essentiallyquenched (a “dimensional transition”). We have theemergence of a new “low frequency weather” regime whosestatistics we characterize. But precipitation is stronglynonlinearly coupled to the other atmospheric fields. To becredible, this scale invariant cascade dynamic must apply tothe other fields as well. We outline such a paradigm based ona) advances in the last 25 years in nonlinear dynamics, b) acritical reanalysis of empirical aircraft and vertical sondedata, c) the systematic scale by scale space-time exploitationof high resolution remotely sensed data (TRMM radar andradiances, MTSAT radiances) d) the systematic reanalysis ofthe outputs of numerical models of the atmosphereincluding GFS, GEM models and the ERA40, and the NOAA20th Century reanalyses) and e) a new turbulent model forthe emergence of the climate from “weather” and climatevariability. We discuss applications to the remote sensing ofrain and implications for hydrology.Luo, YuezhenHigh-Resolution Regional Analyses of Daily andHourly Precipitation Climatology over EasternChinaLuo, Yuezhen 1 ; Shan, Quan 1 ; Chen, Liang 1 ; Luo, Yang 1 ; Xie,Pingping 21. CMA Zhejiang Meteorological Bureau, Hangzhou City,China2. NOAA Climate Prediction Center, Camp Springs, MD,USAAnalyses of daily and hourly precipitation climatologyare constructed on a 1kmx1km grid over Zhejiang Provinceof eastern China through interpolating station data withorographic consideration. The high-resolution regionalprecipitation climatology are defined using the PRISMmonthly climatology of Daly et al. (1994), station reports ofdaily and hourly precipitation from 1961 to 2010 at 68stations over the province of ~100K km2, and DEMelevation data. The PRISM monthly climatology used in thisstudy was constructed on a 5kmx5km resolution over Chinawith orographic consideration and represents the meanclimatology for 1961-1990. First, monthly climatology withorographic consideration is defined on a 1kmx1km grid torepresent the mean state of precipitation for 1981-2010. Tothis end, analyzed fields of ratio between monthly stationnormal for 1981-2010 and that for 1961-1990 areconstructed for each calendar month by interpolatingcorresponding station values at the 68 stations using thealgorithm of Shepard (1965). The analyzed ratio is thenmultiplied to the 1961-1990 PRISM climatology to get theanalyzed fields of PRISM monthly climatology for 1981-2010on a 5kmx5km grid. This PRISM monthly climatology isfurther desegregated to a finer grid of 1kmx1km usinglocally established empirical linear relationship betweenprecipitation climatology and elevation. To define analyzedfields of daily climatology, mean daily precipitation is firstcomputed for each calendar day and for each of the 68stations using the station daily reports from 1981 to 2010.Harmonic analysis is performed to the raw time series of365-day mean daily station precipitation and the summationof the first 6 component is defined to represent theevolution of seasonal changes of daily precipitation at eachstation. Analyzed fields of daily precipitation climatology arethen constructed on a grid of 1kmx1km by interpolating thetruncated daily station values and adjusting the interpolateddaily fields against the monthly PRISM climatologydescribed above. The resulting daily precipitationclimatology presents orographic effects passed from thePRISM climatology through the adjustment. To documentthe seasonal evolution of diurnal cycle, analyzed fields ofhourly precipitation are constructed on a 1kmx1km gridover the province for each of the 365 calendar day. To thisend, raw hourly mean precipitation is computed for eachhourly box and for each calendar day using station reportsfor 1981-2010. Reports for a 15-day sliding window centeringat the target day are used in defining the raw hourly meanvalues. The time series of 24 mean hourly values for each94

calendar day are then truncated and the summation of thefirst 4 harmonic components is used to define the stationmean hourly climatology. Analyzed fields of hourlyprecipitation climatology are finally defined by interpolatingthe truncated station hourly climatology and adjusting theinterpolated hourly values against the gridded dailyprecipitation climatology described above. Cross-validationtests showed reasonable performance of the high-resolutiondaily and hourly precipitation climatology.Mace, Gerald G.Use of Dual Frequency Doppler Radar Spectra toInfer Cloud and Precipitation Properties and AirMotion StatisticsMace, Gerald G. 11. Dept Meteorology Rm 819 819WBB, Univ Utah, Salt LakeCity, UT, USAThe processing of water through the atmosphere occursvia physical processes that are inherently linked to themotions of the atmosphere. Representing such processesaccurately in atmospheric models is a significant challenge.One of the reasons that our understanding of the water cycleremains poor is because of a dearth of empirical datadocumenting these processes. The observational challenge issignificant since such atmospheric volumes are complicatedby multiple phases of water existing within turbulent verticalmotions. Only radar can often penetrate the vertical depthsof such systems and often multiple frequencies of radar areneeded to infer the particle properties using differentialattenuation and scattering properties. Doppler informationprovides additional information regarding air motions andparticle sizes. We have been exploring the capacity ofmultiple frequency Doppler spectra to provide uniqueinformation of precipitating systems that will allow forretrieval of profiles of cloud, precipitation, and air motionproperties. The information available in such data sets willbe described and several case studies illustrating snowingmiddle latitude systems, raining tropical congestus, anddrizzling marine stratocumulus will be presented.Mace, JayA new instrument for high-speed, high resolutionstereoscopic photography of falling hydrometeorswith simultaneous measurement of fallspeedGarrett, Timothy J. 1 ; Fallgatter, Cale 1 ; Yuter, Sandra 2 ; Mace,Jay 11. Atmospheric Sciences, University of Utah, Salt Lake City,UT, USA2. North Carolina State, Raleigh, NC, USAWe introduce a new instrument called the Multi-AngleSnowflake Camera (MASC). The MASC provides

precipitable water) and surface albedo were used as inputs.Net longwave radiation was estimated according to theStephen-Boltzmann approximation where MODIS landsurface temperature/emissivity (MOD11), atmosphericprofile products (MOD07) and cloud products (MOD06)were exploited. The land surface temperature from theNCEP/NCAR re-analysis data was used to resolve cloudy skylongwave radiation. Taking the MODIS Terra overpass hourdata (11:30 am) for January 2003, an Initial evaluation of RNwas carried out over a variety of biome classes (forest,agriculture, savanna and grassland etc.) covering theFLUXNET eddy covariance network. This evaluationrevealed that the MODIS RN could clearly capture thevariation in both clear and cloudy skies. The cropland (CRO)and deciduous broadleaf forests (DBF) showed maximumcorrelation of 0.71 to 0.75, whereas poor correlation wasobserved for evergreen needle-leaf forests (ENF). The rootmean square error (RMSE) varied between 45 W m-2 (DBF)to 207 W m-2 (SAV). This RN product will now be used forthe development of MODIS-based 1 km2 evapotranspirationfields and for the further evaluation of the earth systemmodels.Mallick, KaniskaA satellite net available energy retrieval scheme forglobal evapotranspiration studies using AQUAplatformMallick, Kaniska 1 ; Jarvis, Andrew 2 ; Wohlfahrt, Georg 3 ; Kiely,Gerard 4 ; Niyogi, Dev 5 ; Fisher, Joshua B. 11. Water and Carbon Cycles, Jet Propulsion Laboratory,California Institute of Technology, NASA, Pasadena, CA,USA2. Lancaster Environment Centre, Lancaster University,Lancaster, United Kingdom3. Ecosystem Research & Landscape Ecology, University ofInnsbruck, Innsbruck, Austria4. Department of Civil and Environmental Engineering,University College Cork, Cork, Ireland5. Agronomy and Earth and Atmospheric Sciences, PurdueUniversity, West Lafayette, IN, USASatellite based estimation of evapotranspiration has agreat reliance on the accuracy of the net available energyretrieval. However, no studies have been reported directretrieval of net available energy using satellite data. Thispaper introduces a relatively simple method for estimatingglobal fields of net radiation and near-surface net availableenergy (the sum of the sensible and latent heat flux or thedifference between the net radiation and surface heataccumulation) using earth observation visible and infra-redsounding products from AIRS (Atmospheric InfraredSounder) and, atmospheric data from MODIS (MOderateResolution Imaging Spectroradiometer). The methodfocuses on first specifying net surface radiation byconsidering its various shortwave and longwavecomponents. A robust generic model for shortwave radiationretrieval was constructed from the observed relationshipbetween atmospheric transmissivity, MODIS cloud coverfraction and cloud optical depth, evaluated over 95FLUXNET tower sites. Surface net longwave radiation wasretrieved directly from the AIRS longwave radiance data. Thenoon and nighttime net radiation was then used in a surfaceenergy balance equation in conjunction with AIRS noonnightsurface temperature difference to derive 12 hourdiscrete time estimates of surface system heat capacity andheat accumulation, leading directly to the retrieval forsurface net available energy. Taking monthly average 13:30hour data for the year 2003, net radiation and net availableenergy estimates were evaluated against ground truth dataover 35 terrestrial tower sites affiliated to the FLUXNETnetwork covering a broad spectrum of climate regimes. Thisrevealed a relatively good agreement between the satelliteand tower data, with a pooled root mean square deviation of57 and 73 W m-2 for net radiation and net available energyrespectively. Analysis of the individual shortwave andlongwave components of the net radiation revealed thedownwelling shortwave radiation to be main source of thiserror.Maness, HollyThe Hydrologic Impact of the British ColumbiaMountain Pine Beetle Infestation From RemotelySensed DataManess, Holly 1 ; Kushner, Paul 1 ; Fung, Inez 21. University of Toronto, Toronto, ON, Canada2. University of California at Berkeley, Berkeley, CA, USAThe current mountain pine beetle infestation in BritishColumbia forests ranks among the largest scale disturbancesrecorded to date, affecting approximately 200,000 squarekilometers since the disturbance began in the mid-1990’s.We present an effort to quantify the hydrologicalconsequences of this devastation using a combination of insitu and remotely-sensed observations. The bulk of volumekilled is contained within the 217,000-square-kilometerFraser River basin. However, while precipitation,evapotranspiration, runoff, and storage observationsaggregated at this scale exhibit strong consistency (Figure 1),the effects of disturbance are not detected at this regionalscale. Observations obtained at the sub-regional level (e.g.,AVHRR 8-kilometer observations) similarly show very littleor no change. Given the modest fractional volume killed inmany stands and the spatial discontinuity of severelyaffected areas, only at the scale of 1-kilometer MODISobservations do the effects of disturbance become evident(Figure 2). We describe ongoing efforts to quantify changesin evapotranspiration and snow cover at this scale, as well asthe resulting consequences for land surface temperature.Preliminary results indicate that changes inevapotranspiration can be significant locally, exceeding 30%for volumetric kill fractions of 50% and greater. Results suchas these will serve as an important testbed for climatemodels incorporating the effects of disturbance on foresthydrology. Still, as the average forest volume killed forimpacted areas is less than 20%, the present feedback on96

climate associated with hydrological changes is expected tobe small.compared to the SEBAL version without any modification,and it significantly discriminated ET among 75.8% ofvegetation types, at threshold differences in ET 0.5mm/day.Figure 1Figure 2Mariotto, IsabellaApplication of SEBAL Modified for TopographicReflectance and Roughness to Map the SpatialDistribution of ET in a Heterogeneous AreaMariotto, Isabella 1, 2 ; Gutschick, Vincent P. 21. Soil, Water, Environmental Science, University ofArizona, Tucson, AZ, USA2. Global Change Consulting Consortium, Inc., Las Cruces,NM, USAThis study presents a methodology to build advancedenergy balance algorithms to map ET in a heterogeneoussemi-arid area presenting 12 different land covers rangingfrom sand dunes to grassland and shrublands. The SurfaceEnergy Balance Algorithm for Land (SEBAL) was modifiedfor the roughness term and for the albedo and vegetationindex by respectively incorporating a plant heightcomponent and a non-Lambertian topographic correction ofreflectance. Corrections were performed using a GISraster/vector platform integrated with ASTER thermal andreflectance imagery, and terrain and land cover data. SEBALcomputed with the modifications showed the bestagreement with the eddy covariance flux measurements,97McCabe, Matthew F.Multi-model regional scale estimation ofevapotranspirationMcCabe, Matthew F. 1 ; Ershadi, Ali 1 ; Evans, Jason 11. School of Civil and Environmental Engineering,University of New South Wales, Sydney, NSW, AustraliaAccurate estimation of surface heat fluxes is ofconsiderable interest to meteorological, climatological andagricultural investigations as they identify the key physicalprocesses that link the land surface with the atmosphere.While characterising surface fluxes is critical in describingthe partitioning of water and energy across Earths terrestrialsurfaces, accurately monitoring the spatial variation,particularly at daily and sub-daily scales, is notoriouslydifficult. Spatial and temporal scaling issues, errors inforcing variables, heterogeneity in surface characteristics andsimplifications in process understanding, all limit thecapacity to accurately monitor flux development andvariability. Here, common approaches such as the Penman-Monteith formulation are considered alongside remotesensing based techniques, surface energy balance retrievalsand coupled regional climate model output to examine thevariation and consistency within these different estimationapproaches. The work is discussed in the context of aninternational collaborative effort to develop a globalobservationally based climatology of surface heat fluxes,which is being coordinated by the GEWEX Radiation Panel.McCabe, Matthew F.Intercomparison of flux measurement approaches:eddy covariance, scintillometers and remotesensing retrievals over a grasslandMcCabe, Matthew F. 1 ; Ershadi, Ali 1 ; Graham, Peter 11. School of Civil and Environmental Engineering,University of New South Wales, Sydney, NSW, AustraliaThe accurate estimation of surface heat fluxes using insitubased instrumentation is of considerable importance,particularly in the evaluation of spatially distributed remotesensing based retrievals using satellite and other data. Usingthree recently installed instruments at the BaldryHydrological Observatory in the central-west of NSW inAustralia, an evaluation of these different estimationtechniques is undertaken through instrumentintercomparison and also using common meteorologicalestimation approaches, such as the Penman-Monteith andprofile methods. Remote sensing based retrievals are alsoexamined to establish the degree of spatial variability at thesite and the representativeness of ground based datacollections.

McCreight, James L.Validation of satellite-derived seasonal snow coverby airborne LiDARMcCreight, James L. 1, 2 ; Marshall, Hans-Peter 4 ; Slater,Andrew G. 3 ; Rajagopalan, Balaji 1, 31. Department of Civil, Environmental, and ArchitecturalEngineering, University of Colorado, Boulder, CO, USA2. Ames Research Center, NASA, Moffett Field, CA, USA3. CIRES, University of Colorado, Boulder, CO, USA4. Department of Geosciences, Boise State University, Boise,ID, USASatellite remote sensing of seasonal snow cover isdifficult. (Spatial heterogeneity of too many free variables,including grain size and surface state, complicate microwaveestimation). Equally problematic is the validation of satellitemeasurements. (Estimates without accurate error barsseverely limit application of the data). Airborne LiDARmeasurement of seasonal snow cover shows tremendouspotential for validation of space-borne measurements andfor understanding the validation problem more generally.Subsampling experiments on high spatial resolution LiDARobservations reveal how inference and uncertainty of mean(peak accumulation) snow depth and its spatial distributiondepend on sample size and attributes of predictor variables.In most environments, snow depth is a first order control onsnow water equivalent (SWE) and accounts for the majorityof SWE uncertainty. Results at 6 different 1.2 km 2 sites inthe Colorado Rockies (measured during NASA’s CLPXcampaigns) indicate that estimates of mean snow depthsnow are well constrained (±5% uncertainty) by 400observations and are insensitive to the quality of predictorvariables used in regression. Mean depth estimation at thekilometer scale can be reliably performed with a probe andpredictor sets downloaded from the internet. Estimation ofsnow depth spatial distribution (as measured by R 2 ),however, is typically poor, uncertain, and sensitive to thequality of predictor variables. The prerequisite (forcalculating snow depth as elevation differences), snow-freeLiDAR predictor maps of elevation and vegetation heightgreatly improve the inferred spatial distribution, particularlywhen vegetation dominates snow depth variability.Furthermore, these LiDAR maps are spatially scalable over arange of processes controlling the snow distribution andselecting the proper spatial resolution can help minimizeestimation uncertainty. Results also indicate that forpurposes of estimating the spatial distribution of snowdepth, snow-covered LiDAR observations can be at least 2orders of magnitude less dense than snow-free observations.Observation densities on the order of thousands per squarekm are easily obtainable via LiDAR and can reliably estimatesnow depth spatial distribution, particularly at sites withstrong snow depth variability. Though LiDAR currentlyexperiences difficulties in some environments, werecommend its development and careful application tovalidation of satellite measurements at scales of hundreds tothousands of square kilometers with the aim of quantifyingsatellite retrieval errors. Such investigations will also greatlybenefit our basic and empirical understanding of snowdepth scaling, predictability, and estimation and may bedesigned to benefit other important applications such aswater resource management.McDonald, Kyle C.Satellite Remote Sensing of Inundated Wetlands:Data Record Assembly and Cross-ProductComparisonMcDonald, Kyle C. 1, 2 ; <strong>Chapman</strong>, Bruce 2 ; Podest, Erika 2 ;Schroeder, Ronny 1, 21. Earth and Atmospheric Sciences, The City College ofNew York, New York, NY, USA2. Carbon and Water Cylces Group, Jet Propulsion Lab,California Institute of Technology, Pasadena, CA, USAWetlands cover less than 5% of Earth’s ice-free landsurface but exert major impacts on global biogeochemistry,hydrology, and biological diversity. Despite the importanceof these environments in the global cycling of carbon andwater, there is a scarcity of suitable regional-to-globalremote-sensing data for characterizing their distribution anddynamics. We are assembling a global-scale Earth SystemData Record (ESDR) of natural inundated wetlands tofacilitate investigations on their role in climate,biogeochemistry, hydrology, and biodiversity. The ESDRcomprises (1) Fine-resolution (100 meter) maps, delineatingwetland extent, vegetation type, and seasonal inundationdynamics for regional to continental-scale areas coveringcrucial wetland regions, and (2) global coarse-resolution(~25 km), multi-temporal mappings of inundated areafraction (Fw) across multiple years. The fine-scale ESDRcomponent is constructed from L-band synthetic apertureradar (SAR) data. The global maps of inundated areafraction are obtained by combining coarse-resolution (~25km) remote sensing observations from passive and activemicrowave instruments. Focusing on regions of the Amazonand South America, we present details of remote sensingdata collections, algorithm application, and cross-productharmonization. Surface water and inundated vegetation isclassified at 100m resolution using Advanced LandObserving System (ALOS) Phased Array type L-bandSynthetic Aperture Radar (PALSAR) imagery. We apply adecision tree thresholding algorithm to multi-year timeseries PALSAR ScanSAR data to classify surface inundationprocesses. We combine AMSR-E and SeaWinds-on-QuikSCAT passive/active microwave data sets to quantify Fwat 25 km resolution with ~weekly temporal composites from2002-2009. We compare information content and accuracyof the coarse resolution data sets relative to the SAR-baseddata sets. This ESDR will provide the first high-resolution,accurate, consistent and comprehensive global-scale data setof wetland inundation and vegetation. This work was carriedout in part within the framework of the ALOS Kyoto &Carbon Initiative. PALSAR data were provided byJAXA/EORC and the Alaska Satellite Facility. Portions ofthis work were conducted at the Jet Propulsion Laboratory,98

California Institute of Technology under contract to theNational Aeronautics and Space Administration.Melack, John M.Inland Waters and the Carbon Cycle INVITEDMelack, John M. 11. Univ California Santa Barbara, Santa Barbara, CA, USAOver the last decade the roles of inland waters incontinental and global scale carbon fluxes has becomerecognized as significant based on new measurements andsynthetic analyses complemented by applications of remotesensing. As these efforts have combined information aboutlakes, reservoirs, rivers, streams and wetlands, the high ratesof biogeochemical processes common in inland waters inconjunction with greater areal coverage than earlierestimates have increased their importance relative to oceansand land. Mounting evidence indicates that the flux ofcarbon delivered by rivers to oceans is only a fraction of thatentering inland waters from the atmosphere and land, andthat most carbon the moves in rivers ultimately outgases ascarbon dioxide or is stored in sediments of lakes, wetlandsand reservoirs. Inland waters are generally supersaturated incarbon dioxide and receive subsidies of organic andinorganic carbon from their watersheds. As a result, inlandwaters can be both net emitters of carbon to the atmosphereand net sinks of carbon in their sediments. Within thehumid tropics, high rates of productivity and extensiveinland waters indicate that this region is of particularinterest. Floodplains and associated lakes and wetlands arethe dominant aquatic habitat in the Amazon and areimportant on other tropical continents. Deciphering thecomplex interactions among the hydrology, ecology andbiogeochemistry of these systems has benefitted fromintensive studies and extensive surveys and remote sensing.Evasion of CO2 from rivers and wetlands of the Amazonbasin is of similar magnitude to net uptake by the forest andis an order of magnitude greater than fluvial export oforganic carbon; the greenhouse warming potential of themethane emitted is about 40% that of the carbon dioxide.Melton, Forrest S.An Operational Framework for Estimation ofAgricultural Evapotranspiration with the TerrestrialObservation and Prediction SystemMelton, Forrest S. 1, 2 ; Johnson, Lee 1, 2 ; Lund, Chris 1, 2 ; Pierce,Lars 1 ; Michaelis, Andrew 1, 2 ; Hiatt, Sam 1 ; Guzman, Alberto 1,2 ; Sheffner, Edwin 2 ; Nemani, Rama 21. California State University Monterey Bay, Seaside, CA,USA2. NASA Ames Research Center, Moffett Field, CA, USASatellite measurements of hydrologic parameters havegreat potential for supporting agricultural producers andwater managers working to optimize agricultural watersupply and use. Evapotranspiration (ET) and soil moisturedata are particularly important to both operational watermanagement and long-term planning. Integration of thisinformation into current management practices andoperational models requires the development of newapproaches for delivery of satellite-derived data andinformation products to water managers and agriculturalproducers. The NASA Terrestrial Observation and PredictionSystem (TOPS) provides a modeling and computingframework for integrating satellite and surface observationsin near real-time to meet these challenges. We presentfindings from the development and deployment of aprototype system for irrigation scheduling and managementsupport that utilizes TOPS and the NASA Earth Exchange(NEX) to integrate satellite observations from Landsat andMODIS with meteorological observations from theCalifornia Irrigation Management Information System(CIMIS). The system maps canopy development, associatedbasal crop coefficients (Kcb), and evapotranspiration (ETcb)for multiple crop types in the Central Valley of California ona daily basis at spatial resolutions that are useful forirrigation management at the field level (30m). Automatedatmospheric correction and gap-filling algorithms areoptimized for agricultural areas to provide a robust andreliable data stream. Integration of data from the NOAANWS Forecasted Reference ET (FRET) system allowsforecasting of potential consumptive use and associatedirrigation demand with lead times of up to 1 week,supporting both irrigation scheduling and water deliveryplanning. Information from the system is distributed towater managers and agricultural producers via a browserbasedirrigation management decision support system. Toprovide insight into the utility of the system for commercialfarming operations, we present findings from analysis ofdata collected by surface renewal stations and wireless soilmoisture sensor networks deployed in operationalagricultural fields across California in cooperation withgrowers. We also discuss strategies for extending theframework to include additional satellite-driven models forestimation of ET (potential and actual) and crop stress,which offer further potential for improving watermanagement and making irrigation scheduling morepractical, convenient, and accurate.http://ecocast.arc.nasa.gov/sims/Membrillo, Alejandra S.SEASONAL CHANGE DETECTION WITHMULTISPECTRAL IMAGES ON THE LAKE OFCHAPALA, MEXICOMembrillo, Alejandra S. 1 ; Prol-Ledesma, Rosa Maria 2 ;Estradas-Romero, Alejandro 21. Posgrado en Ciencias de la Tierra, Universidad NacionalAutonoma de México, Cd. México, Mexico2. Instituto de Geofisica, Universidad Nacional Autonomade México, Cd. México, MexicoMembrillo-Abad Alejandra Selene1*, Prol-Ledesma RosaMa. 2, EstradasRomero, Alejandro2 *1Posgrado en Cienciasde la Tierra. Universidad Nacional Autonoma de Mexico2Instituto de Geofísica. Universidad Nacional Autonoma deMexico The Lake of Chapala is the largest fresh body of99

water in Mexico. In the last sixty years it has undergonecritical changes due to human activity that includevariations in the size of the lake, increase of suspendedsediments and chlorophyll content. Overlaid to thosevariations, we have recorded large seasonal changes insuspended sediments that favor the growth ofbacterioplankton on the surface of the lake Multispectralsatellite images (TMLandsat) from May and November2002 were processed to identify suspended sediments andchlorophyll on the Lake of Chapala. Processing includedatmospheric correction, edge enhancement to define thewater body borders, spectral enhancement and principalcomponent analysis. Image processing was efficient to coversimultaneously the whole water body and providedidentification of the suspended sediments and chlorophyllpresence. Results show high concentration of suspendedsediments in the dry season image (May, 2002) and adramatic decrease in suspended sediments after the rainseason (November image) and an increase in chlorophyll dueto the high growth rate of the water hyacinth associatedwith the large input of fertilizers from the agricultural areasthat surround the lake tributaries as the Lerma river.Processed images show that higher chlorophyllconcentrations cluster on the eastern side of the lake drivenby the strong input of the Lerma River. The use of satellitemultispectral images allowed identification of seasonalchanges in suspended sediments and chlorophyll content,and defined the spatial relation of the chemical fertilizersinput from the lake tributaries with the water hyacinthplague that threatens to cause eutrophication of this waterbody.Mersel, Matthew K.Effects of Reach Averaging on Empirically-Based,Remotely-Sensed Estimates of River DepthMersel, Matthew K. 1 ; Smith, Laurence C. 1 ; Andreadis,Konstantinos M. 2 ; Durand, Michael T. 3, 41. Geography, UCLA, Los Angeles, CA, USA2. NASA Jet Propulsion Laboratory, Pasadena, CA, USA3. Byrd Polar Research Center, The Ohio State University,Columbus, OH, USA4. Earth Sciences, The Ohio State University, Columbus,OH, USAThe NASA Surface Water and Ocean Topography(SWOT) satellite mission, planned for launch in 2019, hasthe potential to greatly enhance our understanding of thespatial and temporal dynamics of rivers worldwide. Throughrepeat-pass measurements of water-surface elevation (WSE)and inundation width, SWOT will directly observe changesin flow for many of the world’s rivers (greater than ~100meters wide). However, because SWOT will only measurechannel bathymetry down to the lowest water levelencountered over the mission lifetime, true discharge willnot be directly measured and must thus be estimated.Perhaps the greatest limiting factor to accurate estimates ofriver discharge using SWOT measurements is the estimationof channel depth. An empirically-based method forestimating channel depth from synthetic SWOT retrievalsshows promise as a simple, yet effective method for remotelysensedriver depth approximation. The method exploits thederivatives of water-surface elevation and width in order toestimate average channel depth at “optimal” river locations.This approach, however, has previously been tested usingdiscrete datasets (i.e. cross-section datasets) that do not fullyrepresent the continuous type of data that SWOT willprovide. Using a gridded bathymetric dataset for the UpperMississippi River, we explore the extent to which thismethod for river depth estimation remains effective given amore complete knowledge of a river’s exposed channelgeometry (i.e. that portion of a river’s bathymetry that liesabove the water’s surface and is thus observable by SWOT).Furthermore, we explore the impact of reach-averaging ofremotely-sensed hydraulic variables (i.e. water-surfaceelevation and width) on this method. Initial results suggestthat reach-averaging of these variables up to approximately350m on the Upper Mississippi does not significantly reducethe accuracy of this depth estimation method.Miller, Norman L.Developing a High-Resolution Modeling andAssimilation Scheme for Terrestrial GroundwaterChangeMiller, Norman L. 1 ; Singh, Raj 1 ; Rubin, Yoram 21. Department of Geography, University of California,Berkeley, CA, USA2. Department of Civil and Environmental Engineering,University of California, Berkeley, CA, USATo date, remote sensed terrestrial water storage has beensuccessfully demonstrated and applied at scales of100,000km and coarser. However, water resource managersrequire much finer scales for monitoring local and basinscalechange. Hyper-resolution modeling at scales of 1kmand finer allows for significantly better representation of theeffects of spatial heterogeneity in topography, soils, andvegetation on hydrological dynamics. Such fine scale allowsfor the representation of processes that are sub grid to thecurrent generation of models, including slope and aspecteffects on surface incoming and reflected solar radiation, theeffects on snowmelt, soil moisture redistribution, andevapotranspiration. High-resolution models also enablebetter representation of channel processes and provide anindication of inundated areas, water depth in flooded areas,and indirectly the number of people impacted and criticalinfrastructure potentially at risk. In this study we develop aninnovative method for advancing high spatial resolutionsimulations of the terrestrial water budget with a particularfocus on terrestrial water storage variations through the useof new scaling arguments and assimilation of gravity data.The primary hypothesis is that the local water budget termscan be calculated with improved accuracy through theapplication of such scaling and assimilation methods. Wehave begun to use new methods to run the NCARCommunity Land Model version 4 (CLM4.0) at high (900m)and very high resolution (90m) for an east-west transect100

egion in Northern California that includes part of theCentral Valley and Sierra Nevada foothills and containsseveral wetlands. We use CLM4.0 results to initially quantifyand outline the effects of high-resolution model outcomesand to further develop improved hyper-resolution gravityassimilation for CLM4.0 at regional-to-local scales.Milly, Paul C.Use of Remotely Sensed Data to Advance GlobalHydrologic ModelingMilly, Paul C. 11. U.S. Geological Survey, Princeton, NJ, USASatellite remote sensing provides spatially extensiveobservations related to hydrologic processes, therebycomplementing ground-based observations. Consequently,remote sensing has potential to advance global hydrologicmodeling and, thence, global climate and earth-systemmodeling. Indeed, remotely sensed data have had substantialutility in the development of the “LM3” model of globalterrestrial dynamics of fluxes and storage of water, energy,vegetation, and carbon; LM3 represents the land areas of theearth in GFDL/NOAA climate models and earth-systemmodels. Remotely sensed data have played key roles in theparametric representation (“parameterization”) of keyhydrologic processes in the model and in the evaluation ofseveral aspects of model performance. Specifically, satellitebasedradiometry (Moderate Resolution Spectroradiometer,MODIS), gravimetry (Gravity Recovery and ClimateExperiment, GRACE), and altimetry(TOPEX/Poseidon/Jason) have contributed to enhancedphysical realism in LM3 of such processes and states as soilreflectance, ground water, soil water, snow pack, and lakelevels. These improvements are demonstrably contributingto improvements in global climate simulations.Mitchell, StevenBathymetric Polarization Lidar for HydrologicRemote Sensing ApplicationsMitchell, Steven 1 ; Thayer, Jeffrey 11. University of Colorado Boulder, Boulder, CO, USAA bathymetric, dual detection channel polarization lidartransmitting at 532 nanometers is developed forapplications of water characterization and depthmeasurement. The instrument exploits polarizationattributes of the probed water body to isolate andcharacterize surface and floor returns, utilizing constantfraction detection schemes to determine depth.Measurement of water depths upwards of 10 meters isexpected from a nominal 300 meter flight altitude. In theshallow water regime, the minimum resolvable water depthis no longer dictated by the system’s laser or detector pulsewidth and can achieve better than an order of magnitudeimprovement over current water depth determinationtechniques. In laboratory tests, a Nd:YAG microchip lasercoupled with polarization optics, dual photomultipliertubes, a constant fraction discriminator and a time to digitalconverter are used to target water depths of a simulatedsupraglacial melt pond. Water depth measurements asshallow as 1 centimeter with an uncertainty of ±3millimeters are demonstrated by the instrument.Additionally, simultaneous reception of co- and crosspolarizedsignals scattered from the target water bodyfacilitates measurement of depolarization, enablingdescription of surface and floor characteristics. This novelapproach enables new approaches to designing lidarbathymetry systems for water characterization and depthdetermination from remote platforms in support ofcomprehensive hydrologic studies.Mohanty, Binayak P.An Entropy based Assessment of Evolution ofPhysical Controls of Soil Moisture AcrossWatersheds in a Humid and Sub-Humid ClimateMohanty, Binayak P. 11. Biological & Agricultural Eng, Texas A & M Univ, CollegeStation, TX, USAPhysical controls of soil moisture, namely soil,vegetation, topography and precipitation control its spatialand temporal distribution. The influence of each of theseinterdependent physical controls evolves with time and scale.This study investigates the effect of three physical controlsi.e. topography, vegetation and soil over the Little Washitaand Walnut Creek watersheds in Oklahoma and Iowa,respectively. Point support scale data collected from four soilmoisture campaigns (SMEX 02, SMEX 03, SMEX 05 andCLASIC 07) was used in this analysis. The spatial variabilityof soil moisture and the effect of different physical controlson soil moisture was assessed using Shannon entropy. It wasfound that in Little Washita watershed, during wetconditions, topography is the dominant physical controlwhereas the dominance shifts to soil in dry conditions. Inthe Walnut Creek watershed, vegetation remained thedominant physical control with soil gaining dominanceunder certain specific wetness conditions. It was observedthat there exist specific moisture threshold conditions atwhich the dominant physical control changes fromvegetation to soil or from topography to soil depending onthe nature of heterogeneity present in the specific watershed.Using these findings and our previous studies related tophysical controls of soil moisture a new multi-scalealgorithm for soil moisture scaling has been developed.Results including field testing will be presented.http://vadosezone.tamu.edu101

Mohr, Karen I.Multi-scale observations and modeling of thehydrological dynamics of Andean peatbogsMohr, Karen I. 1 ; Slayback, Daniel 2, 3 ; Yager, Karina 4, 3 ; Tucker,Compton J. 5 ; Mark, Bryan 6 ; Seimon, Anton 71. Mesoscale Atmospheric Processes Laboratory, NASA-GSFC, Greenbelt, MD, USA2. Science Systems & Applications, Inc., Greenbelt, MD,USA3. Biospheric Sciences Laboratory, NASA-GSFC, Greenbelt,MD, USA4. NASA Post-Doctoral Program, NASA-GSFC, Greenbelt,MD, USA5. Earth Sciences Division, NASA-GSFC, Greenbelt, MD,USA6. Byrd Polar Research Center and Department ofGeography, Ohio State University, Columbus, OH, USA7. Wildlife Conservation Society, New York, NY, USANinety percent of the Earth’s tropical glaciers arelocated in Peru and Bolivia, and these glaciers provide a keyresource to regional pastoral agricultural systems thatsupport large Andean populations. Meltwater from theglaciers and seasonal precipitation sustain numerous alpinepeatbogs that provide critical year-round islands ofnutritious forage for livestock. We have documented a 30%recession in Peruvian and Bolivian glaciers over the past 20years. The potential for significant changes in the glacialcontribution to regional runoff may directly affect thesustainability of these peatbog systems. This is the firstattempt to link observed changes in glacial runoff due toclimate change to future regional pastoral agriculturalproductivity. We have recently begun a NASA-funded projectto document and model the behavior of these peatbogsystems. We seek to learn how the water balances in peatbogsand therefore pastoral agriculture in this region may beaffected by glacier recession due to climate change. We willuse ground observations of precipitation, streamflow, andisotopic analyses of peatbog and stream waters bothhistorical and from our own observing network to documentthe water balances of selected peatbogs. These water balancesand satellite-observed changes in glacial recession will formthe baseline for modeling of the surface hydrology of thisregion. We will impose expected climate change scenarios ona hydrological modeling framework based on the NASA-Goddard Land Information System (LIS), a multi-scale,multi-model hydrologic prediction and data assimilationsystem that runs on NASA’s high performance computers.Predicted interseasonal and interannual changes in peatbogextents will be used to estimate changes in forageproduction. Our presentation shows the evidence forchanges in glacial recession from satellite data and the set-upand initial observations from our hydrological observingsystems in multiple peatbogs in a variety of microclimates inthe region.Moller, DelwynInitial Evaluations of SWOT Water SurfaceElevation Retrievals Using a High-Fidelity DynamicSimulatorMoller, Delwyn 1 ; Rodriguez, Ernesto 2 ; Andreadis,Konstantinos 21. Remote Sensing Solutions, Sierra Madre, CA, USA2. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USAThe Surface Water Ocean Topography (SWOT)mission’s key payload, the Ka-band radar inteferometer(KaRIN), is capable of high-resolution wide-swath altimetryof both the ocean surface and terrestrial surface water. Theability to observe and monitor the volume of water storedand flowing in rivers, lakes and wetlands globally is ofparamount importance yet surface water is poorly observedeven in the industrialized world and observations are almostcompletely lacking elsewhere. For terrestrial hydrology,SWOT will provide the key hydrologic variables needed forcomprehensive river discharge and storage observations;specifically maps of temporal height change, slope and thespatial extent of surface water. To support pre-missionactivities and development, we have developed a SWOTinstrument simulator which mimics the interaction of theKaRIN’s transmitted electromagnetic wave with thetopography below. This simulator allows for the predictionand assessment of layover impact, water temporaldecorrelation performance implications and the impact oftropospheric delay and precipitation. It also provides a toolfor development and test of calibration and classificationalgorithms. In this paper we use a KaRIN instrumentsimulator to provide realistic and dynamic syntheticobservations over a study region of the Ohio river. This isachieved by integrating the simulator with a high spatialresolution hydrodynamic temporal model of the Ohio studyregion. The result is a high fidelity assessment of theperformance of the height (and thus slope) andclassification (and thus river width) reconstruction we canexpect during the SWOT mission. Specifically, the KaRINsimulator is used to generate synthetic observations with atemporal and spatial sampling identical to that whichSWOT would generate. Derivation of height, slope andwidth from the interferograms are demonstrated. Beyondthis we illustrate how the swath measurements frommultiple passes overlay to create a synoptic view of theregion. Included in this assessment is the impact oftopographic layover on the accuracy of the estimatedelevations and rudimentary land/water classification as afirst order measure of performance. The results illustrate thestrengths of the KaRIN data to provide two-dimensionalriver discharge maps at fine (~100m) resolution. In thefuture, we will extend these results to encompass a basinscalestudy over seasonal time-frames. We will also furtherrefine classification algorithms and their sensitivity toeffects of temporal decorrelation in addition to backscattervariability and contrast.102

Moller, DelwynTopographic Mapping of the Water Surface usingAirborne Millimeter-Wave InterferometryMoller, Delwyn 1 ; Rodriguez, Ernesto 2 ; Hensley, Scott 2 ; Wu,Xiaoqing 2 ; Carswell, James 11. Remote Sensing Solutions, Sierra Madre, CA, USA2. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USAThe surface water and ocean topography (SWOT)mission, slated for launch in 2019, has a need for an airbornesensor to support pre-mission phenomenologymeasurements and mission calibration and valibration(cal/val). SWOT is unique and distinct from precursor oceanaltimetry missions in some notable regards: 1) 100km+ ofswath will provide complete ocean elevation coverage, 2) inaddition the land surface water will be mapped for storagemeasurement and discharge estimation and 3) Ka-bandsingle-pass interferometry will produce the 2-D water surfaceelevation (WSE) maps. Some initial Ka-band interferometricdata was collected in April 2009 by the NASA/JPL Glacierand Ice Surface Topography Interferometer (GLISTIN-A)onboard the NASA Gulfstream III over surface-water targetsin North Dakota. These data served as a preliminaryvalidation of near-nadir Ka-band interferometry over inlandwater bodies, and were instructive for refining the processingand calibration methodology. However, while ideal for a theice topography mapping application, the combination ofsensor geometry, bandwidth and number of channels neededfor SWOT cal/val cannot be met within the framework ofGLISTIN-A. To address SWOT’s cal/val requirements, theKa-band SWOT Phenomenology Airborne Radar (KaSPAR)builds upon GLISTIN-A heritage and is the primary payloadof the AirSWOT program. KaSPAR is a unique system withmultiple temporal and cross-track baselines to fullycharacterize the scattering and statistics expected fromSWOT, provide data for developing classification algorithms,and understanding instrument performance over the vastvariety of scenes that SWOT will encounter. Furthermore a>5km swath high-accuracy WSE mapping capabilityprovides the framework to translate traditional point orprofile measurements to the spatial framework that SWOTwill measure. Specific measurements from the integratedAirSWOT assembly are: 1. WSE maps over a 5km swath andsub-3cm mean error at 100m x 100m postings (for oceansurface at 6m/s wind speed) 2. 2-D slope maps – as derivedfrom the height maps. 3. shoreline delineation at 10mresolution Each of these measurements will be made atresolutions exceeding that of SWOT to better characterizecorrections or limitations for the spaceborne sensor.Molnia, Bruce F.Global Fiducials Program Remote Sensing of theCold Regions Terrestrial Water CycleMolnia, Bruce F. 1 ; Price, Susan D. 1 ; Angeli, Kim M. 1 ; Duke,Thomas M. 1 ; Chandler, Lisbeth A. 1 ; Manuel, Gregory A. 11. Global Fiducials Program, U. S. Geological Survey,Reston, VA, USANew and emerging satellite missions may produce aclearer synoptic picture of Earth’s hydrosphere than haspreviously been available. However, a little known remotesensing program is already providing some of the highestresolution geospatial imagery time series of sensitive anddynamic cold regions terrestrial hydrological sites ever madeavailable for study of the water cycle and the cryosphere.These sequential satellite imagery time series are collected byU.S. National Imagery Systems sensors for the GlobalFiducials Program (GFP). They provide valuable insightsinto Earth processes and changes taking place at about 300locations on Earth. The collection and interpretation ofthese decadal time series of images from carefully selectedlocations enhances our ability to observe and understandEarth’s dynamic processes and to determine long-termtrends, impacts, and changes. More than one-third of thenearly 300 locations focus on the terrestrial hydrosphere.About one-half of these characterize dynamic aspects of thecold regions terrestrial water cycle. Since 2008, more than4,300 one-meter resolution electro-optical (EO) imageswhich comprise time series from more than 80 GFP siteshave been released for unrestricted public use. In time,imagery from all of the remaining sites will be madepublically available. Initial site selections were made byFederal and academic scientists based on each site’s uniquehistory, susceptibility, or environmental value. For each site,collection strategies were carefully defined with specificrepeat intervals and image characteristics to maximizeinformation extraction capabilities. This consistency ofimagery parameters and acquisition history enhances ourability to understand Earth’s dynamic processes andcharacterize long-term trends. In the ‘cold regions,’individual time series focus on many cold region hydrologicprocesses including: polar lakes; Arctic permafrost; polar andtemperate glaciers; Arctic tundra vegetation and hydrologicprocesses; and Antarctic ‘Dry Valley’ surface processes. One‘cold region’ time series focuses on Arctic coastal sea ice andits terrestrial impacts in the Barrow, Alaska area, while other‘cold region’ time series monitor the dynamics of sea ice atsix fixed Arctic Ocean locations, and the movement ofdrifting Arctic sea ice throughout the Arctic summer. TheCivil Applications Committee (CAC), operated by the U.S.Geological Survey (USGS) on behalf of the Secretary of theInterior, is the Federal interagency committee that facilitatesFederal civil agency access to U.S. National Imagery SystemsEO imagery for natural disaster response; global changeinvestigations; ecosystem monitoring; mapping, charting,and geodesy; and related topics. GFP imagery is archived inthe Global Fiducials Library (GFL), maintained by the USGSin Reston, Virginia. There, it is available for on-going and103

future scientific analysis and research conducted to supportpolicymakers and Federal civil agency missions to inform thepublic. Publically released imagery can be downloaded andfreely used and distributed (source URLs are: gfl.usgs.govand gfp.usgs.gov). Released images are orthorectified andprovided in a GeoTIFF format with supporting metadata.gfp.usgs.gov and gfl.usgs.govMolotch, Noah P.Remote Sensing of the Mountain Snowpack:Integration of Observations and Models toSupport Water Resource Management andEcosystem ScienceMolotch, Noah P. 1, 2 ; Guan, Bin 2 ; Durand, Michael 3 ; Dozier,Jeff 41. Geography / INSTAAR, Univ of CO-Geological Sciences,Boulder, CO, USA2. Jet Propulsion Laboratory - CAL TECH, Pasadena, CA,USA3. Earth Sciences, The Ohio State University, Columbus,OH, USA4. Donald Bren School of Environmental Science andManagement, University of California, Santa Barbara,CA, USAThe impacts of climate change on water sustainability inmountainous regions is inherently linked to changes inmountain snow accumulation and snowmelt timing whichsustains agricultural and municipal water demands for 60million people in the U.S. and one billion people globally.Hence, accurate estimates of the volume of snowpack waterstorage are critical for supporting water resource planningand management. While snow extent is one of the earliestobserved land surface variables from space, hydrologicapplications of these data have been limited as the variableof interest for water management is snow water equivalent(SWE) which is not remotely observable at the fine-scaleresolution needed in the mountains. Since the early 1980’s,several works have illustrated the connection between runoffvolume and snow cover depletion patterns as observed fromsatellite. In this regard, we present a series of experimentswhich illustrate that patterns of snow cover depletion can becoupled to spatially distributed snowmelt models toreconstruct the spatial distribution of SWE. In this regard,we present a proof-of-concept for a global product, providingdaily estimates of snow water equivalent at 500-m scale forthe observation record of the Moderate Resolution ImagingSpectroradiometer (MODIS). Estimates of the reconstructedSWE are validated against observed SWE from extensivesnow surveys across the Sierra Nevada and Rocky Mountainswith adequate spatial sampling, and compared to theoperational Snow Data Assimilation System (SNODAS)SWE product produced by the U.S. National WeatherService. Snow survey SWE is underestimated by 4.6% and36.4%, respectively, in reconstructed and SNODAS SWE,averaged over 17 surveys from sites of varying physiography.Corresponding root-mean-square errors are 0.20 m and 0.25m, respectively, or 2.2 and 2.6 mean standard deviation ofthe snow survey SWE. Comparison between reconstructedand snow sensor SWE suggests that the current snow sensornetwork in the U.S. inadequately represents the domain SWEdue to undersampling of the mid-lower and upperelevations. Correlation with full natural flow is better withreconstructed SWE than with ground-based snow sensors, orwith SNODAS SWE on average; particularly late in thesnowmelt season after snow stations report zero values butsnow persists at higher elevations. These results indicate thatinclusion of remotely sensed snow cover depletion patternsdramatically improves estimates of snow distribution inmountainous regions. Example applications for improvingwater resource management and understanding ecosystemresponse to water availability will be shown.http://instaar.colorado.edu/mtnhydroMonsivais-Huertero, AlejandroOptimal use of active/passive microwaveobservations at L-band for improving root zone soilmoistureMonsivais-Huertero, Alejandro 1 ; Judge, Jasmeet 2 ; Nagarajan,Karthik 21. ESIME Ticoman, Instituto Politecnico Nacional, MexicoCity, Mexico2. Department of Agricultural and Biological Engineering,University of Florida, Gainesville, FL, USAAccurate knowledge of root zone soil moisture (RZSM)is crucial in hydrology, micrometeorology, and agriculturefor estimating energy and moisture fluxes at the landsurface. Soil Vegetation Atmosphere Transfer (SVAT) modelsare typically used to simulate energy and moisture transportin soil and vegetation. Although SVAT models capture thebiophysics of dynamic vegetation fairly well, RZSM estimatesstill diverge from reality due to errors in computation. Thus,uncertainties in model parameters, forcings, and initialconditions should be considered. The model estimates ofRZSM can be significantly improved by assimilatingremotely sensed observations that are sensitive to soilmoisture changes, such as microwave brightness andbackscatter at frequencies < 10 GHz.. For soil moisturestudies, observations at L-band frequencies of 1.2 – 1.4 GHzare desirable due to larger penetration depth and systemfeasibility. The near-future NASA Soil MoistureActive/Passive (SMAP) mission will include active andpassive microwave sensors at L-band (1.2 – 1.4 GHz) toprovide global observations, with a repeat coverage of every2-3 days [3]. In this study, an Ensemble Kalman Filter(EnKF)-based assimilation algorithm was implemented tosimultaneously update states and parameters every 3 days,matching the interval of satellite revisit, by assimilating L-band microwave brightness temperature (TB) andbackscattering coefficient (sigma0) into the SVAT modellinked with a forward active/passive (AP) microwave model.We use a Land Surface Process (LSP) model to estimate theSM profile and ST profile and an AP model to estimate TBand sigma0 during bare soil conditions in an agriculturalfield located at North Florida. Field observations were104

obtained from the Fifth Microwave Water and EnergyBalance (MicroWEX-5) experiment which was conductedduring the growing season of sweet-corn from Day of Year(DoY) 68 (March 9) to DoY 150 (May 30) in 2006. In situ soilmoisture observations were obtained every fifteen minutesat depths of 2, 4, 8, 16, 32, 64, and 120 cm and L-bandbrightness temperature observations at H-polarization and50° incidence angle were measured every fifteen minutes.Comparisons of RZSM estimates using both synthetic andfield observations during the MicroWEX-5 experiment wereconducted to understand the improvement in RZSMestimation using both in situ and remotely sensedmeasurements. The performances of the algorithm werecompared by assimilating both H and V polarizations ofmicrowave observations for passive, and VV and HHpolarizations for active observations. When assimilatingsynthetic observations, the mean estimates of VSM05cmand RZSM improved up to 80%, 50%, and 90%, as comparedto the open-loop estimates, when passive, active, and APobservations were assimilated, respectively. However, themeans decreased to 10%, when assimilating fieldobservations of TB,h from the Fifth Microwave Water EnergyBalance Experiment (MicroWEX-5), suggesting other sourcesof uncertainty that those from model parameters andforcings.Monsiváis-Huertero, AlejandroSOIL MOISTURE FIELD MEASUREMENTS:THEVALIDATION PROCESS USING MICROWAVEREMOTE SENSINGRamos Hernandez, Judith G. 1 ; Monsiváis-Huertero,Alejandro 2 ; Marrufo, Liliana 11. Hidraulica, Instituto de Ingenieria, Distrito Federal,Mexico2. Aeronautica, Instituto Politecnico Nacional, DistritoFederal, MexicoThe estimation of soil moisture (ms) is a key variable inthe large-scale fluxes of energy and water interchange in thesoil-vegetation-atmosphere transfer system (SVAT). mspresents a space and temporal variation, that is crucial whencatchment analysis are required. This variable is influencedby the same hydrological cycle processes, the vegetation andthe edaphologyical and topography aspects and also vary intime and space. Although there are several methods todetermine ms, the majority of them are looking to one ortwo of these aspects. In situ ms observations could beobtained applying direct and indirect methods such asgravimetric, lysimeters, tensiometers and reflectrometry (i.eTime or Frequency Domain Reflectometry). However, in thelast decades, the remote sensing techniques (RS) allows theidentification of several surface characteristics. In particular,the active (radar) microwave sensors that are sensitive to thedielectric properties of a surface as well as the ms. Thus, it ispossible to find a relationship between the totalbackscattering coefficient from the radar image (°total)and the soil moisture at the surface (msfm). One of thecommonly used formulations to estimate these scatteringmechanisms is the Radiative Transfer Theory (RTT), whichproposes an iterative method to solve the scattered energyequations at upward and downward directions (i.e. MichiganMicrowave Canopy Scattering Model). In this paper, ms wasestimated using radar remote sensing (ENVISAT imagery)and the MMICS method and the validation was achieved byapplying the FDR method on a tropical climate. The studyarea is the Zapotes riparian wetland. The measure sitesdesign was subject to the accessibility in the field. Eight siteswere defined and tested in two campaigns, seven of them areshowed in Table 1. The implementation of radar imagery(2010) using the MIMISC models provides a relationship(Table 2) that for all cases have a correlation coefficient (R2)higher than 0.99 with an error of 0-5% in comparison to insitumsfm observations.Table 1. Soil moisture (ms) measureds at 10 cm depthTable 2. Empirical models for each site of the Zapotes wetlandMoradi, AyoubMulti-sensor study of hydrological changes inCaspian SeaMoradi, Ayoub 1, 2 ; Viron, Olivier D. 1, 2 ; Metivier, Laurent 21. Earth Sciences, University of Paris Diderot, Paris, France2. Spatial Geophysics and planetary, Paris Institut ofPhysics of Globe, Paris, FranceThe main purpose of this study is to determine howgeodetic and remote sensing data can be combined togetherin order to better monitor the hydrological processes in aclosed large water bodies like Caspian Sea. The usedobservation techniques are principally different, with theirown benefits and disadvantages. Combining heterogeneousinformation aims at improving our knowledge on the realityof hydrological processes, also to determine, and possiblycorrect, the shortages of different methods. We used timeseries of 3 kinds of dataset, Altimetry, Gravimetry andRemote Sensing data (table below). We reached the trends ofchange of water level and change of total water mass usingaltimetry and gravimetry data respectively. Using MODIStime series we detected changes of snow, grass andvegetation cover in the Caspian basin entirely and changes ofwater extent of the lake (the image is an example forclassification). Altimetry and gravimetry results show anannual change about 35 centimetres and an interannualchange about 70 centimetres in water height from year 1992to present. Interannual changes of water would be verified bychanges in snow cover over the basin. After removing leakageaffect on the gravimetry results the comparison shows a fairconsistency between the altimetry and gravimetry results.105

But this is not confirmed by remote sensing data, thoseresults seem to be out of phase with the change of shoreline,in the other word in a given year the time of peak andbottom of the water level and mass is not coinciding withprogression and regression of water into the land, whichseems to indicate that an increase in water extent of CaspianSea is not directly linked to the water elevation and mass; themismatch might be caused by change in convexity of watersurface.Data Used ListMajor dataset, (GIS layers are not mentioned here)Moran, Thomas C.Comparing annual evapotranspiration estimatesderived from remote sensing and surfacemeasurement for water-limited catchments inCaliforniaMoran, Thomas C. 1 ; Hahn, Melanie 1 ; Agarwal, Deb 2 ; vanIngen, Catharine 3 ; Baldocchi, Dennis D. 1 ; Hunt, James R. 11. University of California, Berkeley, CA, USA2. Lawrence Berkeley National Laboratory, Berkeley, CA,USA3. Formerly of: Microsoft Bay Area Research Center,Microsoft Research, San Francisco, CA, USAQuantifying the partitioning of precipitation intoevapotranspiration (ET), surface runoff, and othercomponents is a long-standing goal of the hydrologicsciences given its importance to ecosystems and watermanagement. In particular, the challenges of accurateestimation of ET include direct measurement of water vaporfluxes, spatial heterogeneity, and uncertainty in thecontrolling processes. As a consequence, this is an active areaof research with various approaches. An increasing numberof eddy covariance flux towers provide reliable pointmeasurements of ET that are used to validate or calibrateother methods. At the catchment scale, a water balance canbe applied to estimate net ET. When rainfall, surface runoff,and subsurface components are well-characterized, ET canbe estimated with quantifiable confidence. Satellite remotesensing offers the promise of near real-time global ETestimates with spatial resolution near 1 sq km. To fullyrealize the potential of this approach, we must describe itsaccuracy and applicability in addition to its many benefits.Our research group has processed water balance data formore than one thousand catchments in California usingprecipitation and streamflow records that span more than acentury. From this data set, a subset of over 100 catchmentsare sufficiently well-characterized so that estimation ofannual ET depth takes on the straightforward form ET = P -R, where P and R denote precipitation and runoff depth,respectively. This simplification is justified by the distinctwet and dry seasons of California’s Mediterranean climate,and it is supported by limited changes in groundwaterstorage from year to year. The study catchments cover thediversity of California climate zones and the data yearsinclude extreme variations in precipitation. These waterbalance estimates of annual ET are compared with fluxtower measurements to establish consistency between thetwo methods. We then examine remotely-sensed ET datafrom three independent research groups: the GlobalEvapotranspiration project at the University of Montana(Zhang, et al., 2009, WRR, doi:10.1029/2009WR008800); thenear-real-time global evapotranspiration data product fromthe University of Washington (Tang, et al., 2009, JGR,doi:10.1029/2008JD010854) and the Breathing Earth SystemSimulator model from UC Berkeley (Ryu, et al., GlobalBiogeochemical Cycles (in review)). In particular, we focus onthe performance of these remotely based estimates forconditions when annual ETxs is limited by water availability,106

a constraint that is observed spatially and temporally in thestudy catchments. The water balance method implicitlyaccounts for rainfall variability that may not be reflected inremote estimates. We investigate consistency among theseestimates, and compare them with the water balance andflux tower results. The observed strengths and limitations ofeach approach are described, and potential improvementsare explored.Mukherjee, SaumitraHeliophysical and cosmic ray fluctuation changeshydrological cycleMukherjee, Saumitra 11. School of Environmental sciences, Jawaharlal NehruUniversity, New Delhi, IndiaAny phenomena that produce a change in thehydrological cycle are manifested by the changes in theterrestrial environment. Besides anthropogenic activities thechanges in the Sun and extragalactic cosmic ray intensityalso influence the hydrological cycle which is playing a majorrole in climate change. Sun-Observatory-HeliosphericObservatory (SOHO) satellite data shows a low electron fluxand planetary indices and high cosmic ray intensity in earthspecific region. Space Environment Viewing and AnalysisNetwork (SEVAN) are being installed in different latitude ofthe world to quantify the changes in the hydrological cycle ofnature to infer the climate change. Using terrestrial remotesensing (LANDSAT,IRS data) and extra terrestrial remotesensing (SOHO and Cosmic ray data) it will be possible topredict the hydrological cycle based environmentalperturbations.http://www.jnu.ac.in/Faculty/smukherjeeMuñoz Barreto, JonathanCREST-SAFE: The CREST-Snow Analysis and FieldExperimentMuñoz Barreto, Jonathan 1 ; Lakhankar, Tarendra 1 ; Romanov,Peter 1 ; Powell, Alfred 2 ; Khanbilvardi, Reza 11. NOAA-CREST Institute, The City College of New York,New York, NY, USA2. NOAA/NESDIS/STAR, Camp Spring, MD, USAThe characterization of intra-seasonal variations ofsnow pack properties is critical for hydro-meteorologicalapplications. The CREST-Snow Analysis and FieldExperiment (CREST-SAFE) is being carried out to collect thelong term intra-seasonal microwave and surface observationsto analyze the snow transitional period from dry, wet, and tomelting snow conditions. CREST-SAFE is setup in thebackyard of the National Weather Service office at Caribou,ME (46:052:59N, 68:01:07W) using high frequency (37 and89 GHz), dual polarized microwave radiometers to develop,improve and validate the snow retrieval algorithms. Inaddition to microwave radiometers, the field experiment siteis equipped with snow pillows (to measure Snow WaterEquivalent), ultrasonic snow depth sensor, infra-redthermometers (for snow skin temperature), net radiationsensors, snow temperature profiler (measures temperature atevery 5 cm of snow layer) and network camera for real timeremote monitoring of the site. As well, measurements ofsnow grain and density are collected throughout the winterseason. In this presentation, we will discuss about fieldexperiment details, and preliminary observations. Theseasonal behavior of measured snow depth, temperature,snow grain size on the brightness temperature measuredfrom 37 and 89 GHz radiometer will be presented. Thesensitivity of fresh and aged snow over the microwaveemission will be discussed. During early spring periods, weobserved larger diurnal variation in brightness temperaturedue to cold nights and the warm days (> 0 degrees) thatcausing wet snow and freezing snow.http://crest.ccny.cuny.edu/Murazaki, KazuyoDiscrimination Between Rain and Snow in JapanWith an Operational Conventional C-band RadarNetworkMurazaki, Kazuyo 1 ; Yamada, Yoshinori 11. Forecast Research Department, Meteorological ResearchInstitute, Tsukuba, Ibaraki, JapanRemote delineation of the transition region betweenrain and snow is of great importance because these twoprecipitation types have vastly different yet significant socialand hydrological impacts in the regions of occurrence.Forecasts of the expected location of rain–snow boundariesare somewhat elusive and often based on incomplete orinadequate climatological-experimental information.Knowledge of the exact location of the rain–snow boundaryis also necessary to accurately determine the precipitationamounts. Recent studies have shown that dual-polarizedradar is useful to discriminate between rain and snow and tolocalize the boundary zones (e.g. Ryzhkov and Zrnic, 1998).Although radar polarimetry has proved useful to classifyhydrometeors of different types, there are a number ofoperational conventional-weather radars that do not havedual-polarized capabilities in the world. Here, we report amethod to discriminate between rain and snow by use of thedata obtained from an operational network of conventionalC-band radar operated by the Japan Meteorological Agency(JMA). The radar network data that covers Japan area inwinter in 2008-2009 were used in the present study. TheConstant Altitude Plan Position Indicator (CAPPI) data weremade from the radar reflectivity data at altitudes of 1 kmand 2 km with horizontal and time resolution of about 1 kmand 10 minutes, respectively. More than 10 snow and rainevents are selected and analyzed. The data of rain gaugeslocated nearest to the radar grid were used for thecomparison. Moreover, radiosonde and wind profiler datawere also used in the analysis. Results show that thedifference in reflectivity (dbZ) between 1 km and 2 km tendsto take minus values in snow case and takes plus values inrain. Further analysis indicates that reflectivity at 2 km inrain takes large values because the so-called bright bands areoften included within the radar beam sampling volumes at107

this altitude. On the other hand, the reflectivity at 1 km insnow case takes large values because there is no bright bandand snowflakes are mostly formed at altitudes less than 2km in convective clouds, whose height is very low in winter.We also found that this method is hard to apply in the areawith large clutters including over the ocean.Nagarajan, KarthikAn Observing System Simulation Experiment forEvaluating Scaling Algorithms Under DynamicLand Cover Conditions for Soil MoistureApplicationsNagarajan, Karthik 1 ; Judge, Jasmeet 11. University of Florida, Gainesville, FL, USAThe availability of soil moisture products from therecent Soil Moisture and Ocean Salinity (SMOS) missionand the forthcoming Soil Moisture Active Passive (SMAP)mission will enable new research in hydrology, agriculturalproductivity, and water resources management by providingsoil moisture information at global scales. While SMOS iscurrently providing soil moisture information at a spatialresolution of ~45km, the SMAP mission will provide aderived soil moisture product at ~9km by combininginformation from the active and passive sensors. Either insitu soil moisture measurements at field scales (typically200m) have to be upscaled to match these derived productsor the products have to be downscaled to field scales toevaluate their accuracy and to study the impact of sub-pixelsoil moisture variability caused due to land surfaceheterogeneity, climatic variability, and dynamic vegetationwithin the satellite footprint. Unfortunately, a dense networkof field measurements is typically unavailable under thesatellite footprint to evaluate the derived products or thescaling algorithms. An effective alternative is to develop anObserving System Simulation Experiment (OSSE) forsimulating soil moisture observations at satellite and fieldscales, by embedding various factors that contribute tospatio-temporal dynamics in soil moisture. In the presenceof agricultural fields within the satellite footprint,vegetation dynamics over growing seasons of crops, landmanagement, and precipitation events have been found topredominantly control the intra-seasonal soil moisturespatial structure. In this study, an OSSE framework wasdeveloped for simulating root-zone soil moisture (RZSM) atmultiple scales under heterogeneous land cover and dynamicvegetation and climatic conditions. Simulations weregenerated over an area of 50kmx50km in North CentralFlorida for land covers comprising of growing sweet-cornand cotton at resolutions of 200m and 10km, the formerrepresentative of agricultural fields and the latter that of aSMAP soil moisture pixel. Maximum differences of0.0320.055 m3/m3 in RZSM were observed betweenestimates obtained over vegetated and bare soil regionsduring precipitation and dry conditions, respectively. Thesignificance of the multi-scale OSSE simulations were alsodemonstrated by, a) Evaluating a novel upscaling algorithmdeveloped using information theory, against existingmethods based upon averaging and kriging and b)Evaluating a probabilistic technique of estimating RZSM at200m from auxiliary remote sensing products such as, landsurface temperature (LST), leaf area index (LAI), and landcover (LC), available from MODIS at spatial resolutions of 1km. The OSSE framework is a valuable contribution to theremote sensing community as it can be used for otherstudies that require synthetic observations of soil moisture,soil temperature, and crop growth under heterogeneous landcover conditions at multiple scales.Nakayama, TadanobuCoupling with satellite data and eco-hydrologymodel for evaluation of two extremes incontinental scaleNakayama, Tadanobu 1, 21. Center for Global Environmental Research, NationalInstitute for Environmental Studies, Tsukuba, Japan2. Process Hydrology Section, Centre for Ecology &Hydrology, Wallingford, United KingdomThe study area includes Changjiang and Yellow Riverbasins in China, where hydro-climate is diverse betweennorth and south. Semi-arid north in Yellow River is heavilyirrigated and combination of increased food demand anddeclining water availability is creating substantial pressures,whereas flood storage ability around lakes in ChangjiangRiver has decreased and impact of Three Gorges Dam (TGD)on flood occurrence in the downstream against originalpurpose is increasing problem. Further, China is nowaccelerating South-to-North Water Transfer Project(SNWTP), to compensate imbalance of water resources.Therefore, it is effective to evaluate optimum amount oftransferred water, socio-economic, and environmentalconsequences in both basins. Here process-based NationalIntegrated Catchment-based Eco-hydrology (NICE) model(Nakayama, 2008a, 2008b, 2010, 2011a, 2011b; Nakayamaand Fujita, 2010; Nakayama and Hashimoto, 2011;Nakayama and Watanabe, 2004, 2006, 2008a, 2008b;Nakayama et al., 2006, 2007, 2010, 2011), which includessurface-unsaturated-saturated water processes andassimilates land-surface processes with satellite datadescribing phenology variation, was coupled with complexsub-systems in irrigation, urban water use, stream junction,and dam/canal, in order to develop coupled human andnatural systems and to analyze impact of anthropogenicactivity on eco-hydrologic change in continental scales.Furthermore, spatial pattern of Time-Integrated NormalizedDifference Vegetation Index (TINDVI) gradient inagricultural fields was analyzed from satellite NDVI imagesin NOAA/AVHRR (Advanced Very High ResolutionRadiometer). Based on the relation between this gradientand the trend in crop yield, the satellite information showedheterogeneous characteristics of crop yield and implied theincrease in irrigation water use is one of the reasons for theincrease in crop production. Coupling with thisinformation, the model presented impact of groundwaterover-irrigation on eco-hydrological processes including108

groundwater degradation, seawater intrusion, and decreasein crop productivity, was predominant in the lower of northbecause surface water was seriously limited. In the south,large-scale flood and consequent severe damage includingdecrease in crop production were related to lake reclamationand storage decrease in shrinking lakes. Hydrologic cycleafter TGD and SNWTP was predicted to clarify whetherdilemmas between water stress, crop productivity, andecosystem degradation would diminish. This integratedapproach of coupling with satellite data and eco-hydrologymodel helps clarify how the substantial pressures of thecombinations of increased food demand and declining wateravailability can be overcome, and how effective decisions canbe made for sustainable development in continental scale.Nde, Ngwa J.Geospatial Analysis of Surface Water Pollutionfrom Automobile Waste in Ife Central, NigeriaNde, Ngwa J. 1 ; Orimoogunje, Orimoogunje 21. GIS, GeoSpace consultancy, Bamenda, Cameroon2. Geography, Obafemi Awolowo University, Ile Ife, NigeriaThe study was designed to identify water pollutant fromautomobile waste in Ife Central. It also mapped and modelwater pollution generated from automobile engineeringwaste in the study area using DTM. This was with a view topropose land suitability model for Automobile EngineeringWorkshops and waste disposal site for Ife Central LocalGovernment area. The study made use of both primary andsecondary data in order to achieve the stated objectives forthe study. Questionnaires were randomly administered in aface to face situation at different locations by the researcher.In all, forty-one people were interviewed. The data gatheredhas a specific focus on gathering information aboutAutomobile Engineering Workshops, waste production,treatment and disposal in the environment and impact tohuman health. Water and waste samples were also randomlycollected for laboratory analysis. The datasets were analyzedusing ERDAS Imagine, ArcGIS, AutoCAD Map 3D and MSOffice. The observed changes were mapped and the resultsof the classification were prepared in different themes in GISmode using ArcGIS. SPSS techniques were used to analyzethe data generated in order to produce tables and figures.The results show that the rivers close to automobileworkshops in the study area are highly polluted. Thetemperature, pH and Electrical Conductivity were found in arange of 25.22 – 25.3, 6.13-6.92 and 207-410 respectively forwater samples only. Pb, Cu and Mn concentrations for allsamples analyzed using Atomic AbsorptionSpectrophotometer also varies and range from 0 -0.055mg/L. The results also shows that Scraps, Black oil,Antifreeze and Lead acid battery are the main wasteproduced in the area with 31.71%, 29.27%, 9.76% and 9.76%respectively. The study concluded that there is need to bringin GIS to mitigate this spatial problem while the authoritiesshould create a suitability automobile workshop and wastedisposal site base on the results of this study.http://www.4shared.com/file/buobEvsn/Paper_-_Geospatial_Analysis_of.htmlNeal, Jeffrey C.A simple hydraulic model for wide area inundationmodeling in data sparse areasNeal, Jeffrey C. 1 ; Schumann, Guy J. 1 ; Bates, Paul D. 11. School of Geographical Sciences, Univ Bristol, Bristol,United KingdomThe simulation of floodplain inundation and wavepropagation in large rivers systems requires computationallyefficient hydraulic models that can be applied to locationswhere limited or no ground based data are available. Thisrequires the development of new models that can be built,calibrated and evaluated using only remotely sensed data onreaches where channel depth and discharge are typicallyunobservable. Much research effort has been expended onmeasuring the dynamics of water surface elevations,gradients and extents from remote sensing using altimetryand imagery, which might be assimilated with such models.However, widely available floodplain elevation data sets, suchas SRTM, may be corrupted by vegetation artifacts and mustbe averaged over large areas to reduce noise. This, along withcomputational constraints, necessitates the use of modelswith grid resolutions larger than many of the river channelsthat control connectivity and flow conveyance. For thesereasons, traditional reach scale approaches to hydraulicmodeling that rely on detailed river survey data are not easilyapplied over large data sparse areas. Furthermore, existingglobal river routing schemes that use kinematic wave modelsare unable to simulate backwatering and floodplaininteractions that may be key controllers of wave propagationin large rivers. We present a gridded two-dimensionalhydraulic model with a parameterised sub-grid scalerepresentation of the 1D channel network that can be buildentirely from remotely sensed data to addresses these issuesfor the first time. For both channel and floodplain flows themodel simulates a simplified shallow water wave using anexplicit finite difference scheme, which was chosen becauseof its computational efficiency relative to both explicitdiffusive and full shallow water wave models. The model wasapplied to an 800 km reach of the River Niger that includesthe complex waterways and lakes of the Niger Inland Deltain Mali. This site has the advantage of having no or lowvegetation cover and hence SRTM represents (close to) bareearth floodplain elevations. Floodplain elevation wasdefined at 1 km resolution from SRTM data to reduce pixelto-pixelnoise, while the widths of main rivers andfloodplain channels were estimated from Landsat imagery.The channel bed was defined as a depth from the adjacentfloodplain from hydraulic geometry principles using a powerlaw relationship between channel width and depth, whichwas first approximated from empirical data from a range ofother sites then refined through model calibration usingobservations of water surface elevation between 2003 and2008 from the ICEsat laser altimeter. Inundation extent wasevaluated using Landsat imagery from the same period. The109

model was used to demonstrate that both the channelnetwork (including the connectivity provided by floodplainchannels) and floodplain storage are necessary to simulatethe correct wave propagation. The calibration of the sub-gridchannel model from the available remotely sensed data setsand prospects for assimilating data with the model on ungaugedrivers were also evaluated.Neale, Christopher M.Water balance of Large Irrigation Systems usingRemotely Sensed ET EstimatesNeale, Christopher M. 1 ; Taghvaeian, Saleh 1 ; Geli, Hatim 11. Civil and Environmental Eng., Utah State University,Logan, UT, USADemand for water for urban/municipal uses continuesto rise in the Western US with the growing population. Mostfresh water is tied up in irrigated agriculture thusunderstanding the pathways of irrigation water and theconsumptive use of water within large irrigation systemsbecomes of vital importance for improved rivermanagement, policy decisions and water transfers. In thispaper we examine the use of different remote sensingmethods for estimating evapotranspiration (ET), namely theenergy balance method and the reflectance-based cropcoefficient method for estimating seasonal ET at the PaloVerde Irrigation District (PVID) in southern, CA. Two energybalance methods are tested, namely the Two-source model by(Norman et al., 1995) and the Surface Energy Balance forLand (SEBAL) method (Bastiaansen et al., 1998). Thereflectance-based crop coefficient method as originallydescribed by Neale et al, 1989, Bausch and Neale, 1987 is alsoapplied. The PVID system diverts water from the ColoradoRiver through an extensive network of canals. Water flowmeasurements are conducted in the inflow to the system aswell as the main outflow drain and all spill locations at theend of lateral canals, allowing a complete water balance to beestimated for this 53000 ha irrigation system. An extensivenetwork of groundwater wells allowed for the monitoring ofdeep percolation and drainage. We close the yearly waterbalance using estimates of ET from the different remotesensing based models. Daily ET values from the differentmodels are compared to Bowen ratio and eddy covariance ETmeasurements from towers placed in alfalfa and cottonrespectively. The PVID is located in the overlap zone betweentwo Landsat TM paths, which resulted in 21 usable imagesduring 2008 (Taghvaeian, 2011) and allowed for a detailedexamination of seasonal ET by the different models.Nearing, GreyEstimating Thermal Inertia with a MaximumEntropy Production Boundary ConditionNearing, Grey 1 ; Moran, Susan 2 ; Scott, Russell 21. Hydrology and Water Resources, University of Arizona,Tucson, AZ, USA2. Southwest Watershed Research Center, USDA-ARS,Tucson, AZ, USAThermal inertia, P [Jm-2s-1/2K-1], is a physical propertythe land surface which determines resistance to temperaturechange under seasonal or diurnal heating. It is a function ofvolumetric heat capacity, c [Jm-3K-1], and thermalconductivity, k [Wm-1K-1] of the soil near the surface:P=ck. Thermal inertia of soil varies with moisture contentdue the difference between thermal properties of water andair, and a number of studies have demonstrated that it isfeasible to estimate soil moisture given thermal inertia (e.g.Lu et al, 2009). One common approach to estimatingthermal inertia using measurements of surface temperatureis to model the Earth’s surface as a 1-dimensionalhomogeneous diffusive half-space and derive surfacetemperature as a function of the ground heat flux (G)boundary condition and thermal inertia; a daily value of P isestimated by matching measured and modeled diurnalsurface temperature fluctuations. The difficulty in applyingthis technique is in measuring G, and a number ofapproaches have been suggested (e.g. Xue and Cracknell,1995). We demonstrate that the new maximum entropyproduction (MEP) method for partitioning net radiationinto surface energy fluxes (Wang and Bras, 2011) provides asuperior boundary condition for estimating P. Adding thediffusion representation of heat transfer in the soil reducesthe number of free parameters in the MEP model from twoto one, and we provide a sensitivity analysis which suggests,for the purpose of estimating P, that it is preferable toparameterize the MEP model by the ratio of thermal inertiaof the soil to the effective thermal inertia of convective heattransfer to the atmosphere. Estimates of thermal inertia attwo semiarid, non-vegetated locations in the Walnut GulchExperimental Watershed in southeast AZ, USA are madeusing time series of ground heat flux measurements andthese are compared to estimates of thermal inertia madeusing the boundary condition suggested by Xue andCracknell (1995) and those made with the MEP ground heatflux boundary condition. Nash-Sutcliffe efficiencycoefficients for predictions made using the MEP boundarycondition are NSE = 0.44 and NSE = 0.59 at the two sitedcompared to NSE = -12.31 and NSE = -6.81 using the Xueand Cracknell boundary condition. Thermal inertiameasurements made using the MEP boundary condition areextrapolated to daily near-surface soil moisture estimatesusing the model developed by Lu et al (2009). In very dryconditions, thermal inertia is less sensitive to changes in soilmoisture than in moderate-to-wet conditions. Overall wefind the correlation between measured and modeled soilmoisture at these semiarid sites to be approximately 0.5.Lu, S., Ju, Z.Q., Ren, T.S., & Horton, R. (2009). A general110

approach to estimate soil water content from thermalinertia. Agricultural and Forest Meteorology, 149, 1693-1698Wang, J.F., & Bras, R.L. (2011). A model ofevapotranspiration based on the theory of maximumentropy production. Water Resources Research, 47 Xue, Y., &Cracknell, A.P. (1995). Adavanced thermal inertia modeling.International Journal of Remote Sensing, 16, 431-446Négrel, JeanRiver surface roughness sensitivity to windconditions : in situ measurement technique,processing method and resultsNégrel, Jean 1 ; Kosuth, Pascal 1 ; Caulliez, Guillemette 2 ;Strauss, Olivier 3 ; Borderies, Pierre 4 ; Lalaurie, Jean-Claude 5 ;Fjortoft, Roger 51. UMR TETIS, IRSTEA, Montpellier, France2. IRPHE, CNRS, Marseille, France3. LIRMM, Université Montpellier 2, Montpellier, France4. DEMR, ONERA, Toulouse, France5. DCT/SI/AR, CNES, Toulouse, FranceWater surface roughness strongly impacts microwavebackscattering process over rivers. Therefore, developpingradar interferometry techniques over continental waters todetermine river slope (cross-track interferometry) or surfacevelocity (along-track interferometry) requires a detailedcharacterization of water surface roughness, its relation withriver flow and wind conditions, its influence on backscattercoefficient. In situ measurement of river surface roughness isa complex task as surface topography is rapidly changingand sensitive to obstacles or contact measurements.Laboratory measurements, although highly informative, fallshort to represent the diversity of river flow and windconditions. In the framework of the SWOT missionpreparatory phase, a method was developped for fieldmeasurement of river surface roughness. It was tested andvalidated in laboratory conditions, and implemented innatural conditions on the Rhône river, under various windintensities. The method is based on the acquisition of waterpressure time series by a network of immersed pressuresensors, with synchronized 10 Hz sampling and 0,1 mbaraccuracy (1mm water elevation). A preliminary low frequencyfiltering is applied to each sensor pressure time series toremove water level trends. Mean depth h, frequencyspectrum, dominant frequency f and standard deviation ofwater pressure Pare determined per time interval (180s). Amultisensor analysis is realised to determine directional wavecelerity c and directional correlation length L corr. Finallystandard deviation of surface water level Zis determined foreach sensor by applying a correction factor, taking intoaccount the signal damping with depth. Z=e 2.pi.h.f/c . P(h)Laboratory tests validated the measurement technique,provided that the correction factor does not exceed 10 (i.e.the immersed sensor records more than 10% of the surfacesignal) which is achievable by limiting the sensor depth.Field measurements were realised during a campaign on theRhône river (may 2011). The sensor network was located10m from the river bank and 0,15m under the surface water.It recorded during 7 hours at 10 Hz. Wind measured at 2mheight had the same direction as river flow (southward),with intensity changing progressively from 8m/s to 0m/s.Surface roughness was characterized, per 3 minute timeintervals, by Frequency spectrum, dominant frequency,standard deviation of surface water level Z, directional wavecelerity c and directional correlation distance L corr. Itssensitivity to wind conditions was analysed and modelled.The method is currently being adapted on a floating supportfor intensive river surface roughness measurement.Njoku, Eni G.Soil Moisture Active Passive (SMAP) MissionScience and Data Product DevelopmentNjoku, Eni G. 1 ; Entekhabi, Dara 2 ; O’Neill, Peggy E. 3 ;Jackson, Thomas J. 41. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA2. Massachusetts Institute of Technology, Cambridge, MA,USA3. NASA Goddard Space Flight Center, Greenbelt, MD, USA4. USDA ARS Hydrology and Remote Sensing Laboratory,Beltsville, MD, USAThe Soil Moisture Active Passive (SMAP) mission,planned for launch in late 2014, has the objective offrequent, global mapping of near-surface soil moisture andits freeze/thaw state. The SMAP measurement systemutilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operateon a spacecraft in a 685-km polar orbit with 6 am/6 pmnodal crossings, viewing the surface at a constant 40-degreeincidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yieldglobal maps of soil moisture and freeze/thaw state at 10 kmand 3 km resolutions, respectively, every two to three days.The 10-km soil moisture product will be generated using acombined radar and radiometer retrieval algorithm. SMAPwill also provide a radiometer-only soil moisture product at40-km spatial resolution and a radar-only soil moistureproduct at 3-km resolution. The relative accuracies of theseproducts will vary regionally and will depend on surfacecharacteristics such as vegetation water content, vegetationtype, surface roughness, and landscape heterogeneity. TheSMAP soil moisture and freeze/thaw measurements willenable significantly improved estimates of the fluxes ofwater, energy and carbon between the land and atmosphere.Soil moisture and freeze/thaw controls of these fluxes arekey factors in the performance of models used for weatherand climate predictions and for quantifying the global111

carbon balance. Soil moisture measurements are also ofimportance in modeling and predicting extreme events suchas floods and droughts. The algorithms and data productsfor SMAP are being developed in the SMAP Science DataSystem (SDS) Testbed. In the Testbed algorithms aredeveloped and evaluated using simulated SMAPobservations as well as observational data from currentairborne and spaceborne L-band sensors including datafrom the SMOS and Aquarius missions. We report here onthe development status of the SMAP data products. TheTestbed simulations are designed to capture various sourcesof errors in the products including environment effects,instrument effects (non-ideal aspects of the measurementsystem), and retrieval algorithm errors. The SMAP projecthas developed a Calibration and Validation (Cal/Val) Planthat is designed to support algorithm development (prelaunch)and data product validation (post-launch). A keycomponent of the Cal/Val Plan is the identification,characterization, and instrumentation of sites that can beused to calibrate and validate the sensor data (Level 1) andderived geophysical products (Level 2 and higher).Nolin, Anne W.Vegetation and Snow: Remote Sensing andInteractions from the Local to the ContinentalScaleNolin, Anne W. 1 ; Coons, Lexi 1 ; Blauvelt, Katie 1 ; Gleason,Kelly 1 ; Sproles, Eric 11. College of Earth, Ocean, and Atmospheric Sciences,Oregon State University, Corvallis, OR, USAIn cold land environments, snow cover is a key part ofthe terrestrial water cycle and snow-vegetation interactionsare intricately linked and bidirectional. For example, reducedsnow cover increases soil moisture stress affecting vegetationgrowth patterns and multiplying impacts to vegetationincluding carbon storage, phenology, pest life history, andfire frequency. Land cover affects aerodynamic roughnessand turbulent fluxes at the snow-atmosphere-vegetationinterface. Changes in land cover due to natural and humanimpacts (wildfire, pest infestation, forest harvest) affectpatterns of snow accumulation and ablation. Moreover, thepresence of forest canopy and shrub vegetation significantlyinhibits our ability to measure and monitor our changingsnowpacks. In this presentation, we present new concepts inmeasuring and understanding snow-vegetation interactionswith relevance to remote sensing. First, we debut a new acanopy adjustment for fractional snow covered area that usesvegetation density and height. Because forest canopyobscures the snow below whereas shrubs typically do not,canopy height must be known if one is to provide accuratemaps of snow-covered area. Second, positive correlationsbetween snow cover and vegetation have been observed.Using 10 years of MODIS data we demonstrate relationshipsbetween green biomass and antecedent snow cover frequencyfor various regions in the United States. Last, we identifyhow changing land cover due to wildfire or forest harvestaffect snow energy balance and how such changes can bemeasured from space using sensor technologiesrecommended by the Decadal Survey.http://www.geo.oregonstate.edu/~nolina/RESEARCH_GROUP/Noone, David C.Evaluation of tropical continental water cyclingfrom space-based observations of water isotoperatiosNoone, David C. 1 ; Berkelhammer, Max 1 ; Worden, John 2 ;Schmidt, Gavin 31. Univ Colorado, Dept Atmospheric & Oceanic Sci,Boulder, CO, USA2. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA3. Goddard Institute for Space Siences, New York, NY, USAThe continental water cycle in the tropics is a leadingcomponent of the global latent heat budget. Uncertainty inthe rates of exchange of water between the tropical landsurface and the atmosphere persist as uncertainties inestimates of the global energy budget. Uncertainties arisebecause of lack of constraint on the pathways that watertakes as it moves from the atmosphere to the landscape andback. Model estimates of land-atmosphere exchange rely onestimates of model parameters that are not well constrainedby observations. Inter-model differences are associated withinherently small scale processes such as infiltration,interception of water on canopies and rooting depth. At theregional scale, the aggregate of complex ecosystem fluxes canbe better understood with knowledge of the isotopiccomposition of water because the isotopic compositionprovides constraint on the net fluxes that result from theconservation and partitioning of isotope ratios duringexchange. Estimates of the D/H isotope ratio of water vaporfrom the Tropospheric Emission Spectrometer (TES) onNASA’s Aura spacecraft are used to deduce features of theterrestrial water budget. The isotopic information is usefulin two ways: 1) it provides a tracer of mechanismscontrolling vertical transport from the boundary layer,through clouds and to the troposphere, and 2) it proves ageophysical “tag” which reflects the fraction of water vaporwhich is derived from transpiration versus water vapor withan oceanic origin and associated with low level advection.Isotopic ratios from TES are used to estimate seasonal andinterannual variations in the terms contributing to theatmospheric water budget of the Amazon and near theIndian/Asian monsoons. Results are contrasted withestimates of continental recycling and seasonal changes inmoisture budgets derived from non-isotopic means. Thework highlights the advantages of using isotopicinformation in integrated assessments of continental waterbudgets. The study also highlights the advantage of pairingisotopic measurements with other trace gases such as CO2and CO to constrain vertical transport, and points to theneed for better surface and aircraft based observations of theisotopic composition to complement the regional synthesisoffered by satellite remote sensing.112

Norouzi, HamidrezaLand Surface Characterization Using Multi-satelliteMicrowave ObservationsNorouzi, Hamidreza 1 ; Aghakouchak, Amir 2 ; Azarderakhsh,Marzieh 31. The City University of New York - NYCCT, New York, NY,USA2. University of California - Irvine, Irvine, CA, USA3. The City College of New York, New York, NY, USAMicrowave observations at low frequencies exhibitsensitivity to surface and subsurface properties as expressedby surface emissivity. Moreover, the microwave brightnesstemperatures at different frequencies originate fromdifferent depths which can provide structural profile of thesurface. This information can be used to characterize thevegetation structure or soil moisture profiles. In this study,we developed a global land emissivity product using AMSR-Epassive microwave data after removing the effect of theatmosphere. Also, the impact of the difference in penetrationdepths between passive microwave and thermal temperatureson the retrieval of land emissivity was investigated. There is adifference in phase time and amplitude between physicaltemperature from IR and MW brightness temperature,especially in arid and semi-arid regions where microwavepenetrates deeper than thermal Infrared observations. Thediurnal variation of passive microwave brightnesstemperature using similar frequencies of different satelliteswas analyzed. Principal Component Analysis (PCA) is usedto explore the spatial variation of passive microwave diurnalcycle. The effect of the moisture in vegetation and soil on theshape of the diurnal cycle at different frequencies wereexamined. Larger diurnal amplitude is observed in aridregions while densely vegetated areas present loweramplitude. The differences in emissivities at differentfrequencies are consistent with vegetation structures.Different land classes and their changes through the time isalso investigated.Nosetto, MarceloLand-use changes in temperate Argentina:Assessing their hydrological impacts with remotesensingNosetto, Marcelo 1, 2 ; Jobbágy, Esteban 1, 21. IMASL - CONICET & UNSL, Grupo de EstudiosAmbientales, San Luis, Argentina2. Ciencias Agropecuarias, FICES, Villa Mercedes, ArgentinaVegetation exerts a strong control on water balance andkey hydrological variables like evapotranspiration, wateryield or even the flooded area may result severely affected byvegetation changes. Particularly, transitions between treeandherbaceous-dominated covers, which are taking place atincreasing rates in southern South America, may have thegreatest impact on the water balance. Both the clearing ofnative dry forests for grain production and the afforestationof grasslands with fast-growing tree species are occurring indifferent areas of temperate Argentina. The fast replacementof perennial pastures by soybean in the Pampas may alsolead to noticeable hydrological effects. Based on Landsat andTerra imagery analysis, field sampling and hydrologicalmodeling we evaluated vapor and liquid ecosystem waterfluxes, soil moisture changes and groundwater levelsdynamics in temperate Argentina and provided a usefulframework to assess potential hydrological impacts of landusechanges. Different native (dry forests, grasslands) andmodified vegetation types (eucalyptus plantations, singlesoybean crop and wheat/soybean rotation, alfalfa pastures)were considered in the analysis. Despite contrastingstructural differences, native dry forests and eucalyptusplantations displayed evapotranspiration values remarkablysimilar (1100 mm y1) and significantly higher thanherbaceous vegetation covers (780, 670 and 800 mm y1for grasslands, soybean and wheat/soybean system,respectively). In agreement with evapotranspirationestimates, soil profiles to a depth of 3 m were significantlydrier in woody covers (0.31 m3 m3) compared to nativegrasslands (0.39 m3 m3), soybean (0.38 m3 m3) andwheat/soybean rotation (0.35 m3 m3). Where groundwaterwas shallow (< 5 m of depth), soil profiles at eucalyptusplantations showed higher salts accumulation compared tocrops and grasslands. Groundwater and soil salinizationincreased as the water balance became more negative and thegroundwater shallower. Liquid water fluxes (deep drainage +surface runoff) were at least doubled in herbaceous covers, assuggested by modeling (170 mm y1) and 357 mm y1),for woody and herbaceous covers, respectively). Our analysisrevealed the hydrological outcomes of different vegetationchanges trajectories and provided valuable tools that willhelp to anticipate likely impacts, minimize uncertainties andprovide a solid base for sustainable land use planning.Nunes, AnaChallenges in Assessing South AmericanHydroclimate: How Can Satellite-BasedPrecipitation Products Help?Nunes, Ana 11. Federal University of Rio de Janeiro, Rio de Janeiro, BrazilAssessing climate variability and change at regionalscales can be challenging due to nonlinear interactionsamong different scale phenomena, particularly in regionswith sparse long-term observational records such as SouthAmerica. Therefore, reconstructing regional climate throughdynamically consistent models can be useful over remoteareas of South America, and also provide additional variablesets for energy and water-cycle studies over the entirecontinental domain. By considering a global reanalysis as theboundary condition provider, and constraining a regionalclimate model’s solution to closely follow the boundaryfields at scales above 1,000 km, one would expect that largescalefeatures from global reanalysis could be preservedduring long-term regional simulations. However,parameterized processes such as convection can cause theregional model’s full solution (base field + perturbation) to113

deviate from “observation”-driven fields. In that regard,assimilation of satellite-based precipitation products andrain-gauge datasets by a regional model can bring the fullregional solution closer to the “observed” mass and dynamicfields. Land-surface processes are heavily dependent uponaccurate precipitation, as a result surface and near-surfacedownscaled features also benefit from assimilation ofsatellite-based precipitation products, with improvedhydroclimatology as shown in the results.Olsen, Jørgen L.Estimating variations in bare soil and vegetationsurface moisture, using solar spectrumgeostationary earth observation data over a semiaridareaOlsen, Jørgen L. 1 ; Ceccato, Pietro 2 ; Proud, Simon R. 1 ;Fensholt, Rasmus 1 ; Sandholt, Inge 11. Geography and Geology, University of Copenhagen,Copenhagen, Denmark2. the International Research Institute, ColumbiaUniversity, New York, NY, USASurface moisture is an important environmental factorin the Sudano-Sahelian areas of West Africa, as water is theprimary restricting factor of vegetation growth. Due to agenerally insufficient number of conventional ground basedclimate observations in the region, Earth observationprovides much needed data for estimating surface moisture.Remote sensing of surface moisture using the short wavesolar spectrum (400nm to 2500nm) has shown promisingdevelopments during the last two decades, and recentresearch have shown the ability of instruments onboardgeostationary satellites to provide continuous surfaceobservations, even during cloud prone rainy seasons, whichis one of the big challenges for much remote sensing. A wellexamined approach for surface moisture estimation usingthe solar spectrum is the combination of near infrared (NIR)and short wave infrared (SWIR) observations into indices.NIR-SWIR indices are sensitive to both vegetation and watercontent. One of these indices is the Short Wave InfraredWater Stress Index (SIWSI), which has previously beenimplemented using data from the Spinning EnhancedVisible and Infrared Imager (SEVIRI) onboard thegeostationary Meteosat Second Generation (MSG) satellite.Some issues remain though, and two of these are examinedin this study. The first is the potential of geostationarysatellite observations for estimating surface moisture duringnear bare soil conditions. The second concerns the difficultyof acquiring reliable information on vegetation watercontent from the SIWSI index in a semi-arid environment,during early to mid- growing season. Using several years ofin situ measurements from the Dahra field station innorthern Senegal, combined with a newly developed MSGSEVIRI daily NBAR product both issues are addressed, byanalysis of time series and statistical analysis. It is found thatfor bare soil conditions a sub daily temporal resolution isnecessary to observe variations in near surface soil moisture,and by using a product calculated from several observations,as in the case of a daily NBAR product, the sensitivity islimited. This fits well with previous findings in the literaturefrom laboratory spectroscopy of soil and soil moisture. Forthe second issue it is found that for an area dominated byannual grasses, the vegetation amount is the deciding factorfor the NIR-SWIR signals in the SIWSI index. Comparisonmade with biomass load samples provides a general idea ofthe lower limits for amount of vegetation necessary forSIWSI to be sensitive to changes in water content.Oyler, Jared W.Assessment of the MODIS Global TerrestrialEvapotranspiration Algorithm within aMountainous LandscapeOyler, Jared W. 1 ; Mu, Qiaozhen 1 ; Running, Steven W. 11. University of Montana, Missoula, MT, USAWith a changing climate, accurately monitoring andpredicting spatial patterns of water balance and subsequenteffects on hydrologic and ecologic function at the landscapescalehas become of critical importance. Remote sensingmethods and data products such as the MODIS 1-km globalevapotranspiration dataset (MODIS ET) have the potentialto be extremely valuable tools for land and water managersin this regard. However, while MODIS ET has been validatedagainst point-source measurements, little work has been todone to assess its ability to depict key ET spatial variabilityat the 1-km scale, especially in complex terrain. Therefore,this study evaluates spatial and temporal patterns in MODISET estimates from 2000-2009 within the rugged Crown ofthe Continent Ecosystem of the U.S. Northern Rockies tosee if it is able to capture the main landscape-scalebiophysical controls on regional ET. MODIS ET is comparedwith ET estimates generated from Biome-BGC, a fullprognostic biogeochemical ecosystem model. Although bothBiome-BGC and MODIS ET use a formulation of thestandard Penman-Monteith equation, Biome-BGC includesseveral other controls on evapotranspiration including soilwater content and water availability from snowpack.Additionally, compared to the coarse meteorologicalreanalysis data (1.00° x 1.25°) used by MODIS ET, Biome-BGC is forced by a 1-km spatial climatology specificallydeveloped to capture the steep climatic gradients of complexterrain. In consequence, this analysis provides an importantassessment of whether MODIS ET can be used to accuratelymonitor spatial patterns of water balance at a 1-kmlandscape-scale or if it should only be applied at largerregional, continental, and global extents.114

Painter, Thomas H.The JPL Airborne Snow Observatory: Cutting edgetechnology for snow hydrology and watermanagementPainter, Thomas H. 1 ; Deems, Jeffrey 2 ; McGurk, Bruce 3 ;Dooley, Jennifer 1 ; Green, Robert O. 11. Jet Propulsion Laboratory, Pasadena, CA, USA2. Western Water Assessment/NSIDC, University ofColorado, Boulder, CO, USA3. McGurk Hydrologic, Orinda, CA, USASnowmelt in the western US dominates the freshwatersupply for tens of millions of people. In particular, theColorado River supplies freshwater to 27 million people inseven states and Mexico, and without the import ofsnowmelt-dominated aqueducts, the metropolitan LosAngeles area could sustain only 400 thousand of its current15 million people. In 2010, Lake Mead faced a drop to a lakelevel of 1075’, which would have triggered action underShortage Sharing agreement with interstate andinternational legal implications. The two most criticalproperties for understanding snowmelt totals and timing arethe spatial distributions of snow water equivalent (SWE) andsnow albedo. Despite their importance, these snowpackproperties are poorly quantified in the US and not at all inmost of the globe, leaving runoff models poorly constrained.Recognizing this void, we are building the Airborne SnowObservatory (ASO), an integrated imaging spectrometer andscanning lidar system, to quantify spatially coincident snowwater equivalent and snow albedo in headwaters throughoutthe Western US. The ASO will provide unprecedentedknowledge of snow properties and complete, robust inputsto water management models and decision-support systemsof the future. The ASO couples a visible through shortwaveinfrared imaging spectrometer (the Airborne Visible/InfraredImaging Spectrometer-NextGeneration, AVIRISng) with ahigh-altitude, scanning LiDAR system (Optech Gemini) on aTwin Otter aircraft. The AVIRISng will measure reflectedsolar radiance from ~5 m pixels in ~220 spectral bands from350 to 2500 nm. The LiDAR will image at 1064 nmwavelength with 4 range measurements and continuousmultipulse technology to provide highly accurate surfaceelevation maps, allowing mapping of snow depth at ~5 m aswell. The snow depth maps will then be combined with fieldand automated measurements of snow density to produceSWE maps. The first ASO Demonstration Mission (ASO-DM1) will cover the Upper Tuolumne River Basin, SierraNevada, California (City of San Francisco water supply) andthe Uncompahgre River Basin, San Juan Mountains,Colorado (Upper Colorado River Basin). The ASO willacquire snow-free data in late summer to provide thebaseline topography against which snow depth may bedetermined. The ASO will then image target basins on aweekly basis from mid winter through complete snowmelt toprovide coincident spatial distributions of snow albedo,snow depth, snow water equivalent, and dust/black carbonradiative forcing in snow. The data will be processed on thenew JPL Snow Server cluster (192 cores) and delivered to115water managers in near real time, lagged by < 24 hours. Inturn, in both basins, we will compare forecast total volumesand timing driven by current, limited data sources withthose forecasts driven by the comprehensive products fromthe ASO. The ASO-DM1 data will then be processed torefined products and delivered to the broader communityfor scientific discovery.Parajka, JurajMODIS Snow Cover Mapping Accuracy in SmallAlpine CatchmentParajka, Juraj 1 ; Holko, Ladislav 21. Institute of Hydraulic Engineering and Water ResourcesManagement, Vienna University of Technology, Vienna,Austria2. Institute of Hydrology, Slovak Academy of Sciences,Liptovsky Mikulas, SlovakiaIn the last decade, a range of MODIS snow coverproducts have been used for regional mapping of snow coverchanges. MODIS images are particularly appealing due totheir high temporal (daily) and spatial resolution. Numerousvalidation studies examined and confirmed their accuracyand consistency against other remote-sensing products andin situ climate station data. The snow cover mappingefficiency in alpine and forested regions is, however, still notwell understood. The main research questions addressed inthis contribution are: How accurate is MODIS snow covermapping in alpine forested environment? Does MODISconsistently identify snow cover beneath forest particularlyat the end of snow melt period? MODIS snow cover changesin small experimental catchment (Jalovecky creek, WesternTatra Mountains, Slovakia) will be compared against theextensive snow course measurements at open and forestedsites. It is anticipated that a decade of snow observations inwell documented experimental catchment may give moregeneral insight into the efficiency and accuracy of MODISsnow cover dataset in forested alpine regions.www.hydro.tuwien.ac.atParinussa, RobertGlobal quality assessment of active and passivemicrowave based soil moisture anomalies forimproved blendingParinussa, Robert 1, 2 ; Holmes, Thomas 2 ; Crow, Wade 2 ;Dorigo, Wouter 3 ; de Jeu, Richard 11. Hydrology and Geo-environmental sciences, VUUniversity Amsterdam, Amsterdam, Netherlands2. Hydrology and Remote Sensing Laboratory, USDA-ARS,Beltsville, MD, USA3. Institute for Photogrammetry and Remote Sensing,Vienna University of Technology, Vienna, AustriaRecently, a methodology that takes advantages of theretrieval characteristics of passive (AMSR-E) and active(ASCAT) microwave satellite soil moisture estimates wasdeveloped. Combining surface soil moisture estimates fromboth microwave sensors offers an improved product at a

global scale, having a better spatial coverage and increasednumber of observations. The developed merging strategy isbased on the use of AMSR-E night-time and ASCATobservations, of which the qualities were determined usingthe Triple Collocation verification technique. To improve thespatial coverage and the number of observations, AMSR-Eday-time and WindSat observations could be included in themerging procedure. Here, we present a quality assessment ofsoil moisture anomalies from active and passive microwaveobservations which could be used for extending the recentlydeveloped merging strategy. We base our analysis on the useof two different evaluation techniques, the TripleCollocation and the Rvalue verification technique, and weinclude modeling to support the use of soil moistureretrievals from day-time passive microwave observations. Theresults from this study may be used for more comprehensivemerging strategy as they suggest that surface soil moistureestimates from day-time passive microwave observationsincrease in quality with increasing vegetation cover. Inregions where passive and active products perform similarlywell, weighting functions may be derived using the resultspresented in this study.Parinussa, RobertA Multi-decadal soil moisture dataset from passiveand active microwave soil moisture retrievalsParinussa, Robert 1 ; De Jeu, Richard 1 ; Dorigo, Wouter 2 ; Liu,Yi 3, 1 ; Wagner, Wolfgang 2 ; Fernandez, Diego 41. Hydrology and Geo-environmental sciences, VUUniversity Amsterdam, Amsterdam, Netherlands2. Institute for Photogrammetry and Remote Sensing,Vienna University of Technology, Vienna, Austria3. Climate Change Research Centre, University of NewSouth Wales, Sydney, NSW, Australia4. ESA, ESRIN, Frascati, ItalyRecently, as part of the Water Cycle MultimissionObservation Strategy (WACMOS) project a methodology hasbeen developed to build a harmonized multi-decadal satellitesoil moisture dataset. The VU University Amsterdam –National Aeronautics and Space Administration (VUA-NASA) passive microwave products derived from foursatellites and the Vienna University of Technology (TU-Wien) active microwave products derived from two satelliteswere used in this study. The products were merged, rescaled,ranked and blended into one final product. The harmonizedsoil moisture values were compared to in situ data from theInternational Soil Moisture Network (ISMN) and generallyshowed a better agreement than the individual products.Interannual variability and long term trends within this soilmoisture dataset were analyzed and evaluated usingadditional datasets, including tree ring data and oceanoscillation indices. These results gave us confidence in thequality of this new product. This product will now befurther improved and implemented within the ClimateChange Initiative (CCI) programme of ESA.Paris, AdrienIMPROVING DISCHARGE ESTIMATES IN ALARGE, POORLY GAUGE BASIN BY TUNING AHYDROLOGICAL MODEL WITH SATELLITEALTIMETRY INFORMATIONCalmant, Stephane 1 ; Paris, Adrien 2, 1 ; Santos da Silva,Joecila 3 ; Collischonn, Walter 2 ; Paiva, Rodrigo 2, 4 ; Bonnet,Marie-Paule 4 ; Seyler, Frederique 51. OMP-LEGOS-IRD, Toulouse Cedex 09, France2. IPH - UFRGS, Porto Alegre, Brazil3. CESTU - UEA, Manaus, Brazil4. UMR-GET-IRD, Toulouse, France5. UMR-Espace DEV-IRD, Montpellier, FranceAccurate modeling of discharge in a basin requires alarge amount of information. This information is threefold:First, knowledge of the river geometry such as the slope ofriver surface and bottom, the width of the cross sectionthroughout the river course, the height at whichoverbanking occurs; second knowledge of the watershed,DTM soil characteristics and vegetation type; and last,physical parameters such as a friction coefficient, includingits space and time variations (i.e. seasonal variations withwater level). In most large tropical basins, knowledge of theriver geometry is dramatically lacking, in particular in themost upstream, remote, parts. Satellite altimetry providestime series of altitude of the river surface. Because theseseries are naturally leveled, slope of the river surface can alsobe derived easily. Also, in some favorable cases, the geometryof the section crossed by the satellite track is imaged by thesuccessive height profiles, between the lowest and higheststages. The time sampling of these series is quite poor,ranging from every decade in the best cases to a fewmeasurements a year in the worse cases. In turn, the spacingis rather good, from a few km to a few hundreds of km. TheMGB model was developed at IPH to compute river flow inlarge basins. Originally, for reaches where actual data arelacking, the riverbed geometry was derived from empiricalgeomorphological relationships. Besides, the flow dynamicshad to be left unconstrained and unchecked down until thefirst gauging station. In the present study, we present recentimprovements obtained in the flow modeling by tuning theMGB model in order that the river geometry and modeloutputs better fit altimetry series. We present and discussthe benefits gained in the case of the Japura-Caqueta river, inthe Amazon basin. The Japura-Caqueta river is atransboundary river, called Caqueta in its upstreamColombian part and Japura in its downstream, Brazilianpart. No gauge measurements are available in the Colombianpart, and only 3 gauging stations exist in the Brazilian part,when 29 ENVISAT tracks cross the river, making as muchopportunities to put constrains on model parameters suchas reach width, river slope, or model outputs such as stagevariations.116

Pavelsky, Tamlin M.Continuous River Width-Drainage AreaRelationships in the Yukon River BasinPavelsky, Tamlin M. 1 ; Allen, George H. 11. Dept of Geological Sciences, University of NorthCarolina, Chapel Hill, NC, USAThrough their role in transporting water and sedimentfrom upland catchments to coastal oceans, rivers play a keyrole in organizing landscapes and represent a major link inthe global hydrologic cycle. River form varies widely, anddifferent characteristics reflect variations in discharge,substrate, climate, and human impacts. Studies of therelationship between fluvial form and discharge (orcatchment area, which is often substituted) have beenconducted since at least the early 1950s, with statisticalrelationships between discharge and river depth, width, andvelocity encapsulated in the hydraulic geometry framework.However, large-scale examinations of river form have beenlimited by a lack of data, and most prior studies havefocused on discrete cross-sections surveyed on the ground oron descriptions of network form (i.e. stream order) ratherthan continuous river morphology. More recently, satelliteremote sensing has been used to study river form over largerscales, without the need for ground-based surveying. To thispoint, however, studies of river form from space have largelyfocused on individual river reaches or sets of discrete crosssectionsrather than measuring fluvial form continuouslyover entire large river basins. In this study, we use theRivWidth software tool(http://www.unc.edu/~pavelsky/Pavelsky/RivWidth.html) tocontinuously map river widths from 30 m Landsat imageryfor all rivers wider than ~50m in the Yukon River Basin ofCanada and Alaska. The Yukon basin was selected because itis almost entirely free of direct human influence on riverform, while also containing a wide range of different channelplanforms. The resulting map of river widths is then linkedto a map of catchment area derived from the Hydro1Kdigital elevation dataset, allowing width and catchment areato be continuously compared across an entire large riverbasin for the first time. From these linked datasets, weevaluate the consistency of width-catchment arearelationships over the entire basin and compare individualsub-basins with different characteristics including sedimentload, permafrost extent, and annual precipitation. Inaddition, the width dataset developed here provides a firstmeasure of which rivers within the Yukon Basin will besampled by the NASA/CNES Surface Water and OceanTopography (SWOT) satellite mission. One of SWOT’s majorgoals is the provision of discharge estimates for all riverswider than 100 m, globally, yet the extent and locations ofthese rivers remains poorly constrained. We demonstrate theability of RivWidth measurements to estimate SWOTsampling extent over larger river basins such as the Yukon.Peters-Lidard, Christa D.The Impact of AMSR-E Soil Moisture Assimilationon Evapotranspiration EstimationPeters-Lidard, Christa D. 1 ; Kumar, Sujay 2, 1 ; Mocko, David 2, 1 ;Tian, Yudong 3, 11. Hydrological Sciences Laboratory, NASA/GSFC Code 617,Greenbelt, MD, USA2. SAIC, Beltsville, MD, USA3. ESSIC, University of Maryland, College Park, MD, USAAn assessment of ET estimates for current LDASsystems is provided along with current research thatdemonstrates improvement in LSM ET estimates due toassimilating satellite-based soil moisture products. Using theEnsemble Kalman Filter in the Land Information System, weassimilate both NASA and Land Parameter Retrieval Model(LPRM) soil moisture products into the Noah LSM Version3.2 with the North American LDAS phase 2 (NLDAS-2)forcing to mimic the NLDAS-2 configuration. Throughcomparisons with two global reference ET products, onebased on interpolated flux tower data and one from a newsatellite ET algorithm, over the NLDAS2 domain, wedemonstrate improvement in ET estimates only whenassimilating the LPRM soil moisture product.http://lis.gsfc.nasa.govPipunic, RobertImpacts of satellite surface soil moistureassimilation on modelled root zone soil moistureand ET over a six year period: Assessment across anin-situ soil moisture monitoring network, Murray-Darling Basin, AustraliaPipunic, Robert 1 ; Ryu, Dongryeol 1 ; Walker, Jeffrey 21. Department of Infrastructure Engineering, TheUniversity of Melbourne, Parkville, VIC, Australia2. Department of Civil Engineering, Monash University,Clayton, VIC, AustraliaThe importance of root zone soil moisture is recognisedfor its role in partitioning rainfall between infiltration andrun-off, drainage to groundwater, and as a water storeaccessible to plant roots contributing to evapotranspiration.Thus accurate predictions of moisture content in the rootzone will have enormous benefit for land and watermanagement practices including agriculture, flood andweather forecasting. While this has been long known, it isstill very difficult to predict the soil moisture content ofdesired accuracies with spatially distributed Land SurfaceModels (LSMs), which becomes more challenging whenLSMs are run at

etrievals of soil moisture considered most reliable arelimited by a large spatial footprint (>10 km) and shallowmeasurement depth (top ~1-2 cm of soil). Past studies haveshown that assimilating surface soil moisture observationshas the potential to improve root zone soil moisturepredictions even though many of these studies are based onidealised synthetic experiments. Recent studies have shownmarginal improvements in predicting root-zone soilmoisture by assimilating real microwave soil moisture. Wepresent an assimilation study using a remotely-sensedsurface soil moisture data product and the CABLE (CSIROAtmosphere Biosphere Land Exchange) model (Kowalczyk etal., 2006) and assess whether root zone soil moisturepredictions are improved as a consequence. CABLE wasdeveloped by the CSIRO (Commonwealth Scientific andIndustry Research Organisation) in Australia andimplementing it in Australia’s climate and weathersimulation system is planned. Our focus is a 100 km x 100km agricultural region in the south eastern Murray DarlingBasin, Australia, containing a network of 13 in-situmonitoring stations measuring soil moisture down to 90 cmdepth at 30-minute intervals. A six-year simulation wasperformed here at 5-km resolution and 30-minute time stepsusing locally measured meteorological forcing. The 25-kmscale AMSRE remotely-sensed surface soil moisture product(Owe et al., 2008), representing the top ~1-2 cm of soil, wasassimilated once daily (where available) into the top soil layerof CABLE (2.2 cm thick). Data from the 13 validation siteswere used in statistical analyses to test for significantimprovements to model predicted soil moisture over thedeeper root zone. Assessment of predicted evaporative fluxesfor a ~18-month period was also assessed at two locationswhere eddy covariance instruments were operating. Theimpact of different spatial scales between model resolutionand the AMSRE product on soil moisture was also analysed.Podest, ErikaA Multi-Scale Comparison of Palm SwampWetland Ecosystems Inundation State BetweenHigh and Low Microwave Remote SensingPodest, Erika 1 ; McDonald, Kyle 2, 1 ; Schroeder, Ronny 2, 1 ;Pinto, Naiara 3 ; Zimmermann, Reiner 4 ; Horna, Viviana 51. Water and Carbon Cycles Group, Jet PropulsionLaboratory, Pasadena, CA, USA2. Earth and Atmospheric Sciences, City College of NewYork, New York, NY, USA3. Geography, University of Maryland, College Park, MD,USA4. Institute of Botany and Botanical Gardens, University ofHohenheim, Hohenheim, Germany5. Ecological Botanical Gardens, University of Bayreuth,Bayreuth, GermanyPalm swamp wetlands are prevalent in the Amazonbasin, including extensive regions in northern Peru. Theseecosystems are characterized by constant surface inundationand moderate seasonal water level variation. Thecombination of constantly saturated soils, giving rise to lowoxygen conditions, and warm temperatures year-round canlead to considerable methane release to the atmosphere.Because of the widespread occurrence and expectedsensitivity of these ecosystems to climate change, knowledgeof their spatial extent and inundation state is crucial forassessing the associated land-atmosphere carbon exchange.Precise spatio-temporal information on palm swamps isdifficult to gather because of their remoteness and difficultaccessibility. Spaceborne microwave remote sensing is aneffective tool for characterizing these ecosystems since it issensitive to surface water and vegetation structure andallows monitoring large inaccessible areas on a temporalbasis regardless of atmospheric conditions or solarillumination. In this study we employ two types of multitemporalmicrowave data: 1) high-resolution (100 m) datafrom the Advanced Land Observing Satellite (ALOS) PhasedArray L-Band Synthetic Aperture Radar (PALSAR) to derivemaps of palm swamp extent and inundation from dualpolarizationfine-beam and multi-temporal HH-polarizedScanSAR through a decision-tree classification approachand 2) coarse resolution (25 km) weekly landscapeinundation products on derived by combining active andpassive microwave data from QuikSCAT and AMSR-E aspart of an Earth System Data Record MEaSURE’s project toassemble a database of global wetlands. We perform a multiscaleassessment between the coarse resolution landscapeinundation product and the high resolution SAR derivedpalm swamp distribution and inundation state product toensure information harmonization. The synergisticcombination of high and low resolution datasets will allowfor characterization of palm swamps and assessment of theirflooding status. This work has been undertaken partlywithin the framework of the JAXA ALOS Kyoto & CarbonInitiative. PALSAR data have been provided by JAXA/EORC.Portions of this work were carried out at the Jet PropulsionLaboratory, California Institute of Technology, undercontract with the National Aeronautics and SpaceAdministration.Pollard, BrianThe Surface Water / Ocean Topography Mission:High Resolution, Wide Swath Surface WaterTopography from SpacePollard, Brian 1 ; Vaze, Parag 1 ; Albouys, Vincent 2 ; Esteban-Fernandez, Daniel 1 ; Hughes, Richard 1 ; Rodriguez, Ernesto 1 ;Callahan, Phillip 1 ; Moshir, Mehrdad 11. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA2. Centre National d’Etudes Spaciales, Toulouse, FranceThe Surface Water / Ocean Topography (SWOT)mission, a partnership between NASA, CNES (CentreNational d’Etudes Spaciales) and the Canadian SpaceAgency, promises to provide first-of-their kindmeasurements of the extent and elevation of rivers and lakesto spatial scales as fine as 250m, as well as an unprecedentedview of mesoscale and sub-mesoscale ocean topography.These unique measurements are enabled by a Ka-band118

interferometric synthetic aperture radar, KaRIn, thatproduces centimetric-level elevation and brightness mapsacross a 100 km swath, sufficient to map the majority of theEarth in a 22-day orbital cycle. The SWOT mission alsoproposes to carry payload elements similar to the Jasonaltimetermissions, including a nadir altimeter andwater-vapor radiometer, as well as a GPS receiver and aDORIS receiver for precision orbit determination. In thispaper, we discuss many of the recent developments in thedesign of the mission. The flight system and mission systemarchitectures have been optimized to support the significantdata volumes of full resolution imaging (several TB/day)necessary for surface water imaging, while allowingflexibility to change the imaged areas as science needs evolve.The flight system architecture itself is designed around theboth the critical thermal and pointing stability requirementsof the elevation measurements, while also optimizing theaccommodation of the other instruments. We also discussthe development challenges facing the mission, which istargeting a 2019 launch.http://swot.jpl.nasa.gov/Pressel, Kyle G.Scale Invariance of the Water Vapor Field Observedby the Atmospheric Infrared SounderPressel, Kyle G. 1, 2 ; Collins, William D. 1, 21. Earth and Planetary Sciences, University of California,Berkeley, Berkeley, CA, USA2. Lawrence Berkeley National Laboratory, Berkeley, CA,USAThe Atmospheric Infrared Sounder (AIRS) providestwice daily physical retrievals of water vapor mass mixingratio with nearly global coverage in clear and partially cloudysky conditions. AIRS retrievals have nominally 50km nadirresolution which allows a characterization of the scaledependence of the water vapor field at scales smaller thanthe smallest resolved scales in modern global climate models(GCMs). The observed scale dependence can be used as anempirical basis for the assessment of the water vapor field inGCM simulations. We will present an analysis of the spatialscale dependence of the AIRS retrieved water vapor fieldthrough the first order structure function. The first orderstructure function relates the mean of spatial fluctuations,also know as increments, to scale. If the structure functionexhibits power law dependence on scale then the fieldexhibits a type of symmetry known as scale invariance. Manynatural systems exhibit scale invariance, and for turbulentflows the power law exponents which characterize the scaleinvariance appear to be a nearly universal property of broadclasses of flows. In particular we compute the first structurefunctions for scales between 50km and 500km of the AIRSlevel 2 water vapor field computed over 10 degree latitudelongitude boxes centered every 2 degrees latitude andlongitude between 60S and 60N. Special attention is given toassessing the isotropy of the increment field and quality ofstructure function power law fits. The results suggest thatthe atmospheric water vapor field exhibits widespread scaleinvariance with a power law fit explaining at least 90% ofvariance in the structure function in more than 99% ofcomputed structure functions on the 925hPa and 500hPapressure surfaces. Comparing structure functions computedusing increments in orthogonal directions allows theisotropy of the increment field to be investigated. Ourresults show that power law exponents exponents computedfrom structure functions in the satellite along and acrossdirections rarely exceed 0.1 in magnitude, which suggests theincrement field is approximately isotropic. The resultssuggest that power law exponents exhibit significant verticalvariability but very little horizontal variability. In particularit is shown that exponents vary from less than 1/2 in theboundary layer to greater than 1/2 in the middletroposphere. Also, it is shown that diurnal variations incomputed exponents are larger over land areas than over theocean and larger in the boundary layer than in the middletroposphere. The result that scaling exponents on aparticular pressure surface exhibit relatively little variabilitysuggests that a quasi-universal exponent may characterizethe scale invariance of water vapor on a particular pressuresurface. The smallest scale investigated in this presentationwas only limited by the resolution of AIRS, hence it is likelythat the observed scaling extends to even smaller scales. Thissuggests that the observed scaling may be used as a basis forthe stochastic parameterization of the water vapor field inGCMs. In situ measurements are need to confirm theseresults at smaller scales.Qiu, GuoyuEstimation of evapotranspiration (ET) and itspartition into evaporation (Es) and transpiration(Ec) based on three-temperature model andMODIS productsTian, Fei 1 ; Qiu, Guoyu 2 ; Yang, Yonghui 31. Beijing Normal University, Beijing, China2. Peking University, Shenzhen, China3. Chinese Academy of Sciences, Shijiazhuang, ChinaET is one of the most important land surface processesfor terrestrial ecosystems that can help us to understandhydrological processes, and manage water resources, soresearches on ET are focused by scientists around theworld.The Heihe River Catchment is the second largestinland river catchment in northwestern China. Due tooverexploitation of water resources, environmental worsenedand downstream was transforming into one of China’s“sandstorm cradles”. To restore the ecosystem, EcologicalWater Conveyances Project (EWCP) has been conducted.While how much water is used for oasis sustainabledevelopment is not clear, an accurate estimate oftranspiration is necessary. So three temperature model (3Tmodel) based on MODIS products (MOD11A2, MOD13A2,MCD43B1) were used to evaluate evapotranspiration andpartition it into evaporation and transpiration.Resultsindicated that yearly averaged ET, Es and Ec distributiondecreased from upstream Qilian mountain area (more than600 mm/a) to the downstream desert region in the north119

(less than 100 mm/a). Furthermore, daily ET varied from0.23 mm/d to 1.27 mm/d. 3T modeled ET was validatedwith energy balance equation, results showed that the meanabsolute error (MAE) was 0.34 mm/d, which indicated that3T model is a simple and an accurate way to estimate ET, hasgood prospects for RS applications.9-year averaged ET estimated by 3T model in Heihe RiverCatchment.Qualls, Russell J.Use of MODIS Snow-Covered-Area to DevelopHistorical, Current and Future Snow DepletionCurves for Snowmelt Runoff ModelingQualls, Russell J. 1 ; Arogundade, Ayodeji 11. Biological & Agricultural Engineering, University ofIdaho, Moscow, ID, USAQuantification of snow-covered area and its declinethroughout the snowmelt season is an important input forsnowmelt runoff models in the prediction of runoff andsimulation of streamflow. Several remote sensing methodsof snowcover mapping exist today that can be used indetermining the progressive reduction of snow cover duringsnowmelt; however, some of these methods of snowmapping, such as the Moderate-Resolution ImagingSpectroradiometer (MODIS) satellite sensor, are relativelynew. The relative recency of MODIS which launched in 1999and other new remote sensing methods, limit their direct usein developing historical snow depletion curves. Nevertheless,historical depletion curves are important for general modelvalidation purposes, and also for studying impacts ofvarying or changing climate on snowmelt and surfacerunoff. For the latter purpose, historical depletion curves areuseful both for establishing a baseline, and for testingimpacts of perturbations to climate such as associated withclimate change scenarios. These historical depletion curves,among many other uses, provide snow cover information forsnowmelt runoff modeling in hydrologic models such assnowmelt runoff model (SRM). Based on numerousobservations in the literature that snowmelt occurs in arepeating patterns, albeit shifted and/or accelerated ordecelerated in time, from one year to the next, a method ispresented in this study that makes use of the availableremotely sensed MODIS data and concurrent ground basedSNOTEL data to construct a single dimensionless snowdepletion curve that is subsequently used with historicalSNOTEL data to reconstruct snow depletion curves for baseperiods preceding the availability of current satellite remotesensing, and for future periods associated with alteredclimate scenarios; the method may also be used in anycurrent snowmelt season to forecast the snowmelt andimprove streamflow forecasts.Separation of evaporation (Es) and transpiration (Ec) based on 3Tmodel.120Rango, AlbertHydrology with Unmanned Aerial Vehicles (UAVs)Rango, Albert 1 ; Vivoni, Enrique R. 21. Jornada Experimental Range, USDA-ARS, Las Cruces,NM, USA2. School of Earth and Space Exploration & School ofSustainable Engineering and Built Environment, ArizonaState University, Tempe, AZ, USAHydrologic remote sensing currently depends onexpensive and infrequent aircraft observations for validationof operational satellite products, typically conducted duringfield campaigns that also include ground-basedmeasurements. With the advent of new, hydrologically-

elevant satellite missions, such as the Soil Moisture ActivePassive (SMAP) mission, there is a pressing need for morefrequent, less expensive techniques for validating satelliteretrievals that can be integrated with ground sensornetworks. Unmanned Aerial Vehicles (UAVs) provideintermediate to high resolutions and spatial coverage thatcan fill the gap between satellite observations and groundbasedsensors at resolutions superior to manned aircraftdata. Their use in the hydrologic community for obtainingvariables that can serve as input or validation fields forhydrologic models is an emerging area that deserves greaterattention. The development of these tools for field toregional-scale hydrologic sensing and modeling is furtherpunctuated by the potential for reduced long-term fundingfor satellite and manned aircraft missions. In this work, wepresent our recent experiences with the use of UAVs forhydrologic assessments and modeling at the JornadaExperimental Range in Las Cruces, New Mexico. Wedocument the capability of UAV platforms for obtaining veryhigh resolution imagery, digital elevation models andvegetation canopy properties over an experimental watershedequipped with a distributed sensor network of water, energyand carbon states and fluxes. We also draw attention to theimportant interaction between UAV products and theirdirect use in hydrologic models at the watershed scale. Froma hydrologic perspective, the development of UAV techniquesshould be driven by the necessary inputs to a hydrologicmodel or the potential for utilizing the imagery to test themodel predictions. This co-development can ensure thatremote sensing advances make their way into products thatdirectly quantify the hydrologic cycle and improve predictiveskill at a range of resolutions. We present results from theapplication of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS) to theinstrumented upland watershed to highlight the challengesand benefits of these tailored remote sensing products. Wealso discuss how UAVs could be used to validate upcomingproducts from satellite missions for the purpose ofimproving their routine use in a range of watershed modelsapplied at local to regional scales.Ratnayake, Amila S.GIS-based hydrological predictions andestimations of hydropower potential: Implicationsfor flood risk mitigation at Gin River, Sri LankaRatnayake, Amila S. 1 ; Pitawala, Amarasooriya 11. University of Peradeniya, Peradeniya, Sri LankaThe most of the primary civilizations of world emergedin or near river valleys or floodplains. The river channels andfloodplains are single hydrologic and geomorphic systemand failure to appreciate the integral connection betweenfloodplains and channel underlies many socioeconomic andenvironmental problems in river management today.However it is a difficult task of collecting reliable fieldhydrological data. Under such situations either synthetic orstatistically generated data were used for hydraulicengineering designing and flood modeling. Thefundamentals of precipitation-runoff relationship throughsynthetic unit hydrograph for Gin River basin were preparedusing the method of the Flood Studies Report of theNational Environmental Research Council, United Kingdom(1975). The Triangular Irregular Network model wasconstructed using Geographic Information System (GIS) todetermine hazard prone zones. The 1:10,000 and 1:50,000topography maps and field excursions were also used forinitial site selection of mini-hydro power units anddetermine flooding area. The turbines output powergenerations were calculated using the parameters of net headand efficiency of turbine. The peak discharge achieves within4.74 hours from the onset of the rainstorm and 11.95 hourstime takes to reach its normal discharge conditions of GinRiver basin. Stream frequency of Gin River is 4.56(Junctions/ km2) while the channel slope is 7.90 (m/km).The regional coefficient on the catchment is 0.00296. Higherstream frequency and gentle channel slope were recognizedas the flood triggering factors of Gin River basin and otherparameters such as basins catchment area, main streamlength, standard average annual rainfall and soil do notshow any significant variations with other catchments of SriLanka. The flood management process, including control offlood disaster, prepared for a flood, and minimize it impactsare complicated in human population encroached andmodified floodplains. The modern GIS technology has beenproductively executed to prepare hazard maps based on theflood modeling and also it would be further utilized fordisaster preparedness and mitigation activities. Five suitablehydraulic heads were recognized for mini-hydro power sitesand it would be the most economical and applicable floodcontrolling hydraulic engineering structure considering allmorphologic, climatic, environmental and socioeconomicproxies of the study area. Mini-hydro power sites alsoutilized as clean, eco friendly and reliable energy source(8630.0 kW). Finally Francis Turbine can be employed as themost efficiency turbine for the selected sites bearing in mindof both technical and economical parameters.Raupach, Michael R.Interactions Between the Terrestrial Water andCarbon Cycles INVITEDRaupach, Michael R. 1 ; Haverd, Vanessa 11. Marine and Atmospheric Research, CSIRO, Canberra,ACT, AustraliaAt land surfaces, one of the great crossroads in the EarthSystem, terrestrial water and carbon cycles exert profoundinfluences on one another. Transpiration and net primaryproduction (NPP) of carbon in biomass are controlled by thesame fundamental resource availabilities (light, water andnutrients) and interact through a shared stomatal pathway.This paper explores two consequences of the interactionsbetween terrestrial water and carbon cycles. First, at regionalscales, information about the carbon cycle helps to constrainthe water cycle, and vice versa. This is an issue of informatics,not dynamics. For example, evapotranspiration (ET) andrunoff (precipitation ET) measurements are powerful121

constraints on carbon NPP, and information about NPPprovides significant constraints on the partition of ET intotranspiration and soil evaporation. We present recent workon the Australian water and carbon cycles in which a model(CABLE-SLI-CASAcnp) is constrained jointly withobservations of streamflow from several hundred gaugedcatchments, eddy flux measurements of ET and NEE (netecosystem exchange of carbon), remotely sensed data onvegetation state, and data on carbon pools (both in-situ andremotely sensed). As well as yielding a consistent picture ofwater and carbon exchanges, these joint constraints suggestthat on the Australian continent, a predominantly semi-aridregion, over half the water loss through ET occurs throughsoil evaporation and bypasses plants entirely. Second, againat regional scale, human forcings of carbon and water cyclespropagate into each other, and both are affected by largescaleclimate forcing. This is a question of dynamics ratherthan informatics. One manifestation is the joint response ofrunoff to warming, CO2 increase and precipitation changes.We use sensitivity tests with the CABLE-SLI-CASAcnp modelto explore this question for the Australian continent.Reager, John T.Effective global soil parameters from GRACE andimpact on land surface simulationsReager, John T. 1 ; Lo, MInhui 2 ; Blum, David 2 ; Famiglietti,James 1, 2 ; Rodell, Matthew 31. Earth Systems Science, University California, Irvine,Irvine, CA, USA2. UC Center for Hydrological Modeling, Irvine, CA, USA3. NASA GSFC, Greenbelt, MD, USAEffective values of soil depth and soil water holdingcapacity are critical hydrological variables in land surfacemodels. In global-scale simulations, these spatially variableparameters are often poorly represented due to observationaland scaling limitations. Some parameters, such as porosity,matric potential and soil conductivity, are based empiricallyon two-dimensional maps of soil types. Other critical soilcharacteristics however, such as soil layering and depth tobedrock, are assumed to be homogeneous in space, imposingan unrealistic constraint on climate model estimates ofgroundwater recharge and water storage in unconfinedaquifers, limiting the reliability of projections of future wateravailability. GRACE observations of terrestrial water storageanomaly are well-suited for estimating the effective range ofsuch land surface model parameters as soil depth and waterholding capacity, based on the spatial variability of thestorage signal. Here we combine GRACE storageobservations with GLDAS output for surface, canopy andsnow water, to derive a 1-degree spatially variable sub-surfaceactive water holding capacity. We use this result with globalestimates of porosity from the FAO Harmonized SoilDatabase to produce an effective 1-degree global active soillayer depth. The calculated depth and water holding capacityvariables can be introduced directly into a model, or used toderive other model parameters. In this study, we evaluate thesensitivity of numerical simulations to realistic waterholding capacity by incorporating our new estimates intothe CLM. Impacts on evaporation and surface radiation inoffline simulations and improvements to simulatedterrestrial hydroclimatology are discussed.Reeves, JessicaUncertainty in InSAR deformation measurementsfor estimating hydraulic head in the San Luis Valley,ColoradoReeves, Jessica 1 ; Knight, Rosemary 1 ; Zebker, Howard 11. Stanford University, Stanford, CA, USAThe San Luis Valley (SLV) is an 8000 km2 region insouthern Colorado that is home to a thriving agriculturaleconomy. The valley is currently in a period of extremedrought, with county and state regulators facing thechallenge of developing appropriate management policiesfor both surface water and ground water supplies.Legislation passed in 2004 requires that hydraulic head levelswithin the confined aquifer system stay within the rangeexperienced in the years 1978 - 2000. While somemeasurements of hydraulic head exist, greater spatial andtemporal sampling would be very valuable in understandingthe behavior of the confined aquifer system. Interferometricsynthetic aperture radar (InSAR) data provide spatially densemaps of surface deformation, with one pixel representing thetime series deformation of a 50 m by 50 m area on theground. Our long-term goal is to use these deformation timeseries to estimate hydraulic head. Here we present theanalysis of InSAR data from the European Space Agency’sERS-1 and ERS-2 satellites, using 31 acquisitions archivedfrom 1992 - 2001. We applied small baseline subset (SBAS)analysis to create a time series of deformation that issampled at the 31 acquisition times. We find that theseasonal deformation measured by InSAR mimics hydraulichead measurements made in the confined aquifer system.These measurements can be used to inform groundwatermanagers about the state of the groundwater system.However, at present little work has been done to quantify theuncertainty associated with InSAR image sequences ofaquifers. We have quantified the uncertainty in the InSARdeformation measurement that is caused by thedecorrelation of the two SAR signals. The correlation of theSAR signals is affected by: the local surface slope, theproperties of the surface, the time between two acquisitionsand the change in satellite position between twoacquisitions. We first quantified the variance and covarianceof the interferometric phase for all interferograms. We thenpropagated this uncertainty through the SBAS processingchain to produce the variance of the final estimates ofdeformation. We have shown that the uncertainty in thedeformation estimated at each acquisition time depends ona) the correlation of the SAR signals throughout time, andb) the number of interferograms used to estimate thedeformation at a given acquisition time. This understandingof the uncertainty in the InSAR measurement will allow usto rigorously assess how InSAR data can best be used to122

support decision-making related to groundwatermanagement.Reichle, RolfAMSR-E Brightness Temperature Estimation overNorth America Using a Land Surface Model and anArtificial Neural NetworkForman, Barton 1, 2 ; Reichle, Rolf 1 ; Derksen, Chris 31. Global Modeling and Assimilation Office, NASA GSFC,Greenbelt, MD, USA2. NASA Postdoctoral Program, Oak Ridge AssociatedUniversities, Oak Ridge, TN, USA3. Climate Processes Branch, Environment Canada,Downsview, ON, CanadaAn artificial neural network (ANN) is presented for thepurpose of estimating passive microwave (PMW) emissionfrom snow covered land in North America. The NASACatchment Land Surface Model (Catchment) is used todefine snowpack properties; the Catchment-based ANN isthen trained with PMW measurements acquired by theAdvanced Microwave Scanning Radiometer (AMSR-E). Theintended use of the ANN is for eventual application as apredicted measurement operator in an ensemble-based dataassimilation (DA) framework to be presented in a follow-onstudy. The details shown here fulfill the necessaryrequirement of demonstrating the feasibility and efficacy ofthe ANN. A comparison of ANN output against AMSR-Emeasurements not used during training activities as well as acomparison against independent PMW measurementscollected during airborne surveys demonstrates thepredictive skill of the ANN. When averaged over the studydomain for the 9-year study period, computed statistics(relative to AMSR-E measurements not used during training)for multiple frequencies and polarizations yielded a nearzerobias, a root mean squared error less than 10K, and ananomaly correlation coefficient of approximately 0.7. TheANN demonstrates skill at reproducing brightnesstemperatures during the ablation phase when the snowpackis ripe and relatively wet. The ANN demonstrates evengreater skill during the accumulation phase when thesnowpack is relatively dry. Overall, the results suggest theANN should serve as an effective predicted measurementoperator that is computationally efficient at the continentalscale.Renzullo, Luigi J.An on-going intercomparison of near real-timeblended satellite-gauge precipitation estimates forAustraliaRaupach, Tim 1 ; Renzullo, Luigi J. 1 ; Chappell, Adrian 11. Commonwealth Scientific and Industrial ResearchOrganisation, Canberra, ACT, AustraliaSatellite-derived precipitation estimates have beenexamined as a useful auxiliary field to aid in theinterpolation of daily rain gauge observations and provideimproved estimates in the largely ungauged parts of123Australia. Blended satellite-gauge precipitation estimatesaim to produce a precipitation field that takes advantage ofboth the accuracy of gauge observations and the spatialcoverage of satellite estimates. We present results from thefirst two years of operation of a system that performs an ongoingintercomparison of near real-time blendedsatellite-gauge precipitation estimates for Australia. On acontinuing basis, we compare daily outputs of fifteenprecipitation products. Performance is measured using anovel technique in which outputs produced using near realtimegauge data are compared to an independent validationdataset of post real-time gauge observations. These post realtimeobservations are made on the day in question but theobservations only become available some days later. Oursystem automatically generates daily precipitation outputs,produces a range of performance statistics as post real-timeobservations become available, and publishes the results ona web portal. The results show extremely similarperformance between techniques, with the best techniquedepending on which specific statistic is examined. Thesystem is on-going and continues to amass a valuable archiveof performance statistics starting in mid-2009.Renzullo, Luigi J.Assimilating satellite-derived soil moisturealongside streamflow into the Australian waterresources assessment systemRenzullo, Luigi J. 1 ; Van Dijk, Albert I. 11. CSIRO, Canberra, ACT, AustraliaThe Australian water resources assessment (AWRA)system provides comprehensive water balance estimates thatunderpin the Australian Bureau of Meteorology’s nationalwater accounts and water resource assessments. The AWRAlandscape model component (AWRA-L) was developed toprovide daily estimates of water storages and fluxes at 0.05°resolution across the continent, constrained using a varietyof ground- and satellite-based observations and derivedproducts. Data used in model development and calibrationinclude: evaporative fluxes from tower measurements,streamflow and deep drainage observations, moderateresolution remotely-sensed vegetation properties (AVHRR,MODIS sensors), basin-scale terrestrial water storage(GRACE) and soil moisture estimates from passive (AMSR-E,TRMM) and active (ASAR GM) sensors. This paper describessome of the work towards an assimilation system for AWRA-L and examines the effect of assimilating streamflow andremotely-sensed soil moisture. The ensemble Kalman filter(EnKF) was applied in both lumped-catchment and gridbasedmodes. The EnKF lumped-catchment approachexamined the assimilation of AMSR-E soil moisture (SM)retrievals and/or streamflow observations for 719catchments across Australia. The EnKF grid-based approachexamined model estimates at 0.05° resolution across theMurrumbidgee catchment (New South Wales). In both cases1980–2005 was used as a spin-up period, and satellite SMwas linearly scaled using mean and variance of the modeltop-layer soil water storage for 2002–2005. The assimilation

was run for 1 Jan 2006 to 31 Dec 2010. At each time step,100-member ensembles of model states were generated byperturbing meteorological forcing data (random butcorrelated errors added to precipitation, shortwave radiationand air temperature) and a small subset of modelparameters. Assimilation performance of AWRA-L inlumped-catchment mode was based on comparing estimatedand observed streamflow for each catchment. As expected,assimilation of streamflow gave best fit to these observations(Nash-Sutcliff scores 0.5 – 0.8). Simultaneous assimilation ofboth streamflow and SM achieved nearly identical results tothat of streamflow alone - whilst improving agreement withAMSR-E SM. This suggests that SM can be assimilatedwithout degrading streamflow estimation, with the potentialof benefiting estimation of other water balance components(this needs to be investigated further). Preliminaryexamination of the gridded SM assimilation results showedthat AWRA-L estimates agree considerably better with theAMSR-E SM data than the open loop simulations. A moredetailed evaluation is planned which involves comparisonsof the SM fields against surface SM monitoring networks,and comparisons of the analysed model storage andvegetation states against independent GRACE-derivedstorages and MODIS/AVHRR vegetation data, respectively.Future work will also evaluate alternative soil moisture datastreams, e.g. SMOS, SMAP, ASAR and ASCAT. We envisagedthat dynamic assimilation of satellite data into AWRA-L willresult in better spatial and temporal representations of themodels water balance components for the Australiancontinent.Rezaie Boroon, HassanLinking Groundwater Quality and Quantity: AnAssessment of Satellite-Based GroundwaterStorage Anomalies From GRACE Against GroundMeasurements of Contaminants in CaliforniaRezaie Boroon, Hassan 1 ; Fisher, Josh B. 21. Geosciences and Environment, California StateUniversity, Los Angeles, Los Angeles, CA, USA2. Water & Carbon Cycles Group, JPL, Pasadena, CA, USAGroundwater primarily supports agriculture inCalifornia, as well as sustains a wide diversity of ecosystemsand consumptive use, but pumping is occurring faster thanreplenishment. At the same time, contaminants from pointand non-point sources including fertilizers and pesticides areinfiltrating into the groundwater, becoming increasinglyconcentrated as water is extracted. We compared space-basedobservations of groundwater anomalies from California’sSan Joaquin Valley (SJV) using the Gravity Recovery andClimate Experiment (GRACE) against measurements of 42organic and inorganic chemicals from 41667 wells in SJVfrom 2003 to 2010. Preliminary results show strongcorrelations with groundwater depletion against increasingchlorine (r2=0.78), boron (r2=0.88), and but negligibleagainst decreasing benzene (r2=0.03). The results are thefirst to link space-based groundwater quantity withgroundwater quality.Rhines, AndrewTropical Loading Patterns Associated withAtmospheric Rivers: Lagrangian Diagnosis andProspects for Remote DetectionRhines, Andrew 11. Earth and Planetary Sciences, Harvard University,Cambridge, MA, USAAtmospheric Rivers (ARs, also known as tropicalmoisture export events) constitute an important and illunderstoodbranch of the hydrologic cycle. Theirclimatological characteristics in midlatitudes have beenexplored in previous studies (e.g., Zhu and Newell [1998],Ralph et al. [2004], and others), and while ARs are clearlyconnected to precipitation extremes, little attention has beenpaid to their tropical origins. Basic questions remainunanswered: Is the water vapor present in filaments of moisttropical air in ARs dynamically important, or is it simplyadvected by an existing midlatitude system? What role dotropical SSTs play in the development of ARs? Does ENSOmodulate their frequency, their typical location, or both? Inthis study, I generate a Lagrangian climatology of tropicalmoisture export from NCEP reanalyses, and illustrate therole played by tropical moisture anomalies in setting thecharacteristics of these events. Focusing on the Pacific sectorand ARs near North America, I find that that sub-annualvariability from SST anomalies, annual variability from theseasonal movement of the ITCZ, and inter-annual variabilityfrom ENSO all strongly influence tropical moisture exportin important ways. The frequency and strength of PacificARs is found to depend mainly on SSTs in the warm pool,while the influence of ENSO upon the distribution oftropical SST anomalies controls their location. Both factorsare important for the prediction of extreme rainfall eventsalong the west coast of North America. The strongcorrespondence between filamentary tropical moistureexport and satellite-based water vapor soundings elicitscomparison between the modeled climatology and satelliteimagery of these events. I characterize the degree to whichthe Lagrangian and satellite diagnostics are in agreement,and where their complementary properties might lead tomore robust event detection.Richey, Alexandra S.Quantifying Water Stress Using Total WaterVolumes and GRACERichey, Alexandra S. 1 ; Famiglietti, James S. 1, 21. Civil and Environmental Engineering, University ofCalifornia - Irvine, Irvine, CA, USA2. Earth Systems Science, University of California - Irvine,Irvine, CA, USAWater will follow oil as the next critical resource leadingto unrest and uprisings globally. To better manage thisthreat, an improved understanding of the distribution ofwater stress is required today. This study builds uponprevious efforts to characterize water stress by improving124

oth the quantification of human water use and thedefinition of water availability. Current statistics on humanwater use are often outdated or inaccurately reportednationally, especially for groundwater. This study usesremote sensing to improve these estimates. We use NASA’sGravity Recovery and Climate Experiment (GRACE) toisolate the anthropogenic signal in water storage anomalies,which we equate to water use. Water availability hastraditionally been limited to “renewable” water, whichignores large, stored water sources that humans use. Wecompare water stress estimates derived using eitherrenewable water or the total volume of water globally. We usethe best-available data to quantify total aquifer and surfacewater volumes, as compared to groundwater recharge andsurface water runoff from land-surface models. The workpresented here should provide a more realistic image ofwater stress by explicitly quantifying groundwater, definingwater availability as total water supply, and using GRACE tomore accurately quantify water use.Rittger, Karl E.Assessment of Viewable and Canopy AdjustedSnow Cover from MODISRittger, Karl E. 1 ; Painter, Thomas H. 2 ; Raleigh, Mark S. 3 ;Lundquist, Jessica D. 3 ; Dozier, Jeff 11. Bren School of Env. Science, Univ of Calif- Santa Barbara,Santa Barbara, CA, USA2. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA3. Civil and Environmental Engineering, University ofWashington, Seattle, WA, USACharacterization of snow is critical for understandingEarth’s water and energy cycles. The cryosphere’s response toforcings largely determines Earth’s climate sensitivity tochanges in atmospheric composition, and one-fifth ofEarth’s population depends on snow or glaciers for waterresources. Maps of snow from MODIS have seen growing usein investigations of climate, hydrology, and glaciology, butthe lack of rigorous validation of different snow mappingmethods compromises these studies. We examine threewidely used MODIS snow products: the “binary” (i.e. snowyes/no) global snow maps, MOD10A1 binary, that relies onthe normalized difference snow index (NDSI); a regressionbasedMODIS fractional snow product, MOD10A1fractional, that relies on an empirical relationship withNDSI; and a physically-based fractional snow product,MODSCAG, that relies on spectral mixture analysis. Wecompare them to maps of snow obtained from LandsatETM+ data to evaluate viewable snow cover. The assessmentuses 172 images spanning a range of snow and vegetationconditions, including the Colorado Rocky Mountains, theUpper Rio Grande, California’s Sierra Nevada, and the NepalHimalaya. MOD10A1 binary and fractional fail to retrievesnow in the transitional periods during accumulation andmelt while MODSCAG consistently maintains its retrievalability during these periods. Fractional statistics show theRMSE for MOD10A1 fractional and MODSCAG are 0.23and 0.10 averaged over all regions. MODSCAG performs themost consistently through accumulation, mid-winter andmelt with median differences ranging from –0.16 to 0.04while differences for MOD10A1 fractional range from –0.34to 0.35. MODSCAG maintains its performance over all landcover classes and throughout a larger range of land surfaceproperties. Estimating snow cover in densely vegetated areasfrom optical remote sensing remains an outstandingproblem. We use a network of ground temperature sensorsto monitor daily snow presence in the Sierra Nevada in threesites with varying forest canopy density. For MODSCAG, weestimate snow cover under the canopy using standardmethods, adjusting with the daily fractional vegetation fromthe MODSCAG algorithm. These adjustments are superiorto static maps such as the National Land Cover Datasetbecause both fractional vegetation and fractional snow covervary as a function of MODIS view angle and season.MOD10A1 viewable snow cover is compared directly to thefield data without vegetation corrections because of itssizeable overestimates in forested areas. Characterizingviewable snow cover by spectral mixing is more accurate thanempirical methods based on the normalized difference snowindex, both for identifying where snow is and is not and forestimating the fractional snow cover within a sensor’sinstantaneous field-of-view. Estimating canopy adjustedsnow cover should rely on our best estimates of the viewablesnow cover to produce reliable and defendable results.Ascertaining the fractional value is particularly important inmountainous terrain and during spring and summer melt.Rodell, MatthewIntegrating Data from GRACE and OtherObserving Systems for Hydrological Research andApplicationsRodell, Matthew 1 ; Famiglietti, James S. 2 ; McWilliams, EricB. 3 ; Beaudoing, Hiroko K. 1, 4 ; Li, Bailing 1, 4 ; Zaitchik,Benjamin F. 5 ; Reichle, Rolf H. 6 ; Bolten, John D. 11. Hydrological Sciences Laboratory, NASA/GSFC,Greenbelt, MD, USA2. Earth System Science, UC Irvine, Irvine, CA, USA3. Atmospheric and Oceanic Science, University ofMaryland, College Park, MD, USA4. Earth System Science Interdisciplinary Center, Universityof Maryland, College Park, MD, USA5. Earth and Planetary Sciences, Johns Hopkins University,Baltimore, MD, USA6. Global Modeling and Assimilation Office, NASA/GSFC,Greenbelt, MD, USAThe Gravity Recovery and Climate Experiment (GRACE)mission provides a unique view of water cycle dynamics,enabling the only space based observations of water on andbeneath the land surface that are not limited by depth.GRACE data are immediately useful for large scaleapplications such as ice sheet ablation monitoring, but theyare even more valuable when combined with other types ofobservations, either directly or within a data assimilationsystem. Here we describe recent results of hydrological125

esearch and applications projects enabled by GRACE. Theseinclude the following: 1) global monitoring of interannualvariability of terrestrial water storage and groundwater; 2)water balance estimates of evapotranspiration over severallarge river basins; 3) NASA’s Energy and Water Cycle Study(NEWS) state of the global water budget project; 4) droughtindicator products now being incorporated into the U.S.Drought Monitor; 5) GRACE data assimilation over severalregions.Rodriguez, ErnestoThe Measurement of Reach-Averaged Discharge bythe SWOT MissionRodriguez, Ernesto 1 ; Neal, Jeffrey 2 ; Bates, Paul 2 ;Biancamaria, Sylvain 3 ; Mognard, Nelly 31. Jet Propulsion Laboratory/Cal Tech, Pasadena, CA, USA2. School of Geographical Sciences, University of Bristol,Bristol, United Kingdom3. LEGOS, Toulouse, FranceThe proposed NASA/CNES Surface Water and OceanTopography (SWOT) mission will collect globalmeasurements of elevation and extent for all continentalwater bodies, as well as floodplain topography. From thesedata, the calculation of storage change will bestraightforward, and the prime hydrology objective for themission. In addition to storage change, globally distributedestimates of discharge can contribute significantly to theunderstanding of the water cycle and its geographicalvariability. There are two primary routes for obtainingdischarge from the SWOT measurements: 1) assimilation ofelevations and water extent into a dynamic model; or, 2)estimation of discharge using the SWOT observables andManning’s equation, to obtain an estimate of the dischargeat the time of observation. The second approach has theadvantage that it is less contaminated by limitations in thedynamic models, mostly due to the SWOT temporalsampling pattern, and we will examine it here. In the firstpart, we show how from the SWOT measurements, estimatescan be obtained for the terms in Manning’s equation: slope,river cross-section, and width. We also show that stableestimates can be obtained by averaging along the river reach.(A part of the channel bathymetry will not be measured bySWOT directly, and its estimation from SWOT time series isaddressed by Rodriguez and Durant in a separatepresentation in this conference). We next show that, giventhe noise level in the SWOT measurements, a naïveapplication of Manning’s equation will result in estimates ofdischarge that have unacceptable distributions, includinglarge relative biases and variances. To overcome thislimitation, we introduce the concept of reach averaging theSWOT observables, and show that, after sufficient averaging(from 1 km to 10 km), Gaussian estimates with acceptablenoise can be obtained by replacing these reach averagedquantities in Manning’s equation. However, due to thenonlinear relation between the SWOT observables and thedischarge, it will certainly be the case that using the reachaveragedSWOT observables will not result in a validestimate of the reach averaged discharge. However, byexamining the effects of averaging on the St Venantequations, we show that a functionally identical relationshipexists between the reach averaged discharge and the reachaveraged parameters: the only change that needs to be madeis an adjustment of the friction coefficient to account forthe fluctuations ignored by the reach averaging. We obtainan analytic expression for the scaled friction coefficient. Thisanalytic expression is then validated by comparison againstthe results from numerical models for a set of different rivertypes. We conclude that the estimation of reach-averagedriver discharge at the time of observation is viable using theSWOT data alone, independent of an underlying dynamicmodel. These globally distributed estimates of instantaneousdischarge, which can be obtained every

parameter inversion of the time invariant data from theSWOT time series. Reach averaging also significantly reducesthe number of parameters that need to be inverted. Weproceed to the parameter inversion by studying inversionusing Maximum Likelihood Estimation (MLE), Maximum aPosteriori (MAP) estimation, and full Bayesian estimation ofthe most likely values (and their variances) using MarkovChain Monte Carlo (MCMC) techniques. The first twoinversion techniques require only search for the maximum ofa cost function, while the third explores the entire space ofpossible solutions but is slower. Among the questions weaddressed in this study are: how long a time series is requiredfor suitable parameter inversion? How does the addition ofprior information stabilize the retrieved parameters? Howwill the inversion work in the presence of significantunknown lateral discharges? The work presented hereextends the work of Durand et al. (2010, JSTARS) to a widerset of conditions, including non-rectangular channels andlateral inputs, and to the joint retrieval of both bathymetryand friction coefficient. It is the first step towards definingthe discharge algorithm that will be implemented by theproposed SWOT mission.Romaguera, MireiaComparison of remote sensing ET estimates andmodel simulations for retrieving irrigationRomaguera, Mireia 1, 2 ; Krol, Maarten S. 2 ; Salama, Mhd. S. 1 ;Hoekstra, Arjen Y. 2 ; Su, Zhongbo 11. Faculty of Geo-Information Science and EarthObservation, Department of Water Resources, Universityof Twente, Enschede, Netherlands2. Faculty of Engineering Technology, Department of WaterEngineering and Management, University of Twente,Enschede, NetherlandsThe analysis of evapotranspiration (ET) plays animportant role to assess the usage of water resources andirrigation practices. In this paper, we propose an innovativemethod based on ET for identifying irrigated areas andquantifying the blue evapotranspiration (ETb), i.e.evapotranspiration of irrigation water from the field. DailyET estimates from the Meteosat Second Generation (MSG)satellites were compared with ET values from the GlobalLand Data Assimilation System (GLDAS) with the Noahmodel. Since the latter do not account for extra water supplydue to irrigation, it is expected that they underestimate ETduring the cropping season in irrigated areas. The biasbetween model simulations and remote sensing observationswas estimated using reference targets of rainfed croplands ona yearly basis. The study region (Europe and Africa) wasclassified based on vegetation cover (using the NormalizedDifference Vegetation Index as a proxy) and MSG viewingangles to define the reference biases. ETb was obtained forcroplands in Europe and Africa for the year 2010. Theanalysis of the daily and yearly ETb values showed that ourmethod identified irrigation when yearly values were higherthan 50mm. The ETb results were compared with existingliterature and with in situ point irrigation values.Rosen, Paul A.DESDynI-R Mission Concept Overview andPossible Uses for Hydrological Sciences andApplicationsRosen, Paul A. 1 ; Nghiem, Son V. 11. Radar Science & Engineering, Jet Propulsion Laboratory,Pasadena, CA, USAEarth’s land surface is constantly changing andinteracting with its interior and atmosphere. In response tointerior forces, plate tectonics deform the surface, causingearthquakes, volcanoes, mountain building, and erosion,including landslides. Human and natural forces are rapidlymodifying terrestrial ecosystems, causing among otherthings reductions in species diversity and endangeringsustainability. Similarly ice sheets, sea ice, and glaciers areundergoing dramatic changes. Increasing rates of land icemelt is the primary contributor to eustatic sea level rise.DESDynI was a mission concept recommended by theNational Academy of Sciences in 2007 [1] to address thesechanges. NASA continues to study affordable ways toimplement the mission, while preserving as much of theability to observe these changes over the life of the missionas possible. The proposed primary mission objectives forDESDynI would be to: 1) Determine the likelihood ofearthquakes, volcanic eruptions, and landslides throughdeformation monitoring; 2) Characterize the globaldistribution and changes of vegetation abovegroundbiomass and ecosystem structure related to the globalcarbon cycle, climate and biodiversity; and 3) Predict theresponse of ice masses to climate change and impact on sealevel. DESDynI would attempt, in an affordable manner, tosystematically and globally study the solid Earth, the icemasses, and ecosystems, all of which are too sparselysampled to address many important global scale problems ingeohazards, carbon and climate. In addition to theseprimary science goals, DESDynI would provide observationsthat would greatly improve our monitoring of groundwater,hydrocarbon, and sequestered CO2 reservoirs, as well aswatersheds and coastal regions with frequent fine-resolutionpolarimetric radar imaging. These data would supporthydrological sciences as well as potentially serving a role inthe nation’s systematic monitoring of areas that are hazardprone due to water related issues. This paper describes thecurrent status of DESDynI mission studies, particularlyfrom the point of view of the expected options for sciencereturn depending on the scoped capabilities proposed forthe mission. Possible applications to hydrology wouldinclude, for example, monitoring of deformation due toextraction or injection of ground water in urban andsuburban aquifers, high-resolution measurement of soilmoisture to complement projected SMAP observations,detection of surface water change due to liquefaction, lakeand reservoir monitoring (including those in cold landregions), river freeze-up and break-up tracking, wetland andflood inundation mapping, global drought monitoring, andmapping of dams and levees and their changes over time.With the capability of weekly global coverage regardless of127

cloud cover and darkness at a resolution better than 10 m,which can resolve the hill-slope scale accounting for theNyquist requirement (~25 m), DESDynI could provideobservations crucial for an array of hydrological scienceresearch and applications. [1] National Research Council.2007. Earth Science and Applications from Space: NationalImperatives for the Next Decade and Beyond. The NationalAcademies Press, Washington, D.C.Rudiger, ChristophSMOS Soil Moisture Validation in AustraliaRudiger, Christoph 1 ; Monerris, Alessandra 1 ; Mialon,Arnaud 2 ; Olivier, Merlin 2 ; Walker, Jeffrey P. 1 ; Kerr, Yann H. 2 ;Kim, Edward J. 31. Dept. of Civil Engineering, Monash University, Clayton,VIC, Australia2. Biospheric Processes, Centre d’Etudes Spatiales de laBiosphère (Cesbio), Toulouse, France3. Hydrospheric and Biospheric Sciences Laboratory, NASAGoddard Space Flight Center, Greenbelt, MD, USAFor the validation of the European Space Agency-ledSoil Moisture and Ocean Salinity (SMOS) Level 2 soilmoisture product two extensive field campaigns wereconducted in the Australian summer (18 January to 21February) and winter (8-23 September) periods of 2010.Such extensive field campaigns including detailed in-situand airborne observations are required due to the newdesign of the SMOS satellite being a 2-dimensionalinterferometric radiometer and its use of a previouslyunderutilized microwave frequency band (L-band at1.4GHz). The Australian Airborne Cal/val Experiments forSMOS (AACES) were undertaken in south-eastern Australia,across the catchment of the Murrumbidgee River, a tributaryof the Murray-Darling basin. The climatological andhydrological conditions throughout the catchment rangefrom flat, semi-arid regions in the west to alpine andtemperate in the central and eastern reaches. This varietymakes the Murrumbidgee River catchment particularly wellsuited for such large scale studies. The study area covered atotal area of 50,000km2 with 20 focus farms distributedacross the catchment in which high-resolution in-situmeasurements were taken. Furthermore, the OzNetmonitoring network consisting of over 60 stations, includingsoil temperature and soil moisture sensors, is located withinthe catchment, complementing the data collection efforts byproviding long-term observations. During the campaignsextensive brightness temperature data sets were collectedusing an airborne L-band radiometer, while ground teamswere deployed to the focus farms to collect in-situ data.Those data sets are used in the present study to producelarge scale soil moisture maps, using the standardparameterization of the L-band Microwave Emission of theBiosphere (L-MEB) model, which forms part of theoperational soil moisture retrieval processor of SMOS. Thesubsequent comparison of those large scale maps, as well asthe station time series show a systematic dry bias in theSMOS retrieval. The magnitude of this bias varies betweenthe regions and is likely related to the varying surface128conditions. As the spatial resolution of SMOS is too low forthe agricultural purposes, SMOS soil moisture data werealso disaggregated, applying an approach based on the asemi-empirical soil evaporative efficiency model, and a firstorder Taylor series expansion around the field-mean soilmoisture. While the bias is well preserved, promising resultsare obtained when comparing the disaggregated productwith aggregated in-situ measurements of the focus farms,with retrieval errors from 0.02 to 0.1 m3 m-3, which issimilar to the errors found in the large scale products. Thetwo studies performed highlight the value SMOS can have invarious applications. In particular, a further expectedimprovement of the retrieval algorithm should allow a soilmoisture product close to the design accuracy of SMOS of0.04 m3 m-3.Rui, HualanNLDAS Views of North American 2011 ExtremeEventsRui, Hualan 1, 3 ; Teng, William 1, 4 ; Vollmer, Bruce 1 ; Mocko,David 2, 5 ; Lei, Guang-Dih 1, 31. GES DISC, GSFC NASA, Greenbelt, MD, USA2. Hydrological Sciences Laboratory, GSFC NASA,Greenbelt, MD, USA3. ADNET Systems, Inc., Rockville, MD, USA4. Wyle Information Systems, Inc., McLean, VA, USA5. SAIC, Beltsville, MD, USA2011 was marked as one of the most extreme years inrecent history. Over the course of the year, weather-relatedextreme events, such as floods, heat waves, blizzards,tornadoes, and wildfires, caused tremendous loss of humanlife and property. Many research projects have focused onacquiring observational and modeling data and revealinglinkages between the intensity and frequency of extremeevents, global water and energy cycle, and global climatechange. However, drawing definite conclusions is still achallenge. The North American Land Data AssimilationSystem (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data, withhigh spatial and temporal resolutions (0.125° x 0.125°,hourly) and various water- and energy-related variables(precipitation, soil moisture, evapotranspiration, latent heat,etc.) is an excellent data source for supporting water andenergy cycle investigations. NLDAS can also provide data forcase studies of extreme events. This presentation illustratessome extreme events from 2011 in North America, includingHurricane Irene, Tropical Storm Lee, the July heat wave, andthe February blizzard, all utilizing NLDAS data.Precipitation and soil moisture fields will be shown for thetwo East Coast tropical storm events, temperatures will beshown for the heat wave event, and snow cover and snowdepth will be shown for the winter blizzard event. Theseevents are presented in the context of the 30-plus yearclimatology of NLDAS. NLDAS is a collaboration projectamong several groups (NOAA/NCEP/EMC, NASA/GSFC,Princeton University, University of Washington,NOAA/OHD, and NOAA/NCEP/CPC) and is a core projectof NOAA/MAPP. To date, NLDAS, with satellite- and

ground-based observational forcing data, has producedmore than 30 years (1979 to present) of quality-controlled,spatially and temporally consistent, land-surface model data.NLDAS data can be accessed from the GES DISC HydrologyData Holdings Portal(http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings). Tofurther facilitate access and use of the data, NLDAS datahave been made available in NASA Giovanni(http://disc.sci.gsfc.nasa.gov/giovanni). Via the GiovanniNLDAS hourly portal, http://gdata1-ts1.sci.gsfc.nasa.gov/daac-bin/G3/gui.cgi?instance_id=NLDAS0125_H, NLDAS forcing data and model outputs can beeasily visualized, analyzed, and intercompared, withouthaving to download the data.http://disc.sci.gsfc.nasa.gov/hydrology/data-holdingsRyu, YoungryelIntegration of MODIS Land and AtmosphereProducts With a Coupled-process Model toEstimate Evapotranspiration From 1 km to GlobalScalesRyu, Youngryel 1 ; Kobayashi, Hideki 2 ; van Ingen, Catharine 3 ;Baldocchi, Dennis 41. Seoul National University, Seoul, Republic of Korea2. JAMSTEC, Yokohama, Japan3. Microsoft Research, San Francisco, CA, USA4. UC Berkeley, Berkeley, CA, USAWe propose the Breathing Earth System Simulator(BESS), an upscaling approach to quantify global grossprimary productivity and evapotranspiration using MODISwith a spatial resolution of 1-5 km and a temporalresolution of 8 days. This effort is novel because it is the firstsystem that harmonizes and utilizes MODIS Atmosphereand Land products on the same projection and spatialresolution over the global land. This enabled us to use theMODIS Atmosphere products to calculate atmosphericradiative transfer for visual and near infrared radiationwavebands. Then we coupled atmospheric and canopyradiative transfer processes, with models that computed leafphotosynthesis, stomatal conductance and transpiration onthe sunlit and shaded portions of the vegetation and soil. Atthe annual time step, the mass and energy fluxes derivedfrom BESS showed strong linear relations withmeasurements of solar irradiance (r2=0.95, relative bias: 8%),gross primary productivity (r2=0.86, relative bias: 5%) andevapotranspiration (r2=0.86, relative bias: 15%) in data from33 flux towers that cover seven plant functional types acrossarctic to tropical climatic zones. A sensitivity analysisrevealed that the gross primary productivity andevapotranspiration computed in BESS were most sensitive toleaf area index and solar irradiance, respectively. Wequantified the mean global terrestrial estimates of grossprimary productivity and evapotranpiration between 2001and 2003 as 118±26 PgC yr-1 and 500±104 mm yr-1(equivalent to 63,000±13,100 km3 yr-1), respectively. BESSderivedgross primary productivity and evapotranspirationestimates were consistent with the estimates fromindependent machine-learning, data-driven products, butthe process-oriented structure has the advantage ofdiagnosing sensitivity of mechanisms. The process-basedBESS is able to offer gridded biophysical variableseverywhere from local to the total global land scales with an8-day interval over multiple years.Sandells, MelodyCan simpler models reproduce the snowtemperature gradients of many-layered models forremote sensing of snow mass? A SNOWMIP2intercomparisonSandells, Melody 1 ; Rutter, Nick 2 ; Essery, Richard 31. ESSC, University of Reading, Reading, United Kingdom2. Northumbria University, Newcastle, United Kingdom3. The University of Edinburgh, Edinburgh, UnitedKingdomAlthough there is a long-time series of passivemicrowave observations available, the snow mass recordsderived from these are unreliable because of the assumptionsof globally constant snow properties behind the retrievalalgorithms. Scattering of electromagnetic radiation isparticularly sensitive to the size of the snow crystals. In orderto retrieve snow mass from passive microwave observations,the size of the snow crystals must be known. Growth of asnow crystal depends on the vapour pressure surroundingthe crystal, which is governed by vapour diffusion along thesnow temperature gradient. Physically-based multi-layermodels that use conservation of mass and energy to simulatethe evolution of the snow have been shown to providereasonable estimates of temperature gradients and snowgrain growth. However, these models are toocomputationally expensive to run at large scales. This is onlyfeasible for simpler models, so the question is whethersimpler models are equally as able to capture temperaturegradients as the more complex multi-layer models. If so,physically-based but computationally simple models may beused to provide snow grain size information to form thebasis of the next generation of snow mass retrievalalgorithms. Outputs from the SNOWMIP2 snow modelintercomparison study have been used to analyse andcompare temperature gradients simulated by different snowmodels. SNOWMIP2 was a co-ordinated model study thatexamined the performance of 33 snow models driven byvirtually identical meteorological forcing data at multiplesites and years. Of these 33 models, snow profileinformation was output for 7 different models, which formsthe basis of this study. Two of these models had multiplelayers, the remaining five models had 3 or fewer layers. Oneparticular site and year was selected for study because of thecomparatively good agreement for snow mass between themodels, and the availability of field observations. Snowtemperature gradients were analysed for the different modelswith respect to different factors such as the depth of thelayers in the snowpack, and the timing within the diurnalcycle. The impact of temperature gradient differences on129

grain size evolution and implications for remote sensing ofsnow mass will be discussed.SANTOS DA SILVA, JoecilaALTIMETRY OF THE AMAZON BASIN RIVERSSANTOS DA SILVA, Joecila 1 ; Calmant, Stéphane 2 ; Seyler,Frédérique 3 ; Moreira, Daniel M. 2, 41. Centro de Estudos do Trópico Úmido – CESTU,Universidade do Estado do Amazonas – UEA, Manaus,Brazil2. UMR 5566 LEGOS CNES/CNRS/IRD/UT3, Institut deRecherche pour le Développement – IRD, Toulouse,France3. UMR ESPACE-DEV, Institut de Recherche pour leDéveloppement – IRD, Montpellier, France4. Universidade Federal do Rio de Janeiro - UFRJ, Rio deJaneiro, BrazilAltimetry of rivers all along their course is majorinformation in hydrology, whatever it is for runninghydrological model, determine the amount of surface waterstored, and predict the consequences of extreme events.Satellite altimetry can be used in many ways to retrieveconsistent altimetry information throughout the course ofrivers. Now, it is now well known as a useful tool to retrievethe space and time variations of the water surface. Besidesthis basic use of satellite altimetry, it can also be used to: 1/level gauges, so making a consistent dataset merging hightemporal sampling from gauges and dense sampling fromthe crossings between satellite tracks and river network; 2/densify climatic series (mean value per month of the year) allalong the river course when series are long enough and, bycomparison with time series, evidence extreme events; 3/detail the altitudinal changes of the river course which, whencompared to a DTM, inform over the basin hypsometry; 4/level bathymetric profiles in order to obtain altitudinalchanges of the river bed; 4/ check for errors in the gaugeseries or in the metadata information related to a gauge. Inthe present study, we present examples of such applicationsof satellite altimetry for the major contributors of theAmazon basins. In this basin, more than 500 series havebeen computed from the ERS2 & ENVISAT missions in theone hand (1995-2010) and from the T/P & JASON2 missionsin the other hand (1992-2002 / 2008-). All series have beencarefully checked manually and we present statistics ofcomparison with ground-truth, i.e. water levels from GPSleveledgauges. Rivers of very different widths have beensampled, ranging from several km wide to less than 100mwide. For some of the rivers, altimetry series are the onlypossibility to get stage and slope information since theserivers are devoid of in-situ measurement or themeasurements are not available, in particular out of Brazil.Schroeder, Dustin M.Remote Sensing of Subglacial Water Networks withIce Penetrating RadarSchroeder, Dustin M. 1 ; Blankenship, Donald D. 1 ; Young,Duncan A. 11. University of Texas Institute for Geophysics, Austin, TX,USAThe subglacial water systems beneath outlet glaciers ofcontinental marine ices sheets is an important and difficultto constrain control on ice sheet mass balance and sea levelrise estimates and their role in the global hydrologic cycle.The net subglacial water flux is the dominant unknown inreconciling satellite gravity and inSAR derived surfacevelocity measurements of ice sheet mass balance. It is also akey parameter in predicting sub-ice-shelf circulation andcollapse as well as glacial surge and retreat initiated by thedynamics of subglacial lakes. Successfully modeling thesephenomena and their effects requires understanding notonly the locations of individual subglacial lakes andconduits but the entire subglacial hydrologic network. Sincedirect observations of the basal hydrology of ice sheets areboth extremely limited in area and prohibitively expensive(e.g. drilling, seismic), airborne radar sounding is the onlypractical means of acquiring basin-scale observations ofsubglacial water systems. Airborne ice penetrating radarsounding has been used with variable success to identify andcharacterize basal water systems and their sedimentarycontext by the strength of the return from the basalinterface. Specularity is a parameterization of the angularitydependent echo intensity that measures how tightly or“mirror-like” the energy is distributed with observing angle.The specularity of the basal return can indicate the presence,extent, and configuration of subglacial water and sedimentindependent of the temperature profile and impurityconcentration of the ice column, which complicatetraditional amplitude based interpretations. We use multipleradar focusing windows to produce a basal specularity mapfrom a gridded aerogeophysical survey of West Antarctica’sThwaites Glacier catchment (over 150,000 square kilometers)using a 60 MHz coherent ice penetrating radar with a 15MHz bandwidth linear frequency modulated waveform. Wefind that regions of high specularity correlate with modeledhydrologic pathways and indicate an extensive water networkbetween the ice and bed. We demonstrate how variations inthe strength of the specularity signal with the survey-line towater-flow-path angle can be used to constrain the size,geometry and flow-regime of the water system using physicaloptics.Using these results, we present an interpretation ofthe basal hydrology and morphology of Thwaites Glacier inthe context of the hydrologic gradient, surface slope,inferred basal melt, and inferred basal shear stress. Thisinterpretation provides insights into the current andpotential role of subglacial water in the Thwaites Glaciersystem and demonstrates the ability of specularity analysisto provide information about the basal boundary conditionat a scale that is inaccessible to traditional amplitude basedradio echo sounding analysis.130

Selkowitz, DavidExploring Landsat-derived Snow Covered Area(SCA) Probability Distributions for DownscalingMODIS-derived Fractional SCASelkowitz, David 1, 21. Alaska Science Center, USGS, Anchorage, AK, USA2. Department of Geography, University of Utah, Salt LakeCity, UT, USAIn this study, Landsat TM data from Landsat path-rowsfor three mountain regions, the Sierra Nevada in California,the Cascades in Washington, and the Rockies in Montana,were analyzed to determine the feasibility of using Landsatsnow covered area (SCA) data to downscale 500 m fractionalsnow covered area (fSCA) estimates from MODIS to 30 mspatial resolution. Snow cover probability distributions at 30m resolution were generated for 500 m MODIS-like gridcells based on binary SCA maps from all available LandsatTM scenes acquired between 2000 and 2006 for the studypath-rows. The probability distributions were then used todownscale Landsat-derived 500 m snow cover fractions foreach 500 m grid cell for all available scenes acquired between2007 and 2009. Results indicate this approach was effectivein the majority of cases for each of the three regions, withthe highest accuracy observed for grid cells above treeline,grid cells with rugged topography, and grid cellsencompassing abrupt land cover transitions. Lower accuracywas observed for grid cells dominated by dense,homogeneous forest cover. Results from this study suggestthat SCA patterns at 30 m spatial resolution mapped byLandsat tend to remain stable over multiple years for theregions sampled. For areas where this is the case,downscaling 500 m fSCA estimates from MODIS to a 30 mspatial resolution binary SCA product should be possible,though the accuracy of this approach will depend partiallyon how well the MODIS fSCA estimates match the numberof 30 m pixels mapped as snow covered by Landsat withinthe 500 m MODIS grid cells. The interannual stability ofSCA patterns may also allow for downscaling from MODISfSCA to Landsat scale fSCA, though a more complexapproach would be necessary.Semmens, Kathryn A.Remote Sensing of Snowmelt - Understanding aChanging (and Melting) FutureSemmens, Kathryn A. 1 ; Ramage, Joan 11. EES, Lehigh University, Bethlehem, PA, USASnowmelt has a significant influence on terrestrialhydrology in snowmelt dominated basins with spring runoffand associated flooding the most significant hydrologicevent of the year. Changes in snowmelt timing andstreamflow seasonality impact the availability of waterresources for populations in these areas. Understanding andmonitoring the diurnal amplitude variation (DAV) betweenmorning and night sheds light on the dynamics of transitionperiods, providing information on timing of water release inthe terrestrial hydrologic cycle. Without remote sensing, thisproperty is difficult to continuously observe over largespatial areas and for inaccessible, remote regions. The DAVapproach provides temporally high resolution informationon melting and refreezing, the timing of which affects theprogression of meltwater through a basin and peaksnowmelt runoff. This is of critical importance for hydrologyand related ecosystem processes as the timing of the end ofmelt-refreeze is closely linked to green-up in high latituderegions. In addition, tracking and studying snowmelt stagesfrom winter through the transition season and green-up canprovide useful landscape scale information on preconditioningfor wildfires and for runoff predictions. Passivemicrowave radiometers such as the Advanced MicrowaveScanning Radiometer – EOS (AMSR-E) and Special SensorMicrowave/Imager (SSM/I) that observe brightnesstemperatures (Tb), a product of physical temperature andemissivity, are used to detect snowpack properties, fromsnowmelt onset to snow water equivalent (SWE). We reviewresearch pertaining to remote sensing of snowmelt timingand runoff with particular attention paid to the techniqueof monitoring DAV. This technique involves determining wetsnow when the difference between ascending and descendingmeasurements exceeds a fixed threshold |TbAsc-TbDes| > A,in conjunction with a brightness temperature thresholdTb>B. For AMSR-E (2002-2011) the 36.5 GHz V thresholdsare A=18K, B=252K. For SSM/I (1987-present) the 37 GHz Vthresholds are A=10K, B=242K. Variations range from adynamic threshold to utilization of different frequencies andpolarizations. For instance, some researchers utilize the 37GHz V due to its sensitivity to wetness, while others consider19 GHz for indication of melt penetration. Combiningfrequencies allows for characterization of surface and nearsurfacedynamics, important for detecting hydrologicparameters such as melt, infiltration, and runoff. Thesetypes of data and monitoring must be continued in futuremissions with an effective transition between past and futurehydrologic remote sensing. The Joint Polar Satellite System(JPSS) may serve to continue and supplement the legacy ofSSM/I and AMSR-E. The Advanced Technology MicrowaveSounder (ATMS), one of the instruments on the NPOESSPreparatory Project (NPP) mission (launched October 2011)and the future JPSS, has 22 channels from 23 GHz to 183GHz. Importantly, the ATMS instrument has imagingchannels relevant to continuing the current algorithmsutilized for SWE and snowmelt detection (23V, 37VH)enabling continuous data collection of snow parametersimportant for terrestrial hydrology.131

Senay, GabrielEvaluating the performance of remote sensingbased evapotranspiration products using fluxtower and water balance approachesSenay, Gabriel 1 ; Singh, Ramesh 2 ; Bohms, Stefanie 3 ; Verdin,James P. 11. USGS, Sioux Falls, SD, USA2. Science, ARTS, Sioux Falls, SD, USA3. SGT, Sioux Falls, SD, USAOperational estimation of actual evapotranspiration(ETa) is important for early warning applications in droughtand crop performance monitoring. The US GeologicalSurvey (USGS) developed the Simplified Surface EnergyBalance (SSEB) model, a simplified modeling approach tocalculate ETa on an operational basis for early warningapplications. The SSEB approach has been implemented forthe conterminous US and Africa to produce ETa on an 8-daybasis that is in turn used to create monthly and seasonal ETanomalies. Thermal data sets from MODIS 8-day productwere used to calculate an ET fraction which is combinedwith reference ET calculated from NOAA-produced dataassimilatedglobal weather data sets. ET anomalies arecalculated as a percent of the average ET (2000-2010) fromthe same month or season. While ET anomalies aresufficient to detect relative crop performance or detecting adrought, water budget studies require accurate estimation ofETa in terms of absolute magnitudes. We evaluated theaccuracy of SSEB based ETa with two data sources. MonthlyETa was evaluated using 18 flux tower data sets in theconterminous US using available data from 2000 through2010. In addition, Annual ETa was evaluated usingwatershed water balance data sets at the HUC8 (hydrologicunit code, level 8) scale. Annual water balance (precipitationminus runoff) for more than 1,300 HUCs were compared toHUC average ET with the assumption that net storagechange is negligible at annual time scale with little interbasinexchange for the selected HUCs. SSEB ET showedstrong correspondence with both flux tower (R2 varied from0.6 to 0.85 depending on years) with a generaloverestimation bias and HUC based water balanceevaluations (R2 > 0.9). For the water balance basedevaluation by contrast, SSEB ET showed a slightunderestimation in lower ET regions (annual ET < 600 mm).While the relationships in the two evaluation approaches arestrong, the differences in the direction of the bias needfurther investigation. However, the initial results suggestthat a simplified modeling approach for estimating ETproduces precise (high R2) and useful products that can beused both in relative applications such as droughtmonitoring but also for water budget studies at watershedscales. Calibrated and validated watershed-scale ET productsare being evaluated for the WaterSMART program of theDepartment of the Interior under which the USGS center forEarth Resources Observation and Science (EROS) isconducting a nationwide study on water availability andwater use.Seto, ShintaNecessity of Integrated Observations of SoilMoisture and Precipitation by Microwave RemoteSensingSeto, Shinta 11. Institute of Industrial Science, University of Tokyo,Tokyo, JapanBoth precipitation and soil moisture are primarycomponents of the terrestrial water cycle, and their spatialand temporal variations are large. Satellite microwave remotesensing is an indispensible tool to measure the variations ofprecipitation and soil moisture, but it is almost impossibleto measure the two components separately from each other.Information on one component is required for moreaccurate estimation of another component. Below studyshows the necessity of integration of precipitation and soilmoisture observations. For space-borne precipitation radar,surface reference technique (SRT) is available. SRT is appliedto derive path integrated attenuation (PIA) from the changein measured surface backscattering cross section (s0m)between no-rain and raining cases. To estimate PIAaccurately, the change in actual surface backscattering crosssection (s0e) caused by the variation in surface conditionsshould be considered. An analysis of Tropical RainfallMeasuring Mission (TRMM) / Precipitation Radar (PR) datashowed that s0e tends to become higher under rainfall. Asthe change of s0e is not explicitly considered, SRTunderestimates PIA and the average of PIA in many regionsis negative which is physicaly incorrect (as shown in Fig.1).The tendency is more apparently seen in sparsely vegetatedarea such as the Sahel of Africa, but not clearly seen indensely vegetated area such as the Amazonia. The increase ins0e is considered to be caused by increase in surface soilmoisture, and is called soil moisture effect. In the latestTRMM/PR standard algorithm, 0.5dB is added to PIA overland to compensate the soil moisture effect. The offset mayincrease precipitation rate at most around 7 %, however, theoffset value should be given more appropriately consideringthe characteristics of soil moisture variations.The average of PIA estimates in previous version of the TRMM/PRstandard algorithm.132

Shahroudi, NargesMicrowave Emissivities of Land Surfaces: Detectionof Snow over Different Surface TypesShahroudi, Narges 1 ; Rossow, William 11. CCNY, New York, NY, USAThe sensitivity of passive microwave satelliteobservations to different land surface types and thepresence/absence of snow are evaluated for the years 2000,2001, and 2002 for the whole globe. Surface microwaveemissivities are derived from SSM/I observations byremoving the contributions of the cloud and atmosphereand separating the surface temperature variations using datafrom the International Satellite Cloud Climatology Project(ISCCP). Vegetation and snow flags are compiled from alarge number of published sources. The spatial and temporalvariability of microwave emissivities over land surfaces withand without snow between 19 and 85 GHz have beenstudied: the presence of snow and the variations of land typeand temperature (as well as precipitation) all affect the signalthat is received by satellite. In this analysis the variations dueto snow presence are isolated from these other factors,revealing much clearer contrasts in the range of theemissivities between snow and snow-free surfaces. Passivemicrowave emissivities at higher frequencies are moresensitive to the presence of shallow layers of snow whereasthe lower frequencies only respond to deeper layers of snow.Combining these two provides a more general technique toidentify the global distribution of snowcover on a daily basis.Such a method was developed and compared with theavailable NOAA weekly snow cover maps. Agreement wasfound in 90% of locations and times. The behavior of thedisagreements was investigated further. Some of theexplanation occurs because the NOAA product, based largelyon visible satellite radiance analysis, misses some snow inforested areas. More interestingly, much of the disagreementcould be explained by differences in the evolution of snowemissivities associated with freeze-melt-re-freeze cycles andadditional snowfall. This source of disagreement results inpart because of the low time resolution of the NOAAproduct. The results were compared with the snow depthproduct from Canadian Meteorological Centre (CMC) andthe snow cover from the Moderate Resolution ImagingSpectroradiometer (MODIS) sensor on NASA’s EarthObserving System (EOS) Aqua and Terra satellites and theywere correlated with our results in about 80% of the timesand locations. Also to confirm our conclusions aboutdetection sensitivity we are investigating the predictions of amicrowave emission model of layered snowpack where weadjust the inputs to attain the observed emissivities.Shields, Gerarda M.Developing a Prioritization Plan to Assess theImpact of Climate Change Predictions on theHydraulic Vulnerability of Coastal BridgesShields, Gerarda M. 11. CMCE, NYC College of Technology, Brooklyn, NY, USAWith the reality of climate change now widely acceptedthe world over by recognized scientific organizations andgovernments, bridge owners are beginning to consider howclimate change may affect the safety of their bridges. In astudy of bridge failure causes in the United States, over 60%were due to hydraulic factors. Changes in sea-level rise,precipitation, and storm frequency may have importantimplications in the hydraulic design, analysis, inspection,operation and maintenance of bridge structures. Climatechange predictions for the northeastern United States areparticularly alarming as many coastal cities would beaffected. For example, regional climate models for the NewYork City coastal region predict sea level to rise as much as12 – 55 inches (30 – 140 cm), possible precipitation increasesof 5 to 10% and an increase in the frequency of storm eventssuch as the 100-year storm by the year 2080. Theincorporation of climate change predictions with respect tobridge hydraulics and scour will be discussed using the NewYork City coastal region as a case study.Shige, ShoichiImprovement of rainfall retrieval for passivemicrowave radiometer over the mountain areasShige, Shoichi 1 ; Taniguchi, Aina 11. Graduate School of Science, Kyoto University, Kyoto,JapanHigh-resolution precipitation products have beenprovided using combined data from passive microwaveradiometers (MWRs) in low Earth orbit and infrared133

adiometers in geostationary Earth orbit (e.g., Joyce et al.2004, J. Hydrometeorol; Huffman et al. 1997, J.Hydrometeorol; Ushio et al. 2009, J. Meteorol. Soc. Jpn.).Although utilization of these datasets for flood andlandslide analysis/prediction has started, it is still in theexperimental stage because of the poor performance ofsatellite estimates in heavy rainfall over mountainousregions. Kubota et al. (2009, J. Meteorol. Soc. Jpn.) showedworst verification results over mountainous regions, inparticular, areas with frequently heavy orographic rainfall,comparing the satellite rainfall estimates around Japan withreference to a ground-radar dataset calibrated by rain gaugesprovided by the Japan Meteorological Agency. Theysuggested that one of main reasons for these errors isunderestimation of MWR algorithms for orographic heavyrainfall over Japan. In this paper, we improve theperformance of estimates by the Global Satellite Mapping ofPrecipitation (GSMaP) estimates from MWRs (Aonashi et al.2009, J. Meteorol. Soc. Jpn.; Kubota et al. 2007, IEEE Trans.Geosci. Remote Sens.) for orographic heavy rainfall. TheGSMaP algorithm consists of the forward calculation part tocalculate the lookup tables (LUTs) showing the relationshipbetween rainfall rates and brightness temperatures (Tbs)with an radiative transfer model (RTM), and the retrievalpart to estimate precipitation rates from the observed Tbsusing the LUTs. We dynamically select whether LUTscalculated from “original” precipitation profiles or thosefrom “orographic” precipitation profiles based on theorographically forced upward vertical motion and surfacemoisture flux convergence. Rainfall estimates from therevised GSMaP algorithm are much better agreement withPR estimates than those from the original GSMaPalgorithm.Shum, C. K.SURFACE FLOOD AND SMALL WATER BODYMONITORING USING RADAR ALTIMETRY:PROSPECTS FOR SWOTShum, C. K. 1 ; Tseng, Kuo-Hsin 1 ; Kuo, Chungyen 2 ; Alsdorf,Douglas 1 ; Calmant, Stephane 3 ; Duan, Jianbin 1 ; Lee,Hyongki 4 ; Yi, Yuchan 11. School of Earth Sciences, Ohio State University,Columbus, OH, USA2. School of Earth Sciences, The Ohio State University,Columbus, Taiwan3. Institut de Recherche pour le Developpement, LEGOS,Toulouse, France4. Civil and Environmental Engineering, University ofHouston, Houston, TX, USAThe planned Surface Water and Ocean Topography(SWOT) wide-swath interferometric altimetry mission isanticipated to revolutionize hydrologic surface watermeasurement from space, with unprecedented spatialresolution, sampling and accuracy. While off-nadir repeatpassradar interferometric SAR (InSAR), when combinedwith satellite radar altimetry to provide needed verticalreference, is capable of measuring high spatial resolution(~40 m) dh/dx surface water changes at SAR acquisitiontimes, unlike SWOT, it could only measure vegetatedwetlands or lakes which allow double-bounced radar signaldetections. This contribution addresses challenging researchobjectives to improve contemporary pulse-limited nadirradar altimetry to enable accurate measurements ofspaceborne water level changes over relatively small waterbodies (< 1 km width, which is much smaller than the 1-Hzdata sampling with footprints of several km), using radarwaveform retracking techniques, exploiting higher sampledaltimeter data (20 Hz for Jason-2), and mitigation ofspurious waveforms caused by contamination of waveformsover non-water surface, especially those with steep or roughterrains. Here we study the feasibility of extending thecapability of contemporary radar altimeters (20-Hz Jason-2,the planned 40-Hz AltiKa, and the mini-swath CryoSatSAR/SIRAL data) for surface flood and inland small waterbody monitoring and hydraulic studies. Demonstrationstudies include for proof-of-concept timely monitoring offlood episodes, flood heights and extents using altimetryand other data sets (MODIS, GRACE), including 1997 RedRiver floods, the 2009 Amazon record flood on Rio Negro,the 2010 flood in Pakistan and China, the 2011 Australian,Memphis and Thailand floods. Demonstration waveformretracking/improvement studies over small inland waterbodies include seasonally inundated Bajhang River, Taiwan,with varying river width at 100 m to 2 km, Poyang Lake,China, and other water bodies, indicating that using bothalternate retrackers (e.g., threshold retrackers) and waveformediting/mitigation techniques based on empirical surfaceresponse data from radar backscatters, resulted in betterImprovement Percentages (IMPs) agreement with availablein situ gage measurements, as compared to the onboardretracked measurements. Finally, this study intends toaddress the feasibility of development of an improved apriori seasonally varying water masks in preparation for theSWOT mission.Singh, AmitASSESSMENT OF MORPHOTECTONICINFLUENCES ON HYDROLOGICALENVIRONMENT IN VICINITY OF AN ACTIVEFAULTSingh, Amit 1 ; Mukherjee, Saumitra 11. School of Environmental Sciences, Jawaharlal NehruUniversity, New Delhi, IndiaStudying effects of faulted zones in shaping thehydrological environment of any landscape in a long run isdifficult, though these can play a crucial role in regulatingthe flow and accumulation of water. While aquifer rechargeis directly influenced by the structural changes associatedwith tectonic activity, surface flow may also be influenceddepending upon the topography. While planning for waterresource management, groundwater remediation orhydrological restoration it is imperative to understand andsuitably include these influences to derive maximumbenefit. This study aimed at characterization of surface as134

well as subsurface hydrological conditions in a hard-rockterrain, morphed under the influence of neotectonic activity,associated with tensional type of faulting. The area selectedlies in vicinity of an active fault, with quartzitic rocksshowing signs of multiple folding. Associated tear faults inadjoining areas have also been observed. To initially identifysites suitable for geophysical surveys, a spatial analysisinvolving seismic data and 3D visualization was done toidentify the lineaments. The information thus obtained wascorrelated with geological information derived fromhyperspectral satellite imagery. Geochemical analysis wasalso performed to verify the same. Influence of faultingactivity on regulating water flow on surface as well asgroundwater was studied. For surface water bodieshydrological analysis on elevation data (DEM) wasperformed whereas for subsurface recharge, margins ofgeological units were targeted. This was confirmed by actualfield geophysical (resistivity) surveys at suitable strategiclocations. The relative influences of structural lineaments onregulating subsurface water storage were also determined.The resulting database in GIS platform can also be used forflow modeling and aquifer potential / vulnerability studies.Also, the role of faulting activity in regulating connectivitybetween multiple aquifers and surface water bodies may bestudied using the outputs.Skuse, Russell J.Thermophysical Characteristics of SurfaceMaterials for Mapping the Spatial Distribution ofSoil Moisture in the Mojave Desert using multisceneASTER TIR Remote Sensing ObservationsSkuse, Russell J. 1 ; Nowicki, Scott A. 11. Water Resource Management, University of Nevada LasVegas, Las Vegas, NV, USAClimate models suggest that the Mojave Desertecoregion is vulnerable to becoming drier in the future, andas the human population grows and development increases,environmental stresses will likely increase. Determining thespatial distribution and variation of soil moisture on aregional scale is an essential component to climate change,hydrologic, and habitat analyses. Soil permeability andsediment stability are characteristics that have been shownto be measurable from remote sensing observations. Theprimary objective of this project is to map the mechanicalcomposition of the surface materials in the Mojave Desertecoregion with implications for soil permeability, sedimentstability, and soil moisture. We are using advanced mappingtechniques to determine the surface mechanicalcompositions of the Mojave, using data provided by theAdvanced Spaceborne Thermal Emission and Reflectionradiometer (ASTER), which provides the spatial resolutionnecessary to map the composition and thermal properties ofarid surfaces and is well suited for mapping the spatialdistribution of soil moisture. A full-resolution mosaic of TIRand VNIR ASTER images has been constructed for the entireMojave Desert for mapping surface components. With a 16-day repeat cycle, ASTER provides the high resolutionmapping perspective, but lacks the temporal sampling toadequately quantify changes over days to weeks. ModerateResolution Imaging Spectroradiometer (MODIS) dataprovides the temporal resolution needed to determineseasonal variations, although at a coarser spatial resolution.Our approach for mapping the Mojave Desert regioninvolves using both MODIS and ASTER to provide the idealspatial and temporal sampling to map individual storms andtheir effects on the seasonal conditions of the surface. Theviability of the Mojave Desert ecosystem relies solely oninfrequent storms and their temporal and spatialdistribution over local regions and varied landscapes.Mapping the distribution of individual wetting events withregard to the geomorphology of the region can be a usefulcomponent for modeling potential changes as a function ofclimate change and human development. Our goal is tobetter understand how random weather events contribute tothe hydrologic cycle in the Mojave and potentially other aridregions around the world.Slayback, Daniel A.Near Real-Time Satellite Monitoring Of GlobalFlooding EventsSlayback, Daniel A. 1 ; Brakenridge, G. R. 3 ; Policelli, FrederickS. 2 ; Tokay, Maura M. 1 ; Kettner, Albert 31. Biospheric Sciences Laboratory, SSAI/NASA GSFC,Greenbelt, MD, USA2. Office of Applied Sciences, NASA GSFC, Greenbelt, MD,USA3. CSDMS, University of Colorado, Boulder, CO, USAFlooding is among the most destructive, frequent, andcostly natural disasters faced by modern society, with severalmajor flood events occurring each year. In 2011 alone, someof the major events include flooding along the Mississippiand regionally in New England, along the Chao Phraya inThailand, the Indus in Pakistan, and coastal Japan after thetsunami. The death and financial toll of these events hasbeen substantial. When such events occur, the disastermanagement community requires flood extent informationwith very little latency and frequent updating to bettercoordinate response efforts. With funding from NASA’sApplied Sciences program, we have developed, and are nowoperating, a near real-time global flood mapping system tohelp provide critical flood extent information within 24-48hours after flooding events. The system applies a waterdetection algorithm to MODIS imagery received from theLANCE (Land Atmosphere Near real-time Capability forEOS) system at NASA Goddard. The LANCE systemtypically processes imagery in less than 3 hours after satelliteoverpass, and our flood mapping system can output floodproducts within ½ hour of acquiring the LANCE products.Using imagery from both the Terra (10:30 AM overpass) andAqua (1:30 PM overpass) platforms allows an initialassessment of flooding extent by late afternoon, every day,and more robust assessments after accumulating imageryover a two day period; the MODIS sensors are optical, socloud cover remains an issue, which is partly overcome by135

using multiple looks over one or two days. Other issuesinclude the relatively coarse scale of the MODIS imagery(250 meters), the difficulty of detecting flood waters in areaswith continuous canopy cover, confusion of cloud shadowwith water, and accurately identifying detected water asflood as opposed to normal water extents (typically only anedge issue). We have made progress on some of these issues,and are working to develop higher resolution flooddetection using alternate sensors, including Landsat andvarious radar sensors (Radarsat, ENVISAT). Although theseprovide better spatial resolution, this usually comes at thecost of being less timely. As of late 2011, the systemexpanded to fully global daily flood monitoring, with freepublic access to the generated products. These include GISvector files of flood and normal water extent (KML,shapefile), and small scale graphic maps (10 degrees square)showing a zoomed out view of regional flood extent. Weplan to expand to distributing the information via live webservices (WMS, etc), in the near future. In the medium term(2-3 years) we hope to transition this system to anoperational partner.https://oas.gsfc.nasa.gov/floodmapSmall, Eric E.Sensing Vegetation Growth with Reflected GPSSignalsSmall, Eric E. 1 ; Larson, Kristine 2 ; Evans, Sarah 1 ; Vikram,Praveen 21. Dept of Geology, Univ of Colorado Boulder, Boulder, CO,USA2. Aerospace Engineering, CU Boulder, Boulder, CO, USAMeasurements of vegetation state are required tovalidate satellite estimates of soil moisture and as boundaryconditions for hydrometeorological modeling. We havedeveloped a new technique to estimate vegetation statususing reflected GPS signals (multipath) measured bygeodetic-quality GPS stations. The sensing footprint is~1000 m2, larger than that provided by typical in situobservations but smaller than that from space-basedproducts. Because GPS satellites transmit L-band signals, thevegetation estimates derived from GPS reflections are ameasure of vegetation water content, not greenness as is thecase for optical remote sensing methods. We present resultsbased on two distinct attributes of the multipath signal: (1)signal attenuation observed as the amplitude of the signalto-noise(SNR) interference pattern; and (2) diffusescattering measured via an operational GPS noise statistic,MP1rms. We have compared GPS multipath to biweeklymeasurements of biomass, vegetation height, and watercontent at ten test sites that span a range of vegetationcharacteristics. These field campaigns were conducted in2010 and 2011. Vegetation height and water content areinversely correlated with amplitude of the SNR signal. Thereflected signal is completely suppressed when vegetationwater content exceeds 3 kg m-2, for example at peak growthat irrigated corn and alfalfa sites. We evaluated theoperational MP1rms statistic at hundreds of sites in NSF’sPlate Boundary Observatory (PBO) network for a five-yeartime period. MP1rms is a measure of multipath scattering; itexhibits a clear seasonal cycle as expected for vegetationgrowth and senescence. MP1rms is inversely correlated withNormalized Difference Vegetative Index (NDVI) at most PBOsites: there is more scattering of L-band signals at timeswhen vegetation is greener. The MP1rms variations lagNDVI by approximately three weeks, consistent with the ideathat green-up precedes plant growth. Once lag effects areconsidered, r2 values are typically > 0.8 at sites withconsiderable seasonal cycles in NDVI. Multipath statisticsare calculated daily from existing GPS stations and could beused to estimate biophysical properties to help constrainremotely sensed estimates of soil moisture.http://xenon.colorado.edu/reflections/GPS_reflections/Vegetation.htmlStephens, GraemeA CloudSat perspective of the atmospheric watercycle: recent progress and grand challengesIm, Eastwood 1 ; Stephens, Graeme 11. Jet Propulsion Laboratory, Pasadena, CA, USAThe CloudSat mission is unique in its view of theatmospheric processes of central importance tounderstanding the planetary water cycle. The sensitivity ofthe CloudSat radar (CPR) to all modes of precipitation andthe unique ability to connect this to cloud properties haveprovided important insights on precipitation formingprocesses in the atmosphere. The observations have yieldedthe first real global survey of snowfall, new insights on midlatitudeprecipitation and have provided stunning examplesof how aerosol affect warm rain processes in layered clouds.The results have further exposed a common problem in allGCMs in the over-occurrence of light precipitation rates(drizzle) at the surface. This is not only an issue forprecipitation forecasting, but can play a crucial role in therepresentation of low cloud layers over the oceans and it hasbeen shown is the reason for long-standing and significantmoisture biases in model, essential for the lifecycle ofstratocumulus among a number of factors. This talk willhighlight how global satellite observations are providing keyinsights on the planets water cycle and will provide a view ofwhat major challenges exist and future observational needsthat will address these challenges.136

Sturm, MatthewRemote Sensing and Ground-based SnowMeasurements: Limitations, Strengths, andOptimal BlendingSturm, Matthew 1 ; Liston, Glen 21. Terrestrial Sciences Branch, U.S.A. Cold Regions Research& Engineering Laboratory-Alaska, Ft. Wainwright, AK,USA2. Cooperative Institute for Research in the Atmosphere,Colorado State University, Ft. Collins, CO, USAAll snow measurements share six attributes: 1) support(S), 2) extent (E), 3) spacing (P), 4) repeat frequency (), 5)accuracy (A) and 6) work effort (W). Table I contrasts theseparameters for remote sensing vs. ground-basedmeasurements. Measurement resolution is a function of S, Eand P: the smaller S and P, the higher the resolution, butonly if E spans the snow structures or gradients of interest.Work effort (W) increases dramatically as E increases and Sand P decrease. Accuracy is related to S but in complex ways.In the case of remote sensing products, accuracy is alsodependent on having an appropriate and well-calibratedalgorithm and understanding how small-scale variationsaggregate electromagnetically, an area where ourunderstanding is currently limited. An optimal observingsystem would have a small support, a large extent, a closespacing, a low work effort, high repeat frequency, and highaccuracy. This appears to be impossible to achieve, so thebest hope is to blend systems, building on the strengths ofeach system, reconciling scaling weaknesses in each methodthrough clever combinations, using models to blend the two.We illustrate this idea using ground and remote sensing datafor snow-covered areas in Colorado and Alaska.http://www.crrel.usace.army.mil/sid/personnel/sturm.matthew.htmlTable I: Comparison of Remote and Ground-based MeasurementsSultan, MohamedAn Integrated (remote sensing, GIS, hydrogeology,geochemistry, geophysics, and hydrologicmodeling) Approach for a Better Understanding ofthe Hydrology of the Nubian Aquifer, NE AfricaSultan, Mohamed 1 ; Ahmed, Mohamed 1 ; Sturchio, Neil 2 ; Yan,Eugene 3 ; Milewski, Adam 4 ; Becker, Richard 5 ; Wahr, John 6 ;Becker, Doris 5 ; Chouinard, Kyle 11. Dept Geosciences, Western Michigan Univ, Kalamazoo,MI, USA2. Earth and Environmental Sciences, University Illinois atChicago, Chicago, IL, USA3. Environmental Sciences, Argonne National Laboratory,Argonne, IL, USA4. Geology, University of Georgia, Athens, GA, USA5. Environmental Sciences, University of Toledo, Toledo,OH, USA6. Physics, University of Colorado at Boulder, Boulder, CO,USAIntegrated studies (remote sensing, GIS, hydrogeology,geochemistry, geophysics, and hydrologic modeling) wereconducted to investigate the hydrologic setting of theNubian Sandstone Fossil Aquifer of northeast Africa, and toassess the response and of the system to climatic andanthropic forcing parameters. Results indicate: (1) theNubian Aquifer System is more likely to be formed of anumber of discrete sub-basins that are largely disconnectedfrom one another; (2) potential paleo-recharge areas weredelineated from SRTM and SIR-C data; (3) areas receivingmodern natural recharge were identified in northern Sudanand northeast Chad and locally in central and southernSinai using TRMM data; (4) recharge was estimated at 13.0 x10 6 m 3 by using a continuous rainfall-runoff model; (5) totalrecharge (10 11 m 3 ) from Lake Nasser to the aquifer wassimulated by using a calibrated groundwater flow model forperiods of high lake levels (1975 to 1983: 6 x10 10 m 3 ; 1993 to2001: 4 x 10 10 m 3 yr -1 ); (5) previously unrecognized naturaldischarge locations were identified by remote sensing,geophysics, and geochemistry, and quantified withhydrologic models along the River Nile basin and the Gulf ofSuez fault complexes; (6) analysis of monthly GRACE (April2002 through November 2010) indicated near steady-statesolutions in the south (Sudan: 8 mm yr -1 ; Chad: -9 mm yr -1 )and in Libya (-11 mm yr -1 ) and declining water supplies inEgypt (-35 mm yr -1 ) largely related to progressive increase inextraction rates with time.137

Sun, WenchaoEstimating River Discharge by the HydrologicalModel Calibrated Based on River Flow WidthDerived from Synthetic Aperture Radar ImagesSun, Wenchao 1 ; Ishidaira, Hiroshi 2 ; Bastola, Satish 31. College of Water Sciences, Beijing Normal University,Beijing, China2. University of Yamanashi, Kofu, Japan3. National University of Ireland, Maynooth, IrelandRiver discharge is an integral part of terrestrialhydrology and the overall hydrological cycle. Thehydrological is a common tool for estimating river dischargein the field of hydrology. The dependence on observed riverdischarge data for calibration restricts applications ofmodels in basins that the in situ observation is unavailable.In the last decade, the river cross-sectional water surfacewidth obtained from remote sensing images, especially fromthe synthetic aperture radar (SAR) which can penetrate theclouds, has been proved to be effective to trace riverdischarge from space. In this study, we present a methodusing river widths measured from SAR images for calibratingrainfall-runoff models based on at-a-station hydraulicgeometry. One distinct advantage is that this calibration isindependent of river discharge information. To explore thefeasibility of the proposed calibration scheme intensively andanalyse the uncertainty in the modelling processquantitively, the generalized likelihood uncertaintyestimation (GLUE) was applied. The method is illustratedthough a case study in the Mekong basin. The resultsindicate that the satellite observation of river width is acompetent surrogate of observed discharge for thecalibration of rainfall-runoff model. This study contributesto river discharge estimation in basins that no in situgauging is available.Ensemble simulations of river dischargeSur, ChanyangRelationship of Remote sensing-basedEvapotranspiration and Eco-hydrological Factor;Water Use EfficiencySur, Chanyang 1 ; Choi, Minha 11. Civil and Environment Engineering, Hanyang University,Seoul, Republic of KoreaWater Use Efficiency (WUE) as an eco-hydrologicalparameter, is an index that how amount ofevapotranspiration (ET) is used for vegetative productivity.This index is defined as the ratio of Gross PrimaryProductivity (GPP) and ET per unit area. In this study, weextracted GPP and estimated ET using Moderate ResolutionImaging Spectroradiometer (MODIS) image data tocompute spatio-temporal distribution of WUE in North-East Asia. The WUE will contribute to understand the rolevegetative activity on hydrologic cycle in the ecosystem. Mainpurpose of this study is to understand relationship betweenWUE and remote sensing based ET. ET includingevaporation from a land surface and transpiration fromphotosynthesis of vegetation is a sensitive hydrologicalfactor with outer circumstances. Direct measurements EThave a limitation that the observation can stand for theexact site, not for an area. Remote sensing technique isadopted to compensate the limitation of ground observationusing the Moderate Resolution Imaging Spectroradiometer(MODIS) multispectral sensor mounted on Terra satellite.Based on this study, we estimated Penman-Monteith basedevapotranspiration in North-East Asia and compared withremote sensing based WUE in order to understand theinteraction between atmosphere and vegetation activity.The schematic description of the method138

Sutanudjaja, Edwin H.Using space-borne remote sensing products tocalibrate a large-scale groundwater model: a testcasefor the Rhine-Meuse basinSutanudjaja, Edwin H. 1 ; van Beek, Ludovicus P. 1 ; de Jong,Steven M. 1 ; van Geer, Frans C. 1, 3 ; Bierkens, Marc F. 1, 21. Department of Physical Geography, Faculty ofGeosciences, Utrecht University, Utrecht, Netherlands2. Unit Soil and Groundwater Systems, Deltares, Utrecht,Netherlands3. Netherlands Organization for Applied Scientific ResearchTNO, Utrecht, NetherlandsCalibration of large-scale groundwater models isdifficult due to a general lack of groundwater headmeasurements and the disparity between nationalobservation systems in case of trans-boundary aquifers. Inthis study, we explore the possibility to calibrate such modelsusing space-borne remote sensing products. As the test bed,we use the combined Rhine-Meuse basins (200,000 km2).For this region, an extensive groundwater head database isavailable. However, head observations were used forvalidation only and the model was calibrated solely using aspace-borne soil moisture product (European RemoteSensing Soil Water Index: ERS-SWI), combined with riverdischarge observations from the Global Runoff Data Centre(GRDC). The model itself has been set up using globaldatasets only, such that the modeling procedure is generallyportable to other areas of the world including data poorenvironments. The hydrological model used is a tightcoupling of a land surface model, which conceptualizes theprocesses above and in the unsaturated zone layer, and aMODFLOW-based groundwater model simulating saturatedlateral flow. Together both model parts simulate thedynamic interaction between surface water and groundwaterbodies, and between the unsaturated soil and the saturatedgroundwater zones on a daily basis and with a spatialresolution of 1 km. Calibration is carried out by adjustingaquifer characteristics, and land surface and soil physicalparameters. State variables used in calibration are theunsaturated zone/soil moisture storage and river discharge.Here we performed two calibration methods: (i) calibrate themodel using river discharge measurements only; and (ii)calibrate the model by using a combination of riverdischarge and remotely sensed ERS SWI (soil moisture)products. Results are promising and suggest that it ispossible to use satellite remote sensing derived products asan additional constraint in the calibration of large-scalegroundwater models. Comparing the model results of (i) to(ii) with observed groundwater head time series data, weconclude that important model improvements can be madeby integrating models with remote sensing products. Weargue that, in the absence of groundwater headmeasurement data, space-borne remote sensing products areuseful products for calibrating groundwater models.Sweigart, MaileDrought Characterization of the Las Vegas Valleyusing Satellite Observations of TerrestrialGroundwater StorageSweigart, Maile 1 ; Nowicki, Scott 11. University of Nevada, Las Vegas, Las Vegas, NV, USAThe declining water levels of the Las Vegas Valleyaquifers and the half-empty Lake Mead is an issue of greatconcern. The decrease of water storage in the region can beattributed to natural environmental factors, such aschanging rainfall patterns and evaporation, but climatechange may also be a contributing factor. This projectutilizes data from NASA and numerous other agencies forhydrogeological comparisons and calculations to assess thepossible effect of climate change on groundwater storage inthe Las Vegas Valley. Historical hydrogeological data fromthe area, combined with satellite imagery observations, werecollected and various calculations were made for datacomparisons. Analyzed results reveal trends in the decliningwater levels in Lake Mead and the Las Vegas Valley aquifersin recent years. Graphed results show similar trends betweenGRACE (Gravity Recovery and Climate Experiment) satellitedata and the declining levels of Lake Mead. The observationsof GRACE total water storage, precipitation,evapotranspiration and the net flux of water in the area allshow a similar trending decline in yearly wateraccumulation, which may be indicators of the impact ofdrought and climate change in Southern Nevada. This datawill not only help predict future water level decreases of thelake, but it will also show any adverse affects that climatechange may be having on the area. As Lake Mead declines,there will be a corresponding increase in the rate at whichthe Las Vegas metropolitan area will be dependent on itsaquifers for water. Due to the fact that treated Lake Meadwater is used to recharge aquifers, the decreasing water levelsof the lake could also affect aquifer-recharging efforts. Theanalyzed hydrogeological data will reveal any impact ofclimate change not only on Lake Mead, but also the impactit has on the groundwater in the aquifers and, in turn, theimpact it has on the Las Vegas metropolitan area’s watersupply in general.Swenson, Sean C.A Gridded GRACE Total Water Storage Dataset forHydrological ApplicationsSwenson, Sean C. 1 ; Landerer, Felix W. 21. NCAR, Boulder, CO, USA2. Jet Propulsion Laboratory, Pasadena, CA, USASince about 2003, the GRACE satellite mission hasgenerated data that have been used to estimate total waterstorage variations. These data have been valuable formonitoring groundwater and surface water changes, regionalwater balance studies, and model evaluation. However,widespread utilization of GRACE data has been hindered bythe need for sophisticated data-processing techniques. In139

esponse to this need, a global, gridded GRACE total waterstorage dataset has been created. In this presentation, wedescribe this publicly available dataset, which possesses thefollowing features. The raw GRACE spherical harmoniccoefficients have been filtered to remove measurementerrors, and converted to a 1 degree by 1 degree grid. Toreduce the possible signal modification induced by theapplication of the filter, gain factors are calculated fromsynthetic GRACE data derived from land model simulations.Finally, an error budget composed of both residualmeasurement and leakage errors is determined for eachgridcell. Regional time series computed from the griddeddataset agree very well with time series computed directlyfrom the GRACE coefficients. This allows users to createtotal water storage time series for arbitrary regions that canbe combined or compared to other hydrological datasetsdirectly, without the need for expertise in GRACE dataprocessing.Tang, QiuhongTerrestrial Water Storage Variations from GRACEand Water Budget in Major River Basins of ChinaTang, Qiuhong 1 ; Leng, Guoyong 1, 21. Institute of Geographic Sciences and Natural ResourcesResearch, Beijing, China2. Graduate School of Chinese Academy of Sciences, Beijing,ChinaTerrestrial water storage (TWS) is an integrated measureof water storage that includes surface waters, soil moisture,groundwater, and snow and land ice where applicable. Thevariation in TWS, which indexes the general dry or wetcondition of a river basin, is essential for betterunderstanding of regional variations in soil moisture andgroundwater. The Gravity Recovery And Climate Experiment(GRACE) mission can provide monthly TWS variations since2002. This study compares the TWS variations from GRACEwith the estimates from water budget method in the majorriver basins of China. We use river gauge data andobservation-based precipitation and land surfaceevapotranspiration (ET) data to derive TWS variation termof the water budget equation. The streamflow data arecollected from the Annual Reports of Water ResourcesBulletin. The precipitation data are extended from thegridded precipitation data of China MeteorologicalAdministration (CMA). The gridded CMA precipitationdataset is available only in the period 1962-2002. The stationprecipitation observations are collected from CMA through2009. In order to produce a gridded precipitation datathrough 2009, the Synagraphic Mapping System (SYMAP)algorithm is used to interpolate the station observations.The monthly mean SYMAP gridded precipitation data arescaled to match the monthly mean CMA precipitation in ahistorical period 1962-1991. ET is estimated using a satellitebasedapproach developed at the University of Washington.The approach uses primarily the Moderate ResolutionImaging Spectroradiometer (MODIS) data and theInternational Satellite Cloud Climatology Project (ISCCP)surface radiation fluxes. The satellite-based ET estimates arecompared with the estimates from water budget methodthat inferred ET from GRACE water storage variations,precipitation and streamflow observations. The ET estimatesfrom the water budget method were used to adjust the longtermmean of the satellite-based ET estimates. Theadjustment is performed to achieve a long-term waterbalance that may not be naturally ensured because of thedata inconsistency from different sources and differentscales. The adjusted ET estimates are used to generate thetime series of TWS variations in the major river basin ofChina. The long-term trend of TWS should have beendamped because of the ET adjustments. However, the interannualand inter-seasonal variations of TWS are comparableto the GRACE observations. The comparisons between thewater budget TWS and GRACE TWS show generalagreement on the peak storage in the wet year and lowstorage in the dry year. Both estimates capture the jump ofTWS in the Yangtze River due to the impoundment of theThree Gorges Reservoir. It indicates the GRACE observationsprovide unique information towards large scale water budgetstudy.Tapiador, Francisco J.Comparing Precipitation Observations, SatelliteEstimates and Regional Climate Model Outputsover EuropeTapiador, Francisco J. 11. UCLM, Toledo, SpainRegional Climate Models (RCMs) are downscaling toolsused to improve the spatial resolution of outputs fromreanalyses and Global Climate Models (GCMs). RCMs havebeen proven useful to analyze changes in precipitation inglobal warming scenarios, but the issue of how well can theyactually reproduce present climate is always hovering overthis research field. Drawing on data from the PRUDENCEand ENSEMBLE projects, it has been shown that RCMsprovide consistent estimates of precipitation when comparedwith observations and with satellite data sources, especiallyafter accounting for the known uncertainties in the referencedata. The agreement with observations builds confidence inmodels been capable of simulating the climates of thefuture.Tapley, Byron D.The Status of the GRACE Mass Flux MeasurementsTapley, Byron D. 1 ; Bettadpur, Srinivas 1 ; Watkins, Michael 21. Ctr Space Research, Univ Texas Austin, Austin, TX, USA2. NASA Jet Propulsion Laboratoty, Pasadena, CA, USAThe measurements of mass transport between theearth’s atmosphere, oceans and solid earth is a criticalcomponent of global climate change processes and is animportant component of the signals associated with globalsea level and polar ice mass change, depletion and rechargeof continental aquifers, and change in the deep oceancurrents. This mass exchange has a gravitational signal,140

which can be monitored as an indication of the on-goingdynamical processes. The Gravity Recovery and ClimateExperiment (GRACE) is a mission designed to make thesemeasurements. The major cause of the time varying mass iswater motion and the GRACE mission has provided acontinuous measurement sequences, now approaching 10years, which characterizes the seasonal cycle of masstransport between the oceans, land, cryosphere andatmosphere; its inter-annual variability; and the secular, orlong period, mass transport. Measurements of continentalaquifer mass change, polar ice mass change and oceanbottom currents are examples of new remote sensingobservations enabled by the GRACE satellite measurements.Recent emphasis on providing a rapid product withenhanced temporal resolution has opened the possibilities ofusing the GRACE measurement for operational hydrologyproducts. This presentation will review the current missionstatus and science accomplishments, discuss project effortsto improve the spatial and temporal sampling, describe theimprovement expected with the planned RL05 data releaseand discuss the impact of these results on contemporaryearth system studies studies.Teng, William L.NASA Giovanni: A Tool for Visualizing, Analyzing,and Inter-comparing Soil Moisture DataTeng, William L. 1, 3 ; Rui, Hualan 2, 3 ; Vollmer, Bruce 3 ; de Jeu,Richard 4 ; Fang, Fan 2, 3 ; Lei, Guang-Dih 2, 31. Wyle IS, Greenbelt, MD, USA2. Adnet, Greenbelt, MD, USA3. NASA GES DISC, Greenbelt, MD, USA4. Vrije Universiteit Amsterdam, Amsterdam, NetherlandsThere are many existing satellite soil moisturealgorithms and their derived data products, but there is nosimple way for a user to inter-compare the products oranalyze them together with other related data (e.g.,precipitation). An environment that facilitates such intercomparisonand analysis would be useful for validation ofsatellite soil moisture retrievals against in situ data and fordetermining the relationships between different soilmoisture products. The latter relationships are particularlyimportant for applications users, for whom the continuity ofsoil moisture data, from whatever source, is critical. A recentexample was provided by the sudden demise of Aqua AMSR-E and the end of its soil moisture data production, as well asthe end of other soil moisture products that had used theAMSR-E brightness temperature data. The purpose of thecurrent effort is to create an environment that facilitatesinter-comparisons of soil moisture algorithms and theirderived data products. As part of two NASA ROSES-fundedprojects, with end user project team members from NOAANational Weather Service (NWS) and USDA WorldAgricultural Outlook Board (WAOB), three daily Level 3 soilmoisture products have been incorporated into a prototypeNASA Giovanni Soil Moisture portal: (1) AMSR-E/Aqua(POC: E. Njoku, JPL), (2) Land Surface Microwave EmissionModel (LSMEM)-TMI (POC: E. Wood, Princeton U.), and (3)Land Parameter Retrieval Model (LPRM)-AMSR-E (POC: R.de Jeu, Vrije U. Amsterdam). The portal also contains TRMM3B42-V6 precipitation and AIRS/Aqua surface airtemperature data and has a suite of basic services (lat-lonmap, time series, scatter plot, and animation). Other existingGiovanni services will be added as appropriate. As well, newsoil moisture and related products will be added, resourcespermitting. Current work is focused on replacing the lostAMSR-E/Aqua data stream, by applying LPRM to theTRMM Microwave Imager (TMI) and WindSat brightnesstemperatures. Other possible soil moisture products includethe Single-Channel Algorithm (SCA)-AMSR-E (POC: T.Jackson, USDA ARS) and model outputs from the GlobalLand Data Assimilation System (GLDAS) and the NorthAmerican Land Data Assimilation System (NLDAS)(aggregation to daily would be needed for the latter two).Examples of Giovanni outputs will be shown, of somenotable recent events, such as the Texas drought of summer2011. The Giovanni Soil Moisture portal is versatile, withmany possible uses, for applications such as natural disasters(e.g., landslides) and agriculture (e.g., crop yield forecasts). Itshould also prove useful for pre-launch SMAP activities (e.g.,“Early Adopters” program).Thakur, Praveen K.Inter Comparison of Satellite and Ground BasedRainfall Products - A Case Study for IndiaThakur, Praveen K. 1 ; Nikam, Bhaskar R. 1 ; Garg, Vaibhav 1 ;Aggarwal, S. P. 11. Water Resources Division, Indian Institute of RemoteSesning (IIRS), Dehradun, IndiaRainfall is one of the most important hydrologicalcomponent in hydrology, earth’s water and energy cycle andwater balance studies. Accurate information on amount andintensity of rainfall is important for agriculture and powerwater management, flood and drought studies andgroundwater recharge. Spatial and temporal variations inrainfall necessitates the use ground based rain gauges,weather radars and space based, satellite derived rainfallestimates. In present study, the inter comparison of variousgridded rainfall products of India MeteorologicalDepartment (IMD), Tropical Rainfall Measuring Mission’s(TRMM) (3B42 and 3B43), Climate prediction centre (CPC)and Asian Precipitation - Highly-Resolved ObservationalData Integration Towards Evaluation of Water Resources(APHRODITE’s Water Resources) data has been carried outfor entire India. Analysis was done on full country as well asstate and agro-climate zone wise. This study has used IMD’srain gauge derived gridded rainfall data as the base rainfallfor comparing the other rainfall data products. This studyshows that all the satellite based rainfall products areunderestimating the total rainfall, except for year 2004 asshown in figure below. It was found that there is consistentunderestimation of 7.0 to 10 % in total annual rainfall. It isconcluded that, in case of non-availability of IMD rainfalldata, these satellite based rainfall products can be utilized141

for various water resources studies with certain degree oferror and uncertainty.Thenkabail, Prasad S.Water Use and Water Productivity of Key WorldCrops using Hyperion-ASTER, and a LargeCollection of in-situ Field Biological and SpectralDataThenkabail, Prasad S. 1 ; Mariotto, Isabella 11. Geography, U.S. Geological Survey, Flagstaff, AZ, USAThe overarching goal of this study is to assess water useand water productivity of key world crops using Hyperion-ASTER and a large collection of in-situ field biological andspectral data. The study will be based on existing datasets,collected during the 2006 and 2007 crop growing seasons,over large-scale irrigated areas of the arid Syr Darya riverbasin (444,000 km2) in Central Asia where recent studiesshow snowmelt water supplies from Himalayas are on swiftdeclines. The irrigated cropland data acquired include: (a)Hyperion narrow-band data (5 images) from EarthObserving-1 (EO-1), (b) spectroradiometer data from 400-2500 nanometers, (c) broad-band data from ASTER as wellas ETM+, ALI, IKONOS, and Quickbird, and (d) field-plotbiological data. The field-plot data of 5 crops (wheat, cotton,maize, rice and alfalfa) were collected, every 15-20 days,throughout the summer crop growing seasons (April-October) of 2006 and 2007 for a total of 1003 samplelocations and consisted of: several thousand spectralmeasurements, crop variables (e.g. biomass, LAI, yield), soiltype and salinity, water variables (e.g., inflow, outflow), andmeteorological data (e.g., rainfall, ET). The study of 5 cropsusing Hyperion-ASTER-field spectral and biological datawill: (a) develop and test water productivity models (WPMs),(b) establish shifts in phenology depicting canopies’integrated response to environmental change and\orcontrolled-planted by humans, (c) highlight best performinghyperspectral water indices (HWIs); and (d) establish chiefcauses of water productivity variations and identifyhyperspectral wavebands and indices that are most sensitiveto them. The water productivity (WP; kg\m3) is obtained bydividing crop productivity (CP kg\m2; based on the bestHyperion models) by water use (WU; m3\m2; based on thebest ASTER models). Water use of irrigated crops will bedetermined by the Simplified Surface Energy Balance Model(SSEBM), which is derived by multiplying evaporativefraction obtained using ASTER thermal imagery withreference ET derived from the Penman-Monteith equation.Crop productivity is determined through the besthyperspectral models. Hyperspectral wavebands and indicesin studying water productivity, water use, and phenology willbe established and will involve: (a) two-band vegetation index(TBVIs) models, (b) Optimum multiple-band vegetationindex (OMBVI) models, (c) derivative index models, (d)broad-band models (NIR-red based, mid-infrared, soiladjusted,and atmospherically corrected), (e) principalcomponent analysis, (f) discriminant or separability analysis(e.g., stepwise discriminant analysis), and (g) crop waterstress indices using red-edge, NIR and SWIR water bands, aswell as thermal bands. The outcome of the research will leadto: 1. Determining proportion of irrigated areas in low,medium, or high water productivity (WP; kg\m3) and theirdrivers (management practice, soil type, salinity status, etc.);3. Pin-pointing areas of low and high WP, 3. Establishingwater use (m3\m2) of 5 irrigated crops, and 4.Recommending optimal Hyperion waveband centers andwidths, in 400 to 2500 nanometer range, required to beststudy irrigated cropland characteristics;Thenkabail, Prasad S.Global croplands and their water use assessmentsthrough advanced remote sensing and non-remotesensing approachesThenkabail, Prasad S. 11. Geography, U.S. Geological Survey, Flagstaff, AZ, USAThe global cropland area estimates amongst differentstudies are quite close and range between 1.47 to 1.53 billionhectares. The total water use by global croplands, estimatedbased on existing cropland maps, varies between 6,685 to7500 km3 yr-1; of this 4,586 km3 yr-1 is by rainfed croplands(green water use) and the rest by irrigated croplands (bluewater use). Irrigated areas use about 2,099 km3 yr-1 (1,180km3 yr-1 of blue water and the rest by rain that falls directlyover irrigated croplands). However, 1.6 to 2.5 times the bluewater required by irrigated croplands (1,180 km3 yr-1) isactually withdrawn (from reservoirs or pumping of groundwater) making irrigation efficiency of only between 40-62percent. However, there are major uncertainties indetermining: a) precise location of croplands; (b) whethercrops were irrigated or rainfed; (c) exact crop types and theirphenologies; and (d) cropping intensities. This in turn leadsto uncertainties in green water use (from rainfed croplands)and blue water use (from irrigated croplands) computations.Given that about 80% of all human water use goes towardsagriculture, precise estimates of global croplands and theirwater use is of major importance. The causes of differenceswere as a result of definitions in mapping, data types used,methodologies used, resolution of the imagery, uncertaintiesin sub-pixel area computations, inadequate accounting ofstatistics on minor irrigation (groundwater, small reservoirsand tanks), and data sharing issues. To overcome the abovelimitations this research proposes an implementationstrategy to produce products using advanced remote sensing142

tools and methods to address one of the biggest challengeshumanity will face in coming decades: how to adequatelyfeed a projected population of about 10 billion people by2050 in a changing climate and increasingly water-scarceworld without having to increase present allocations ofcroplands and\or water. In order to achieve this goal, wepropose and discuss a strategy to map global irrigated andrainfed cropland areas by fusing Landsat GLS2005 data withMODIS time-series (2004-2006), secondary data (e.g., longterm precipitation-temperature-evapotranspiration, GDEM),and a large collection of in-situ data. Finally, the paper willdiscuss the increased certainties in global blue water andgreen water computations.http://powellcenter.usgs.gov/current_projects.php#GlobalCroplandsHighlightsThenkabail, Prasad S.Selecting Areas of Wetland Cultivation andPreservation in Africa: Satellite Sensor Data FusionSynthesized with Socio-economic data in a SpatialModeling Framework to Support Africa’s Greenand Blue RevolutionThenkabail, Prasad S. 11. Geography, U.S. Geological Survey, Flagstaff, AZ, USATo prioritize the use and conservation of wetlands, thisresearch will produce multi-resolution inland valley (IV)wetland data and map products for all the 24 West andCentral African (WCA) Nations, by fusing multiple datasets.Data sources will be: (a) Global Land Survey 2005(GLS2005) 30m, (b) ENVISAT ASAR after 2002 (widescan100-150m), ALOS PALSAR wide-beam (after 2006), and JERSSAR 100m, (c) MODIS 250-500m Terra\Aqua monthly timeseriesfor 2001-<strong>2012</strong>; (d) Space Shuttle Topographic Mission(SRTM) 90m, and (f) extensive socio-economic and in-situdata on health hazards in wetland development, access fromwetlands to roads and markets, available credit, richness oftheir soils, and crops grown in wetlands and their water use.The outcome will enable and support decision-making thatwill pin-point IV wetland areas that are (1) best suited forcultivation, and (2) prioritized for conservation. Thewetlands of West and Central Africa (WCA) are increasinglyconsidered “hotspots” for agricultural development and forexpediting Africa’s Green and Blue Revolution*. Currently,these IV wetlands are un-utilized or highly under-utilized inWCA in spite of their rich soils and abundant wateravailability as a result of: (a) limited road and market access,and (b) prevailing diseases such as Malaria, Trypanosomiasis(sleeping sickness) and Onchocerciasis (river blindness).However, the utilization of IV wetlands for agriculture isbecoming unavoidable in WCA countries due to increasingpressure for food from a ballooning human population anddifficulty finding arable uplands. It is also critical torecognize important functions of wetlands, which includeholding about 20% of all carbon on earth and providinghabitat for unique and rare flora and fauna. Therefore, anyproposed use of wetlands for agriculture has to be carefullyweighed against the socio-economic benefits provided by theinherent ecological services of conserved and intactwetlands. In order to address the issue of development vs.conservation of wetlands, this work will produce and provideaccess to critical maps and models for informed decisionmakingby local and regional stakeholders. Data andproducts developed here will be actively promoted andwidely disseminated to stakeholders through WCA networks(e.g.,CARD\AGRA, CGIAR CSI), keeping in mind asustainable-environmentally-ecologically-climaticallyfriendly development agenda.Trenberth, Kevin E.Challenges for Observing and Modeling the GlobalWater Cycle INVITEDTrenberth, Kevin E. 11. Climate Analysis Section, NCAR, Boulder, CO, USAObservations of climate system components andforcings are increasingly needed for planning and decisionmaking related to climate services. Although significantprogress has been made, much more remains to be donebefore a fully functional climate observing system exists.Observations are needed on all spatial scales from local toglobal, and all time scales, especially to understand anddocument changes in extremes. A major challenge is toadequately deal with the continually changing observingsystem, especially from satellites. Even with newcomputational tools, further challenges remain to provideadequate analysis, processing, meta-data, archival, access,and management of the resulting data and the dataproducts. The main synthesis of all observations, includingthose from remote sensing from space, is in the globalreanalyses. An assessment of hydrological cycles from eightcurrent atmospheric reanalyses and their depiction ofchanges over time reveals substantial shortcomings andsensitivity to the observing system and its changes over time.Using model-based precipitation P and evaporation E, thetime and area average E-P for the oceans, P-E for land, andthe vertically integrated atmospheric moisture transportfrom ocean to land should all be identical but are not closein most reanalyses, and often differ significantly fromobservational estimates of the surface return flow based onnet river discharge into the oceans. Most reanalysis models,the exception being MERRA, have too intense water cycling(P and E) over the ocean. There is a tendency for moisture tobe quickly rained out in models, with the lifetime too shortand the recycling too large in models. The large-scalemoisture budget divergences are more stable in time andsimilar across reanalyses than model-based estimates of E-P.Major improvements are needed in model treatment andassimilation of moisture, and E and P from reanalysesshould only be used with great caution. Moreover, use ofglobal reanalyses for downscaling clearly also has limitationsthat should be appreciated.http://www.cgd.ucar.edu/cas/trenbert.html143

Tripoli, Gregory J.Trends in Evapo-transpiration in the Great LakesStatesTripoli, Gregory J. 1 ; Kung, Sam 21. Atmospheric and Oceanic Scienc, University of Wisconsin- Madi, Madison, WI, USA2. Soil Science, University of Wisconsin - Madison,Madison, WI, USARecently, an alarming drop in lake levels and water tablelevels in the Central Sands of Wisconsin over the past 12years has raised concerns with regard to the relationshipbetween domestic, agricultural and natural uses of water.Angry residents have argued that high capacity wells beingused by agriculture are draining water supplies, vital to therecreational industry. Others suggest that forests,particularly conifer forests, use as much or more waterannually as agriculture where fields are dormant for much ofthe year. Recent hydrological studies, carried out inWisconsin, used measurement of stream flow andprecipitation over the past 12 years and in a more limitedstudy, over the past century demonstrated that suggestedthat (1) the precipitation over the State has remainedrelatively constant, and (2) stream flow is decreasing statewide, suggesting that evapo-transipration has beenincreasing, particularly in the last 12 years. This is due insome part for an increase in the length of the growingseason and the ice free period over historic periods. Inaddition, these studies have found that the climatologicalseasonal profile of precipitation has been changing from amore flat or constant rate across the warm season, to onedominated by drought with interludes of heavyprecipitation, particularly in the early months and latemonths of the growing season when plant life cannot benefitas much. These studies seem to suggest that the recentchanges in the evapo-transpiration rate over Wisconsin maybe indicative of a general trend affecting the entire GreatLakes Basin, rather than being focused on the Central Sandsof Wisconsin, and are not a result of local excessive wateruse. In fact, the documented changes in Wisconsin, showshorter term variability consistent with the climaticfluctuations of the ENSO cycle, and perhaps consistent alsowith long term climate change. To learn more about theregional footprint of how evapo-transpiration has beenchanging, the authors have proposed a study to NASA to useModis to document the evolution of the growing season overthe past 10-12 years. The results of the completed water cyclebudget studies in Wisconsin and the progress on basin widestudies using satellite will be shown at the oral presentation.http://cup.aos.wisc.edu:/NEWSTsend-Ayush, JavzandulamGenerating a long-term vegetation index datarecord from AVHRR and MODISTsend-Ayush, Javzandulam 1 ; Miura, Tomoaki 11. Natural Resources and Environmental Management,University of Hawaii, Honolulu, HI, USAA long-term global data record of spectral vegetationindex (VI) is considered one of the key datasets for water andenergy, and terrestrial carbon cycle studies. Such a long-termdata record needs to be constructed from multi-sensor data.However, extending a VI data record from one sensor toanother requires ensuring cross-sensor continuity andcompatibility because datasets from different sensors are notexactly the same due to differences in sensor/platformcharacteristics and product generation algorithms. In thisstudy, we evaluated cross-sensor Normalized DifferenceVegetation Index (NDVI) compatibility for translating theLong-term Data Record (LTDR) AVHRR NDVI dataset to aTerra MODIS-compatible dataset by “top-down”, directimage comparisons. There was about one year of anoverlapping observation period for NOAA-14 AVHRR andTerra MODIS in years 2000-2001; however, the LTDRAVHRR product for that period was not generated due tosignificant orbital drift. Thus, we designed our compatibilityanalysis approach to use SPOT-4 VEGETATION (VGT) forbridging the AVHRR to MODIS datasets. Three global daily5-km datasets, LTDR NOAA-14 AVHRR NDVI, TerraMODIS Climate Modeling Grid (CMG) NDVI, and VGT S1NDVI, were obtained for their overlapping periods ofobservations (1998-1999 for AVHRR, 2001-2002 for MODIS,and 1998-1999 and 2001-2002 for VGT). A set of twocomparisons were made for (1) AVHRR vs. VGT and (2) VGTvs. MODIS. Cross-sensor NDVI compatibility was measuredand analyzed using agreement coefficients (ACs), whichcomputes a set statistics for evaluating the degree ofagreement between two datasets, including R2 values,geometric mean functional regression (GMFR), andsystematic and unsystematic differences. Our analysisshowed good linear agreements for both sensor pairs (R2 =0.53 for AVHRR and VGT and R2 = 0.95 for VGT andMODIS). GMFRs indicated that MODIS NDVI was slightlyhigher than that of VGT and that VGT NDVI was largerthan that of AVHRR. Likewise, these systematic differenceswere larger for larger NDVI values for both pairs.Unsystematic differences, which are measured as scatteringabout the mean trend (GMFR line) in AC, were larger for theAVHRR-VGT pair than for the VGT-MODIS pair. Furtherevaluation of systematic and unsystematic differencesindicated that the viewing angle constraint could improvethe predictive power of the regression equations as itincreased consistency (i.e., similar observation geometry) ofpaired observations. This study suggests that compatibilityof the NDVI from AVHRR to MODIS is achievable, but theconsiderations of sensor geometry, aerosols, residual cloudcontaminations, and surface conditions are needed to reduceunsystematic differences or uncertainties in cross-sensortranslation.144

Vanderjagt, Benjamin J.How sub-pixel snow depth, vegetation, and grainsize variability affect the ability to estimate largescaleSWE from microwave measurements in alpineareasVanderjagt, Benjamin J. 1 ; Durand, Michael 1 ; Margulis, Steve 2 ;Kim, Ed 3 ; Molotch, Noah 41. Ohio State, Columbus, OH, USA2. University of California at Los Angeles, Los Angeles, CA,USA3. NASA Goddard Space Flight Center, Greenbelt, MD, USA4. University of Colorado at Boulder, Boulder, CO, USACurrent methods to retrieve snow water equivalent(SWE) using passive microwave (PM) remote sensingmeasurements are often characterized by large uncertaintieswhich result from the natural heterogeneity of snowpackand vegetation within the microwave footprint. Snowpackheterogeneities include snow grain size, snow depth, andlayering of snowpack. Vegetation height, needle or leafdensity, and species also vary within microwave footprints. Itis not currently understood the extent to which the passivemicrowave measurement is sensitive (or insensitive) to SWE(as well as to the different variables listed above), as afunction of the scale of the microwave measurement. In ourinvestigation, we utilized the multi-scale Cold LandProcesses Experiment dataset for in situ and microwavedatasets. In order to better characterize the effect thatvariability in the snowpack and vegetative states has on themicrowave observation as function of scale, we conductanalysis in two different ways. 1) First, we estimate what weexpect the observed radiances (brightness temperature) to beat specific locations, based on in situ and LiDAR derivedsnow data gathered from those same locations, using aradiative transfer model (RTM). We then compare ourestimated radiances to the actual observed radiances, andcharacterize the errors, as a function of the variability of thedifferent snowpack and vegetative properties. 2) Based onthe “real” variability of snow and vegetative states, we willcreate synthetic observations of microwave brightnesstemperatures, and perturb the different snowpack andvegetative properties in order to examine the extent to whichthe synthetic microwave signal is affected by each individualproperty, at differing scales. Based on the synthetic analysisdescribed above, there still exists sensitivity to the meansnow depth within microwave footprints, even with highlyheterogeneous alpine snowpack and snow grain exponentialcorrelation lengths ranging from 0.05-0.3 millimeters.Furthermore, we find that the modeled microwave signal issensitive to the mean snow depth even as we aggregate tolarger scales. We also characterize the effect to whichvegetation attenuates the microwave observation, as afunction of the forest cover contained within the PMfootprint. We find that even relatively little forest coverwithin the subpixel (> 15%) can increase the microwavemeasurement by up to 10 K, as well as reduce the signal-tonoiseratio between the microwave measurements and theSWE. While the increase in brightness temperature can inprinciple be accounted for in SWE retrieval algorithms, thedecrease in signal-to-noise ratio results in a loss ofinformation about SWE. The primary research advance thatwe expect from our work is a fundamental understanding ofthe sensitivity (or lack thereof) of the passive microwaveobservation to spatial average SWE as a function of the scaleof the microwave measurement. Limiting cases, such as thethreshold vegetation cover fraction at which SWE is nolonger retrievable are discussed.Varhola, AndrésCombining Coordinate-Transformed AirborneLiDAR and LANDSAT Indices to Obtain ForestStructure Metrics Relevant to DistributedHydrologic ModelingVarhola, Andrés 1 ; Coops, Nicholas C. 11. University of British Columbia, Vancouver, BC, CanadaCurrent remote sensing technologies are not yet capableof directly and reliably measuring snow water equivalent atspatial and temporal resolutions adequate for the estimationof streamflow and flood risk in snow-dominatedcatchments. Hydrologists therefore depend on detailedprocess-based hydrologic models to simulate snowaccumulation and depletion patterns, which are in turnhighly affected by the presence and structure of vegetation.However, the lack of spatially-explicit and relevant foreststructure metrics needed to parameterize these models overlarge basins has led to the use of oversimplifiedrepresentations of heterogeneous forested landscapes,introducing additional uncertainties to predictions. One keyremote sensing technology that has demonstratedsignificant potential for measuring forest structure is LightDetection and Ranging (LiDAR). As airborne LiDARbecomes more available across larger areas, its use as a driverof vegetation structure for hydrologic models has alsobecome increasingly important. Traditional hydrologicmodels require four vegetation structure metrics —leaf areaindex (LAI), sky-view factor (SVF), canopy cover and height—to simulate processes related to radiation fluxes, windattenuation, snow or rain interception andevapotranspiration. In this study we developed a novelmethodology with two objectives: a) derive these fourstructural metrics at the tree and plot levels using a LiDARdataset, and b) explore their relationships with Landsatderivedvegetation and foliar moisture indices forextrapolation purposes. To achieve this we projected LiDARreturns into a polar coordinate system to generate synthetichemispherical images that directly provided LAI and SVFwhen calibrated with their field-based optical counterparts,whereas canopy cover and height were accurately obtainedfrom LiDAR without coordinate transformation. Themethod allowed the retrieval of these metrics at any locationwithin the 8,000 ha LiDAR transect we acquired in centralBritish Columbia, resulting in a sampling design thatincluded 376 different Landsat pixels and nearly 16,000synthetic images. Results indicated that the EnhancedVegetation Index, and spectral brightness and greenness are145

potentially good predictors of LAI and SVF, while a foliarmoisture index was the best predictor of forest cover in thisarea. The combined use of LiDAR and Landsat showed goodpotential to generate accurate, fully-distributed vegetationmetrics required by hydrologic models, and the specificmethodologies we developed demonstrated applicability to awide range of forest stand types of different age, height,density and health status.Velicogna, IsabellaIncrease in groundwater storage in discontinuouspermafrost areas in Eurasia and impact onvegetation productivityVelicogna, Isabella 1, 2 ; Tong, Jinjun 1 ; Kimball, John 4 ; Zhang,Tingjun 31. Dept of Earth System Science, Univ of California Irvine,Irvine, CA, USA2. JPL, Pasadena, CA, USA3. University of Colorado, Boulder, CO, USA4. University of Montana, Polson, MT, USAWe use monthly measurements of time-variable gravityfrom the GRACE (Gravity Recovery and ClimateExperiment) satellite mission to determine the increase interrestrial water storage (TWS) in Eurasia, during the period2002-2011. We compare monthly TWS from GRACE withTWS from time series of precipitation (P) minus evapotranspiration(ET) from ERA-Interim re-analysis andobservational river discharge (R) in the Lena, Yenisei and Obriver basins. We find an excellent agreement between the twotime series of TWS. If we account for a negative bias in theaverage annual precipitation during the analyzed period, weeffectively close the terrestrial water budget. From thiscomparison, we attribute both the increase in R and in TWSto an increase in P. In the Lena river basin the TWS increaseis dominated by a large signal in an area of discontinuouspermafrost. We attribute the observed signal to an increasein groundwater storage of 68+/-19 cubic km or to surfacewater recharging the ground water through areas notunderlain by permafrost, while changes in active layerthickness have likely less impact. These TWS changes willhave a significant impact on the terrestrial hydrology of theregion, including increased baseflow and alteration ofseasonal runoff. We also analyze the temporal and spatialcorrelation between TWS and Normalized DifferenceVegetation Index (NDVI) and Net Primary Production (NPP)from MODIS. We show how the correlation changes withinwater rich and water limited areas as well as in function ofdifferent land cover types. We find that vegetationproductivity in the Lena river basin is mainly controlled bytemperature constraints rather than moisture availability,while in the Ob river basin it is mainly controlled by waterlimitation.146Verosub, Kenneth L.Determining River Flows Using Historical AerialPhotography and Satellite ImageryVerosub, Kenneth L. 1 ; Molnia, Bruce 21. Dept Geology, Univ California Davis, Davis, CA, USA2. United States Geological Survey, Reston, VA, USAHistorical aerial photography and satellite imagery arean important data archive that can be used to study changesin the terrestrial water cycle. We have developed a methodthat uses the width of a river as measured in older imageryas a key component in determining the flow in the river atthe time the imagery was collected. The approach requiresknowledge of the topography of the site at which the flow isbeing determined, but such information can be collected inthe present, using ground surveys and/or modern imagery.Once the topographic information is available, we usenumerical integration to determine the hydraulic parametersof the channel. These parameters are then used to calculatethe flow as a function of width. The method has beenvalidated using gauged rivers in the United States for whichboth older imagery and historical flow data are available.Uncertainties in the determination of any given flow are onthe order of 20% or better. The approach provides a way ofobtaining new flow data for sites that have been inaccessibledue to either physical or geopolitical considerations. It canalso be used to extend the record of sites where monitoringhas been discontinued or done only recently. Our approachmakes it possible to study trends in river flows due to globalclimate change over a greater geographic extent and/or alonger time scale than is currently possible. It can alsoprovide better estimates of the impacts of changes in landuse and water resources management on river flows.Vila, Daniel A.Validation of the Hydrological Monthly Productsusing Passive Microwave SensorsVila, Daniel A. 1, 2 ; Hernandez, Cecilia 2 ; Ferraro, Ralph R. 3, 2 ;Semunegus, Hilawe 41. DSA/CPTEC/INPE, Cachoeira Paulista, Brazil2. CICS, ESSIC/UMD, College Park, MD, USA3. NESDIS, NOAA, Camps Spring, MD, USA4. NCDC, NOAA, Ashville, NC, USAGlobal monthly rainfall estimates and otherhydrological products have been produced from 1987 to2009 using measurements from the Defense MeteorologicalSatellite Program (DMSP) series of Special SensorMicrowave Imager (SSM/I), while from 2009 to present, theSpecial Sensor Microwave Imager/Sounder (SSMI/S) is beingused for retrieving several hydrological parameters fromprecipitation and total precipitable water to snow and icecover. The aim of this paper has two purposes: discuss themethodology used to merge both sensors and the impact onthe time series analysis and a second objective is related withthe validation of the current data with in-situ data, like theGlobal Precipitation Climatology Centre (GPCC)monitoring product among others.

Vila, Daniel A.Satellite Rainfall Retrieval Assessment overDifferent Rainfall Regimes and the ‘Chuva’Experiment Preliminary ResultsVila, Daniel A. 1, 2 ; Machado, Luiz A. 1 ; Lima, Wagner 11. DSA/CPTEC/INPE, Cachoeira Paulista, Brazil2. CICS, ESSIC/UMD, College Park, MD, USAThe first part of this paper evaluates different satellitebasedmethodologies for precipitation retrieval over differentrainfall regimes in the Brazilian territory along the year onseasonal basis. The algorithms analyzed in this study are:Hydroestimator, 3B42RT and CMORPH. The evaluation ofthese algorithms was performed by comparing against dailyrain gauges. Preliminary results showed a deficiency inestimating precipitation in northeastern Brazil due to thepresence of low warm-top precipitating clouds (warmclouds). In order to address some of those issues, one of theobjectives of the “Cloud processes of tHe main precipitationsystems in Brazil:A contribUtion to cloud resolVingmodeling and to the GPM (GlobAl PrecipitationMeasurement) “ CHUVA experiment is to evaluate andvalidate the performance of satellite rainfall algorithms inestimating rainfall produced by different rainfall regimesand precipitating systems. Preliminary results of the firstfield campaigns will be presented for discussion.Walker, AnneAirborne and Ground-Based Passive MicrowaveRadiometer Field Campaigns for the Developmentand Validation of new Satellite Derived SnowDatasetsDerksen, Christopher 1 ; Walker, Anne 1 ; Pulliainen, Jouni 2 ;Lemmetyinen, Juha 2 ; Luojus, Kari 21. Environment Canada, Climate Research Division,Toronto, ON, Canada2. Arctic Research Center, Finnish Meteorological Institute,Helsinki, FinlandA series of field campaigns with airborne and groundbasedmicrowave radiometers were conducted acrosssub-Arctic Canada, to address the development andevaluation of new satellite derived snow water equivalent(SWE) datasets. Campaign activities were focused on twoareas: (1) In 2008, airborne and satellite brightnesstemperature (TB) measurements were combined withintensive field observations of snow cover at three sitesacross the Canadian sub-Arctic to develop a new tundraspecificpassive microwave snow water equivalent (SWE)retrieval algorithm specific to high latitude environments.This complements the existing suite of mid-latitude landcover specific algorithms developed and utilized atEnvironment Canada. (2) Plot-scale TB measurements wereacquired in forest, open, and lake environments nearChurchill, Manitoba, Canada with mobile sled-basedmicrowave radiometers during the 2009/10 winter season.These measurements were combined with coincidentphysical snow measurements to evaluate multi-scale forwardTB simulations with the Helsinki University of Technologysnow emission model, a fundamental component of a newnorthern hemisphere SWE dataset recently produced by theEuropean Space Agency GlobSnow initiative(www.globsnow.info), through an assimilation of satellitepassive microwave data and snow depth measurements fromsynoptic weather stations. This presentation will provide anoverview of the measurements made in these campaigns, anda synthesis of snow emission model simulations and SWEretrieval experiments. In general, results indicate thataddressing sub-grid heterogeneity remains a key challenge inthe development of satellite retrieval algorithms becausevariable land cover and associated physical snow propertiesdrive uncertainty in the forward TB simulations and withinthe SWE retrieval schemes. Furthermore, satellite-scalepassive microwave SWE retrievals can provide only a singlevalue for coarse resolution grid cells, which introduces animplicit level of uncertainty for nearly all applications. Thesecampaigns also contributed to preparatory activities for theCold Regions High Resolution Hydrological Observatory(CoReH2O), a dual frequency SAR mission dedicated toobservations of the cryosphere (CoReH20 is one of thecandidates for the European Space Agency’s next satellite inthe series of Earth Explorer Core missions). These proposedspaceborne Ku- and X-band SAR measurements, includingpotential synergistic use with satellite microwaveobservations, will represent considerable improvement inspatial resolution.Walker, AnneSpring thaw detection from satellite active andpassive microwave measurementsWang, Libo 1 ; Walker, Anne 1 ; Derksen, Chris 11. Climate Research Division, Environment Canada,Toronto, ON, CanadaThe timing of seasonal transition from frozen to nonfrozenconditions is coincident with the seasonal switchfrom the landscape being a net source to a net sink foratmospheric carbon. It also affects the length of the growingseason and the surface water and energy balances. Bothsatellite active and passive microwave sensors have beenwidely used to monitor landscape freeze/thaw status. In thisstudy, we investigate the capability of combined enhancedresolution active/passive microwave data from the SeaWindsscatterometer onboard QuikSCAT and the AdvancedMicrowave Scanning Radiometer for the Earth ObservingSystem (AMSR-E) for spring thaw detection. An attempt ismade to differentiate the timing of spring snowmelt onsetand soil thaw, which are not resolved from previous methodsusing the original resolution satellite data. In situobservations of snow depth and soil temperature dataobtained from Boreal Ecosystem Research and MonitoringSites (BERMS) locations in the southern boreal forest ofSaskatchewan and measurements from International PolarYear campaigns in northern Quebec (tundra) were used toassist in the interpretation of the satellite measurements.147

Land surface temperature and snow cover products from theModerate Resolution Imaging Spectroradiometer (MODIS)are used to investigate the sub-grid heterogeneity within theenhanced resolution QuikSCAT/AMSR-E 8.9km grid cells.We expect detailed information about the spring thawprocess, such as the differentiation of soil thaw fromsnowmelt onset, will allow us to show improvedcorrespondence between spring thaw timing and theseasonal switch of the landscape being source/sink foratmospheric carbon.Walker, Anne E.Canadian Advancements in Characterizing HighLatitude Snow Cover Properties Using SatelliteDataWalker, Anne E. 1 ; Derksen, Chris 1 ; Wang, Libo 11. Climate Research Division, Environment Canada,Toronto, ON, CanadaThe Climate Research Division (CRD) of EnvironmentCanada has a long-standing research program focussed onthe development of satellite-based capabilities forcharacterizing the spatial and temporal variability in snowcover across Canada to support analyses of climatevariability and change and contribute to enhancedmodelling (climate, numerical weather prediction,hydrology) capabilities. Scientific understanding of snowcover variability and change in northern regions isparticularly lacking due to a sparse conventional observingnetwork that has a strong coastal bias. This presentation willprovide an overview of recent Canadian advancements thathave been made in characterizing high latitude snow coverproperties using data from current satellites and efforts todetermine the potential for future missions such asCoReH2O (Cold Regions Hydrology High-resolutionObservatory). These include new capabilities generated fromresearch activities carried out during International PolarYear (2007-2009) for snow water equivalent (SWE) retrievalin Arctic tundra landscapes, and the development of a pan-Arctic data set documenting melt onset dates for terrestrialsnow cover, lake ice, land ice, and sea ice surfaces from Kubandscatterometer and passive microwave radiometermeasurements. The application of new satellite snow coverdata sets for documenting changes in Arctic snow cover andimproving the initialization of surface conditions innumerical weather prediction models will be highlighted.This includes application of the suite of land cover specificalgorithms developed at Environment Canada (suitable forregional modeling applications) and a new NorthernHemisphere SWE dataset (suitable for global modelingapplications) recently produced by the European SpaceAgency GlobSnow initiative. GlobSnow SWE retrievals areproduced through an assimilation of satellite passivemicrowave data, forward snow emission model simulations,and snow depth measurements from synoptic weatherstations. Evaluation with independent reference datasetsindicate this approach produces retrievals with notablyimproved accuracy compared to contemporary ‘stand-alone’passive microwave datasets.Walker, Jeffrey P.The Soil Moisture Active Passive Experiment:Towards Active Passive Retrieval and DownsclaingWalker, Jeffrey P. 1 ; Monerris, Alessandra 1 ; Gao, Ying 1 ; Wu,Xiaoling 1 ; Panciera, Rocco 2 ; Tanase, Mihai 2 ; Ryu,Dongryeol 2 ; Gray, Doug 3 ; Yardley, Heath 3 ; Goh, Alvin 3 ;Jackson, Tom 41. Department of Civil Engineering, Monash University,Clayton, VIC, Australia2. Department of Infrastructure Engineering, University ofMelbourne, Parkville, VIC, Australia3. Department of Electrical and Electronic Engineering,University of Adelaide, Adelaide, SA, Australia4. United Stated Department of Agriculture, Beltsville, MD,USANASA’s Soil Moisture Active Passive (SMAP) mission isscheduled for launch in 2014. This soil moisture dedicatedmission will carry a combined L-band radar and radiometersystem with the objective of mapping near surface soilmoisture globally at an unprecedented spatial resolution.The scientific rationale for SMAP is an improved accuracyand spatial resolution of soil moisture estimates through thecombination of high resolution (3 km) but noisy radarderived soil moisture information and the more accurate yetlower resolution (36 km) radiometer derived soil moistureinformation, yielding a 9 km active-passive soil moistureproduct. In order to achieve these objectives, algorithmsneed to be developed and tested using airborne data thatsimulate the radar and radiometer observations that SMAPwill provide. The Soil Moisture Active Passive Experiment(SMAPEx) is a series of three airborne field campaignscontributing to the development and validation of suchalgorithms, providing prototype SMAP observationscollected with a unique active and passive airborne facilityover a heavily monitored study area in south-easternAustralia. This paper outlines the airborne and groundsampling rationale, the progress towards producingsimulated active-passive SMAP data sets for a range of soilmoisture and vegetation conditions, including a single 3-week long dry-down period during the spring growingseason, and the development of 1 km resolution passive onlysoil moisture maps for validation of active-passive retrievaland downscaling studies. Note that the order of authorsdoes not necessarily reflect the order of contributions.Wang, GuangyuSustainability and Landuse Pattern ChangeDetection in the Min River Watershed, ChinaWang, Guangyu 11. Faculty of Forestry, University of British Columbia,Vancouver, BC, CanadaDetecting patterns and change in landuse over time isvery important in determining regional ecosystem well-being148

and landuse sustainability. In this paper, the combination ofGIS mapping methods and remote sensing imageryclassification tool (ERDAS) with landuse qualification tool(FRAGSTATS) and Factor Analysis are used to for detectingregional sustainability and landuse change over time in theMin Watershed, China. Four periods of Landsat imageriesfrom 1986, 1990, 2000 and 2003 have been used andclassified into ten land use cover types- arable land, waterbody, orchard, conifer forest, broadleaf forest, other forest,grassland, transportation land, and unused land. Therelationships between the landscape metric changes, thewatershed development and management practices havebeen examined. Markov’s model has been used to projectfuture landuse changes in the watershed. The result showsthat the Min Watershed has experienced a great change inthe last two decades due to the aggressive economicdevelopment policy and population growth in thewatershed. The increasing intensive land use and overexploration,has lead the recent years’ tragedy in thewatershed. A quick action should be taken to ensure thedevelopment in a right track toward sustainablemanagement. Key words: watershed, land use coverclassification, sustainability, Fragstats quantification, FactorAnalysis, Markov projection, Chinawww.forestry.ubc.caWang, JiaoRemotely Sensed Evapotranspiration Estimation inCentral TexasWang, Jiao 1 ; Currit, Nate 11. Texas State University, San Marcos, TX, USARemotely Sensed Evapotranspiration Estimation inCentral Texas Evapotranspiration(ET) is an essentialcomponent in the hydrologic cycle, which determines energyand mass exchanges between the surface and theatmosphere. Knowledge of spatial and temporal pattern ofET is important for a better understanding of the watercycle, as well as for water management, agriculturalirrigation. Estimations and measurements of ET can bemade at various scales ranging from small scale (e.g. the leaf,plant) to large scale (e.g. field and catchment). Small scaleET utilizes various equipments and theories (e.g. lysimeters,scintillometers, Bowen ratio and eddy covariance). Theseequipments can be used to estimate ET at the plot scale, buthave the limitation of only sampling the local environment.And their accuracy is highly impacted by how representativethey are for the surrounding vegetation and soil moisture.Large scale measurements are needed to monitor ET over aregional or global scale to study its spatial pattern ofdistribution. Remote sensing techniques have been usedwidely in large scale ET estimation due to their capability ofquantifying the spatial distribution of vegetation, surfacetemperature and moisture, which are important componentsin ET estimation. Several models have been developed toestimate ET at a regional level using satellite imagery. Thesemodels can be divided into two kinds: one-source and twosource,depending on whether they distinguish between149evaporation from the soil surface and transpiration from thevegetation. A widely used one is called SEBAL, a one-sourcemodel. This model been evaluated across various areas andhas an accuracy of 85% for daily measurement, 95%seasonally over a range of soil wetness and vegetationconditions. In this paper, the model SEBAL was used toestimate ET from LANDSAT ETM+ imagery in centralTexas. ET estimations from remote sensing data werecompared to the field measurements from three eddy towerslocated in the study site. One eddy tower is located atgrassland, one at woodland, and one at mesquite-juniper.Results show that ET estimations at woodland and mesquitesites are very close to ET measured at eddy towers (within 6%difference), although that at grassland underestimated ET by24%. The reason for this bigger difference can be related tothe footprint of the eddy tower at grassland. In this study,the footprint of eddy tower is assumed to be approximately 1km2 as suggested by literatures. However, the footprint ofthe eddy tower at the grassland may be smaller than 1 km2,which may be smaller than the pixel size of LANDSATETM+ (30m by 30m). Then, the spatial pattern of ET wasstudied by comparing to land cover, soil, surfacetemperature, and vegetation indices maps. Results revealthat the spatial pattern of ET is highly correlated to that ofland cover, surface temperature and vegetation indices. Thereis not much relationship between the soil distribution andthe spatial pattern of ET. The regression between surfacetemperature and ET presents a negative relationship withthe r2 above 0.9. The regression between vegetation indicesand ET shows a positive relationship with the r2 around 0.7.Findings from this paper will be helpful for further analysisof ET drivers and their impacts on the spatial pattern of ET.Wang, Nai-YuDeveloping Winter Precipitation AlgorithmWang, Nai-Yu 1 ; Gopalan, Kaushik 1 ; Ferraro, Ralph 2 ; Turk,Joe 31. ESSIC, University of Maryland, College Park, MD, USA2. NESDIS/STAR, NOAA, College Park, MD, USA3. NASA JPL, Pasadena, CA, USAAs we move from the TRMM to GPM era, moreemphasis will be placed on precipitation in mid- and highlatitudes.In these areas, a large and highly variable portionof the total annual precipitation is snow. During the winterof 2006-2007, NASA GPM Ground Validation programjoined a field campaign designed to measure winterprecipitation for the Canadian Cloudsat/CALIPSOvalidation program (C3VP). GPM’s participation was aimedat improving satellite-based snowfall detection and retrievalalgorithms. Intensive observations of snowfall usingairborne and ground-based instrumentation were conductedcentered on the Centre of Atmospheric ResearchExperiments (CARE) site near Egber, Ontario, Canada(about 80km north of Toronto). In this paper, we willpresent the progress towards developing a winterprecipitation algorithm over land using current satelliteobservations from AMSU/MHS and CloudSat, and C3VPfield campaign data. In addition, we will examine the

microwave retrievals of surface emissivity spectra fromAMSU and AMSR-E in the summer and winter monthsunder clear sky conditions over C3VP site. The cloud-freeatmospheric contribution is calculated from AIRStemperature and humidity profiles, and NWP modelreanalysis from GDAS and ECMWF. The land surfacetemperature from MODIS, GDAS and ECMWF are used forcomparison purposes. The differences in the atmosphericcontribution due to different inputs of temperature andhumidity profiles along with the effect of surfacetemperature are discussed. The relationship between theland surface emissivity, surface temperature and snow waterequivalent in the winter months is also analysed. Thepotential for using microwave emissivity for precipitationretrievals over land is discussed.Wang, ShusenCharacterization of Spatiotemporal Variations inEvapotranspiration Over Canada’s LandmassWang, Shusen 1 ; Yang, Yan 1 ; Rivera, Alfonso 21. Canada Centre for Remote Sensing, Natural ResourcesCanada, Ottawa, ON, Canada2. Geological Survey of Canada, Natural Resources Canada,Quebec, QC, CanadaA 30-year dataset of evapotranspiration (ET) at 1-kmresolution was generated over Canada’s landmass using theland surface model EALCO driven by gridded climate dataof years 1979-2008 and land surface data derived mostlyfrom remote sensing. EALCO is a physically based numericalmodel developed to simulate the ecological and hydrologicalprocesses of terrestrial ecosystems using Earth Observations.ET is simulated in EALCO through solving the coupledradiation, energy, and water balance equations at 30-minutetime step. Plant carbon and nitrogen processes aredynamically coupled with energy and water processes tosimulate the plant physiological control on ET. This longtermhigh resolution ET dataset was used to characterize thespatiotemporal variations of land surface ET in Canada. Ourresults show that ET varied remarkably both in time andspace over Canada’s landmass. The modelled annual ETreaches about 600 mm over several regions in the southernpart of the country including the western Pacific Maritime,southern Montane Cordillera, southern Mixed Wood Plainsand Boreal Shield, and southeastern Atlantic Maritime. Theannual ET is modelled below 100 mm in the northern arcticregions. Annually, ET took large part of the precipitationalong a broad strip stretching from the Prairies in the south,northwestward through Boreal Plains and Taiga Plains, tothe regions of Taiga Cordillera and northwest Arctic. Inparticular, the ratio of ET to precipitation is close to 1.0 inthe central and southern part of the Prairies where the driestplaces in Canada are located. Since irrigation and water bodyevaporation are not included in this study, the actual ETover these areas could well exceed the amount ofprecipitation. Over the rest of the landmass, annual totalprecipitation is significantly higher than ET. The seasonalvariations of ET were dramatic due to the pronouncedseasonal changes in climate and vegetation. The monthly ETin July reached the highest for all of the 15 ecozones inCanada. In the cold season months which last about half ayear, the monthly ET remained below 10 mm for most of theecozones. Negative ET was obtained over the arctic regionduring the winter months, indicating the EALCO model hassimulated a larger amount of condensation thanevapotranspiration during the cold season. In contrast, theseasonal distribution of precipitation was less pronouncedthan ET, with more amount of precipitation occurred in thesecond half of the year. Overall, the modelled average ETover the entire Canadian landmass during the 30 years of1979-2008 was 239 mm year-1, or 44% of its correspondingprecipitation. Comparison with existing studies of ET inCanada was conducted revealing uncertainties in ETestimates by using different approaches of surface waterbudget, atmospheric moisture budget, various modellingincluding remote sensing, atmosphere model forecast andreanalysis. The scarcity of ET measurements for the diverseecosystems in Canada remains a significant challenge forreducing the uncertainties in ET estimates; this gap needs tobe addressed in future studies to improve our capabilities inclimate/weather modelling and water resource management.Wei, HelinThe application of satellite remote-sensing dataproducts for land surface modeling in the NCEPoperational modelsWei, Helin 1 ; Meng, Jesse 1 ; Zheng, Weizhong 1 ; Ek, Mike 11. NOAA/NWS/NCEP/EMC, Camp Springs, MD, USAThe land surface application of remote sensing aregetting more and more advanced. For the NCEP operationalmodels, not only do they provide the high-resolution spatialinformation for land surface characterization, but also moreproducts are assimilated to improve the accuracy of theweather/climate forecasts. In this presentation, twoapplications of satellite remote-sensing data will be shown.The first one is using CPC Merged Analysis of Precipitation(CMAP) in the NCEP Climate Forecast System (CFS)Reanalysis. The second one is the assimilation of the SoilMoisture and Ocean Salinity (SMOS) soil moisture in theNCEP Global Forecast System (GFS).Wilson, JeanRegional scale assessment of SubmarineGroundwater Discharge in Ireland combiningmedium resolution satellite imagery andgeochemical tracing techniquesWilson, Jean 1 ; Rocha, Carlos 11. Geography, Trinity College Dublin, Dublin, IrelandSubmarine Groundwater Discharge (SGD) is receivingconsiderable attention in the literature as a major pathwayfor anthropogenic pollutants travelling from land to sea.While SGD comprises less than 10% of global freshwatersources to oceans, the ecological impact of groundwater may150

e very significant as seepage occurs over large areas andassociated solute concentrations are often several orders ofmagnitude greater than those in receiving surface waters.Recognition that SGD is an important pathway forfreshwater and associated materials to near shore marineenvironments implies the development of tools that willfacilitate regional coastal zone assessments of itsenvironmental impact, including localization, spatial extentand magnitude as well as the provision of geographical andgeomorphological constraints for follow-up studies aimingat precise quantification of pollutant discharges whilekeeping costs at a minimum. Here, a tiered, three-stepapproach is proposed as the most effective and affordablemeans to assess the regional extent of groundwaterdischarge at the coast. This paper sets the foundation for theuse of freely available Landsat Enhanced Thematic Mapper(ETM+) thermal infrared (TIR) imagery as a preliminarygeographical constraint of the approach, culminating insubsequent on-site verification and quantification usingRadon-222 (222Rn) as a natural groundwater tracer. Ourresults show that sea surface temperature values (SST)derived from the Landsat ETM+ TIR waveband can be usedto successfully detect plumes of colder water associated withSGD in close proximity to the shoreline. By combiningthermal information with ancillary on-shore spatial datasetsdescribing bedrock geology including aquifer fault lines, thesecond stage of the approach links potential sites of SGDidentified from temperature anomalies observed at sea togeological features on land acting as possible sources.Finally, on-site verification of groundwater discharge isundertaken via surveys aiming to measure 222Rn as aquantitative tracer of SGD. Practical application of theapproach is illustrated through a case-study of the Republicof Ireland in the context of coastal zone management whereover 30 previously unidentified links between aquifers onland and the sea have been highlighted as part of an ongoingstudy.Wilson, Matthew D.The Surface Water and Ocean Topography SatelliteMission – An Assessment of Swath AltimetryMeasurements of River HydrodynamicsWilson, Matthew D. 1 ; Durand, Michael 2, 3 ; Alsdorf, Douglas 2,3 ; Jung, Hahn Chul 4 ; Andreadis, Konstantinos M. 5 ; Lee,Hyongki 61. Geography Unit, University of the West Indies, StAugustine, Trinidad and Tobago2. Byrd Polar Research Center, Ohio State University,Columbus, OH, USA3. School of Earth Sciences, Ohio State University,Columbus, OH, USA4. Hydrological Sciences Laboratory, NASA Goddard SpaceFlight Center, Greenbelt, MD, USA5. NASA Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA6. Department of Civil and Environmental Engineering,University of Houston, Houston, TX, USAThe Surface Water and Ocean Topography (SWOT)satellite mission, scheduled for launch in 2020 withdevelopment commencing in 2015, will provide a stepchangeimprovement in the measurement of terrestrialsurface water storage and dynamics. In particular, it willprovide the first, routine two-dimensional measurements ofwater surface elevations, which will allow for the estimationof river and floodplain flows via the water surface slope. Inthis paper, we characterize the measurements which may beobtained from SWOT and illustrate how they may be used toderive estimates of river discharge. In particular, we show (i)the spatio-temporal sampling scheme of SWOT, (ii) theerrors which maybe expected in swath altimetrymeasurements of the terrestrial surface water, and (iii) theimpacts such errors may have on estimates of water surfaceslope and river discharge. We illustrate this through a“virtual mission” study for a ~300 km reach of the centralAmazon river, using a hydraulic model to provide watersurface elevations according to the SWOT spatio-temporalsampling scheme (orbit with 78° inclination, 22 day repeatand 140 km swath width) to which errors were added basedon a two-dimension height error spectrum derived from theSWOT design requirements. Water surface elevationmeasurements for the Amazon mainstem as may be observedby SWOT were thereby obtained. Using these measurements,estimates of river slope and discharge were derived andcompared to those which may be obtained without error,and those obtained directly from the hydraulic model. It wasfound that discharge can be reproduced highly accuratelyfrom the water height, without knowledge of the detailedchannel bathymetry using a modified Manning’s equation, iffriction, depth, width and slope are known. Increasing reachlength was found to be an effective method to reducesystematic height error in SWOT measurements.151

Wood, EricInternal validation of a distributed hydrologicalmodel through land surface temperature fromremote sensingCorbari, Chiara 1 ; Ravazzani, Giovanni 1 ; Masseroni, Daniele 1 ;Mancini, Marco 1 ; Wood, Eric 21. Politecnico di Milano, Milano, Italy2. Princeton University, Princeton, NJ, USAThis presentation presents a validation of a distributedenergy-water balance model through the constraints on aninternal model variable, the pixel-scale equilibriumtemperature, using remote sensing data of land surfacetemperature. The pixels span different test scales fromagricultural fields to the river basin. The model algorithmsolves the system of energy and mass balances in term of theequilibrium pixel temperature or representative equilibriumtemperature (RET) that governs the fluxes of energy andmass over the basin domain. This equilibrium surfacetemperature is compared to land surface temperature (LST)as retrieved from operational remote sensing data atdifferent spatial and temporal resolutions. The LST is acritical model state variable and remote sensing LST thatcan be effectively used, in combination with energy and massbalance modeling, to monitor latent and sensible heatfluxes. The fluxes regulated from this equilibriumtemperature are also compared and controlled from thosecomputed from local eddy covariance tower data. Adiscussion on the representativeness of satellite, eddycovariance and energy water balance fluxes is made, showingscale congruence among these. A number of case studieshave been carried out ranging from agricultural districtareas to river basins using data from operational satellitesensors and specific airborne flight. The case studies includea maize field in Landriano (Italy), the agricultural district ofBarrax (Spain) and the Upper Po river basin (Italy). Thepresent approach contributes to the research directionhighlighted 30 years ago from Jim Dooge, who encouragedthe scientific modeling community to analyze the behaviourof the model internal state variable (e.g. soil moisture and itsproxy) in addition to the traditional external fluxes (e.g.discharge) to obtain better understanding of hydrologicprocess and model analysis. We think that the use of LSTand RET concepts from energy water balance modeling is acontribution in this direction and is synergistic to effortsdone in remote sensing microwave regarding soil moisture.evaporation at the earth surface. Soil moisture also has astrong effect on surface energy exchange. Thus soil moisturetrends may have a great impact on climate change over land.Likewise, soil moisture is clearly important for thehydrologic applications such as flood and droughtmonitoring, weather forecast, water management andagricultural plant growth. There has been a range ofspaceborne remote sensing sensors deployed during the lasttwo decades to retrieve near surface (~ 0 - 2 cm) soilmoisture. The retrieval techniques to derive satellite basedsoil moisture include either physically based algorithms(such as radiative transfer equations) or various indirectstatistical algorithms. Multiple efforts have been devoted inthe community to retrieve the global near surface soilmoisture content from the Advanced Microwave ScanningRadiometer (AMSR-E) 10.7 GHz measurements using sometype of Radiative Transfer Models (RTM). We find that amajor challenge for using a physically based RTM to retrievesurface soil moisture is to determine the suitable values ofRTM parameters such as the surface soil and vegetationproperties, because the default values of these parametersderived from standard approaches, e.g., soil texture or landcover lookup table, often do not reflect the reality and resultin wrong or off-physical-limit soil moisture retrievals. In thisstudy, we calibrate three major static surface parameters, thefraction of vegetation coverage, roughness height and sandfraction, in the Land Surface Microwave Emission Model(LSMEM), such that the surface emissivity predictions fromthe model climatologically match with the AMSR-Emeasurements. The calibration produces robust parameters,i.e., the parameter values remain stable with longer trainingperiods. Additionally, to improve the vegetation thicknessparameter, which is dynamic in space and time and difficultto calibrate, we implement a new scheme developed atUniversity of Montana to calculate the vegetation opticaldepth. The new calibration technique along with theupdated parameterizations in LSMEM produces a reliablesoil moisture estimate from AMSR-E for the period of 2002to 2011 with higher accuracy. The above calibrationtechnique will be applied to other potential past (e.g.Tropical Rainfall Measuring Mission Microwave Imager(TMI); Scanning Multi-channel Microwave Radiometer(SMMR)) and current (e.g. Soil Moisture and Ocean Salinity(SMOS)) sensors to create a consistent global soil moistureclimatic data record.Wood, EricCreating Global Soil Moisture Data Record FromAMSR-E Through Calibration of a RadiativeTransfer ModelPan, Ming 1 ; Sahoo, Alok 1 ; Wood, Eric 11. Dept of CEE, Princeton University, Princeton, NJ, USASoil moisture is a critical element for both global waterand energy budgets. Soil moisture controls theredistribution of rainfall into infiltration, surface runoff and152

Wood, Eric F.Challenges in Developing Long-term Climate DataRecords for the Terrestrial Water and Energy CyclesINVITEDWood, Eric F. 1 ; Pan, Ming 1 ; Sahoo, Alok K. 1 ; Troy, Tara J. 3 ;Vinukollu, Raghuveer K. 2 ; Sheffield, Justin 11. Dept Civil & Environmental Engineering, PrincetonUniversity, Princeton, NJ, USA2. Swiss Re, Armonk, NY, USA3. Columbia Univsersity, New York, NY, USAComprehensive documentation of the terrestrial watercycle at the global scale and its evolution over time isfundamental to understanding Earth’s climate system andassessing the impacts due to climate change. Suchdocumentation is also needed to characterize the memories,pathways and feedbacks between key water, energy andbiogeochemical cycles. With such enhanced understanding,there is the potential for research programs to resolveoverarching scientific goals to document the energy andwater cycles. GEWEX’s long-term scientific goal is to obtaina quantitative description of weather-scale variations in theglobal energy and water cycles over a period of at least 20years, which will provide the needed scientific basis forunderstanding climate variability and change. Such longtermdata sets have been referred to as Earth System DataRecords (ESDRs) by NASA’s MEaSUREs program, ClimateData Records (CDRs) by NOAA’s National Climatic DataCenter and the European Organization for the Exploitationof Meteorological Satellites (EUMETSAT). In developingglobal-scale climate data records, satellite-based observationsoffer global consistency that can fill spatial-temporal gaps inground-based data collection. Observations from satellitemissions over the last two decades are already providingimportant observations that are being used to developCDRs. In this presentation the underlying challenges will bediscussed in using remote sensing based variables fordeveloping long-term CDRs for the terrestrial water andenergy budget variables. These challenges include temporalconsistency among sensors and algorithms on differentsatellites, uncertainty in retrieval algorithms, and lack ofbudget closure when using the independently estimatedterms. Recent results show that using multiple remotesensing estimates, merged with in-situ and model estimatesand applying budget closure constraints can lead toconsistent long-term CDRs. These CDRs will be used toassess variability and trends in regional and global water andenergy budgets.Worden, JohnConstraints on High Latitude Moisture Fluxes andContinental Recycling Using Satellite and AircraftMeasurements of Water Vapor IsotopesWorden, John 1 ; Lee, Jung-Eun 1 ; Cherry, Jessie 2 ; Risi, Camille 4 ;Frankenberg, Christian 1 ; Welker, Jeff 2 ; Cable, Jessie 2 ; Noone,David 31. JPL / California Institute of Techonology, Pasadena, CA,USA2. University of Alaska Fairbanks, Fairbanks, AK, USA3. University of Colorado, Boulder, CO, USA4. Le Laboratoire de Météorologie Dynamique, Paris, FranceChanges in the water cycle at high latitudes couldsubstantially change the global energy balance due to severalpositive and negative feedbacks. For example, the decrease inthe arctic ice cap can have a positive feedback resulting fromthe decreased albedo and increased water vapor in theatmosphere. The change in cloud cover can be either apositive or negative feedback. If the frequency of snowfallincreases as a result of increased moisture, it would be anegative feedback because fresh snow has higher albedo thanold snow or bare ground. Characterizing the distribution ofthe moisture sources, rainfall, continental recycling and theprocesses controlling cloud distributions are then critical forunderstanding how changes in the polar sea ice and snowdistributions will affect future climate. Measurements ofwater isotopes can place constraints on the distribution ofthese processes because local and transported water vaporhave different isotope signals . In this poster we use newmeasurements of water vapor isotopes from the Aura TESand JAXA GOSAT satellites, in situ measurements fromground and aircraft, and the LMDz model to examine thedistribution of moisture sources at high latitudes and toestimate the amount of continental recycling.Xaver, AngelikaRecent progress on the International Soil MoistureNetworkXaver, Angelika 1 ; Gruber, Alexander 1 ; Hegyiova, Alena 1 ;Dorigo, Wouter A. 1 ; Drusch, Matthias 21. Institute of Photogrammetry & Remote Sensing, ViennaUniversity of Technology, Vienna, Austria2. ESTEC, European Space Agency, Noordwijk, NetherlandsFor the calibration and validation of satellite- and landsurface model based soil moisture estimates in situ soilmoisture measurements are indispensable. Although acouple of meteorological networks measuring soil moistureexist, on a global and long-term scale, ground-basedobservations are few. In addition, measurements fromdifferent networks are performed in quite different ways,resulting in significant disparities, e.g., with respect to soilmoisture units, measurement depths, and sampling rates.This has been the reason for initiating the International SoilMoisture Network (ISMN;http://www.ipf.tuwien.ac.at/insitu/), a centralized data153

hosting facility for in situ soil moisture observations.Available in situ soil moisture measurements from networksover the whole globe are collected, harmonized and stored inthe data base after an advanced flagging scheme is appliedto indicate the quality of the measurements. This databecomes accessible for users through a web interface anddownloaded files are provided in various file formats inaccordance with international data and metadata standards.Currently, data from 25 networks in total covering morethan 700 stations in Europe, North America, Australia, Asiaand Africa is hosted by the ISMN, including historical andoperational datasets with near-real time availablemeasurements. Apart from soil moisture measurements indifferent depths, also meteorological observations, e.g. soiltemperature, air temperature and precipitation, andimportant metadata are stored in the database. As the ISMNis growing continuously a fully automated process chainincluding harmonization and quality control for thecollected data has been developed. Incoming data isautomatically converted into volumetric soil moisture unitsand harmonized in terms of temporal scale. The quality of insitu soil moisture measurements is crucial for the validationof satellite- and model-based soil moisture retrievals.Therefore quality flags are added to each measurement aftera check for plausibility and geophysical limits. Recently,novel quality indicators were defined to detect for examplespurious spikes and jumps in the measurement time series.In addition, new methods for the characterization of thequality of single stations and networks were introduced.With the improved quality control system and continuouslygrowing data content the ISMN will become an increasinglyimportant source for evaluating satellite-based soil moistureproducts and land surface models. The presentation will givea general overview of the ISMN and its recent updates, anddiscuss the methods and potential impact of the new qualitycharacterization system.http://www.ipf.tuwien.ac.at/insitu/Figure. Overview of the locations of soil moisture stations indicatedby pins.Xi, BaikeAN EVALUATION AND INTERCOMPARISON OFCLOUD FRACTION AND RADIATIVE FLUXES INRECENT ATMOSPHERIC REANALYSES OVERARCTIC CYCLE BY USING SATELLITEOBSERVATIONSXi, Baike 1 ; Dong, Xiquan 1 ; Zib, Behn 11. University of North Dakota, Grand Forks, ND, USAWith continual advancements in data assimilationsystems, new observing systems, and improvements in modelparameterizations, several new atmospheric reanalysisdatasets have recently become available. This study is aimedin providing insight into the advantages and disadvantagesof several recently available and widely used atmosphericreanalysis datasets over the Arctic with respect to cloudfraction and TOA radiative fluxes. Reanalyzed cloudfractions (CFs) and TOA radiative fluxes in several of theselatest reanalyses are evaluated and compared to CERES-CRSsatellite-derived radiation products over the entire Arctic.The five reanalyses being evaluated in this study are (i)NASA’s Modern-Era Retrospective analysis for Research andApplications (MERRA), (ii) NCEP’s Climate Forecast SystemReanalysis (CFSR), (iii) NOAA’s Twentieth CenturyReanalysis Project (20CR), (iv) ECMWF’s Reanalysis Interim(ERA-I), and (v) NCEP-DOE’s Reanalysis II (R2). Thesimulated monthly biases in TOA radiation fluxes wereexamined over the entire Arctic region [70o-90o N] ascompared with CERES-CRS radiation products. In the TOAevaluation, MERRA had the lowest annual mean biases inboth reflected SW and outgoing LW fluxes at TOA over theentire Arctic region (+1.0 Wm-2 and +0.2 Wm-2,respectively). However, from a spatial distribution analysis ofthe biases it is frequently seen where large positive biases andlarge negative biases canceled out resulting in small netbiases across the region. Therefore, absolute biases weredetermined for each season and CFSR was shown to have thelowest mean absolute bias for both TOA SW and LWupwelling fluxes. R2 contained the largest positive bias inTOA SWup flux of +10.3 Wm-2 for the annual average withsummertime biases as large as +26 Wm-2. On the otherhand, 20CR was the only reanalysis to have an annual meannegative bias (-6.0 Wm-2) in TOA SWup flux over the Arcticwith biases as large as -14.3 Wm-2 during springtime. Thedifferences between satellite and reanalyses TOA LWupfluxes were much less than the SWup fluxes ranging from -1.2 Wm-2 (20CR) to +1.8 Wm-2 (ERA-I) on the annualaverage. Lastly, Arctic-wide CFs were examined in each of thereanalyses along with CERES-MODIS-derived cloudamounts. It was determined that the reanalyses have adifficult time representing the observed seasonal variation ofclouds over the Arctic, especially during the winter seasons.These errors/biases in CFs in turn have significantimplications on TOA upwelling radiation fluxes.154

Xie, PingpingGauge - Satellite Merged Analyses of LandPrecipitation: A Prototype Algorithm INVITEDXie, Pingping 1 ; Xiong, An-Yuan 21. NOAA/NCEP, Camp Springs, MD, USA2. CMA National Meteorological Information Center,Beijing, ChinaA prototype algorithm has been developed to createhigh-resolution precipitation analyses over land by merginggauge-based analysis and CMORPH satellite estimates. Atwo-step strategy is adopted to remove the bias inherent inthe CMORPH satellite precipitation estimates and tocombine the bias-corrected satellite estimates with the gaugeanalysis, respectively. First, bias correction is performed forthe CMORPH estimates by matching the cumulatedprobability density function (PDF) of the satellite data withthat of the gauge analysis using co-located data pairs over aspatial domain of 5olat/lon centering at the target grid boxand over a time period of 30-days ending at the target date.The spatial domain is expanded, wherever necessary overgauge sparse regions, to ensure the collection of sufficientnumber of gauge – satellite data pairs. The bias-correctedCMORPH precipitation estimates are then combined withthe gauge analysis through the optimal interpolation (OI)technique, in which the bias-corrected CMORPH is used asthe first guess while the gauge data is used as theobservations to modify the first guess over regions withstation coverage. Error statistics are computed for the inputgauge and satellite data to maximize the performance of thehigh-resolution merged analysis of daily precipitation. Crossvalidationtests and comparisons against independent gaugeobservations demonstrate feasibility and effectiveness of theconceptual algorithm in constructing merged precipitationanalysis with substantially removed bias and significantlyimproved pattern agreements compared to the input gaugeand satellite data. Details about the implementation strategyand global applications will be reported at the conference.Xu, BinHourly Gauge-satellite Merged PrecipitationAnalysis over ChinaXu, Bin 1 ; Yoo, Soo-Hyun 2 ; Xie, Pingping 2 ; Xiong, An-Yuan 11. CMA National Meteorological Information Centre,Beijing, China2. NOAA Climate Prediction Center, Washington, DC, USAAs part of the collaboration between ChinaMeteorological Administration (CMA) NationalMeteorological Information Centre (NMIC) and NOAAClimate Prediction Center (CPC), a new system is beingdeveloped to construct hourly precipitation analysis on a0.25olat/lon grid over China by merging informationderived from gauge observations and CMORPH satelliteprecipitation estimates. Foundation to the development ofthe gauge-satellite merging algorithm is the definition of thesystematic and random error inherent in the CMORPHsatellite precipitation estimates. In this study, we quantify155the CMORPH error structures through comparisons againsta gauge-based analysis of hourly precipitation derived fromstation reports from a dense network over China, andcombine the gauge analysis with the bias-correctedCMORPH through the optimal interpolation (OI) techniqueusing the error statistics defined in this study. First,systematic error (bias) of the CMORPH satellite estimatesare examined with co-located hourly gauge precipitationanalysis over 0.25olat/lon grid boxes with at least onereporting station. The CMORPH exhibits biases of regionalvariations showing over-estimates over eastern China, andseasonal changes with over-/under-estimates duringwarm/cold seasons. The CMORPH bias presents rangedependency.In general, the CMORPH tends toover-/under-estimate weak / strong rainfall. The bias, whenexpressed in the form of ratio between the gaugeobservations and the CMORPH satellite estimates, increaseswith the rainfall intensity but tends to saturate at a certainlevel for high rainfall. Based on the above results, a prototypealgorithm is developed to remove the CMORPH biasthrough matching the PDF of original CMORPH estimatesagainst that of the gauge analysis using data pairs co-locatedover grid boxes with at least one reporting gauge over a 30-day period ending at the target date. The spatial domain forcollecting the co-located data pairs is expanded so that atleast 5000 pairs of data are available to ensure statisticalavailability. The bias-corrected CMORPH is then comparedagainst the gauge data to quantify the remaining randomerror. The results showed that the random error in the biascorrectedCMORPH is proportional to the smoothness ofthe target precipitation fields, expressed as the standarddeviation of the CMORPH fields, and to the size of thespatial domain over which the data pairs to construct thePDF functions are collected. An empirical equation is thendefined to compute the random error in the bias-correctedCMORPH from the CMORPH spatial standard deviationand the size of the data collection domain. An algorithm isbeing developed to combine the gauge analysis with the biascorrectedCMORPH through the optimal interpolation (OI)technique using the error statistics defined in this study. Inthis process, the bias-corrected CMORPH will be used as thefirst guess, while the gauge data will be utilized asobservations to modify the first guess over regions withgauge network coverage. Detailed results will be reported atthe conference.

Yamazaki, DaiAdjustment of a spaceborne DEM for use infloodplain hydrodynamic modellingYamazaki, Dai 1, 4 ; Baugh, Calum 2 ; Bates, Paul D. 2 ; Kanae,Shinjiro 3 ; Alsdorf, Douglas E. 4 ; Oki, Taikan 11. Institute of Industrial Science, The University of Tokyo,Tokyo, Japan2. School of Geographical Sciences, University of Bristol,Bristol, United Kingdom3. Graduate School of Information Science andEngineering, Tokyo Institute of Technology, Tokyo, Japan4. Byrd Polar Research Center, the Ohio State University,Columbus, OH, USAPrecise Digital Elevation Models (DEMs) are requiredfor the accurate modelling of floodplain hydrodynamics.The accuracy of currently available spaceborne DEMshowever is hindered by a variety of errors which reduce theflow connectivity between river channels and thesurrounding floodplains. Here we introduce a newalgorithm for adjusting a spaceborne DEM which utilizesthe information from a prescribed drainage networksdataset. The algorithm is designed to remove all the pits inthe spaceborne DEM caused by vegetation canopies, subpixelsized structures, and random radar speckles whileminimizing the amount of modification required forremoving the pits. The proposed algorithm was applied tothe SRTM3 DEM with reference to the drainage networkinformation in the HydroSHEDS flow direction map. Withconsideration of the systematic errors in the SRMT3 DEM,small channels connecting floodplains were successfullyimplemented into the adjusted DEM. The accuracy of theadjusted DEM was validated using hydrodynamicsimulations with the LISFLOOD-FP model in a middlereach of the Amazon River. The simulated water surfaceelevations and flooded areas with the adjusted DEM showsbetter agreement to observation data when compared to theresults from the original SRTM3 DEM. The flowconnectivity ensured by the DEM adjustment algorithm isfound to be essential for representing realistic waterexchanges between river channels and floodplains inhydrodynamics modeling.production system with integrated processing chain fromdata pre-processing, ET calculation and analysis, autocalibrationand database management(Figure 2). ETWatchhas been tested by a qualified software test agency on thesoftware product of the ET monitoring system. ETWatch isan operational platform serves for the trained engineersrather than by developers or specialized Remote Sensing/ETspecialists. This is essential to sustainability of waterplanning and management. ETWatch can be used acrossdifferent landscapes on calculating continuous ET data atthe scale from 1km down to 30m. ETWatch has beencustomized for and deployed at the Haihe BasinCommission of Ministry of Water Resources and BeijingMunicipal of Water Affair. ETWatch has been calibrated andvalidated intensively and independently in Northen Chinarivers that face serious over-exploitation of groundwater,including Hai Basin, Heihe River, Turpan Basin, etc. Fieldcampaigns of meterological data, solar radiance, soilmoisture depletion, lysimeter measurements, eddycovariance measurements, LAS, and water balancecalculations at diverse landscapes were used for calibrationand validation. The independent verification results fromthird parties on ET data produced by ETWatch are alsopresented.Figure 1: Customized ETWatch User InterfaceYan, NanaAn Operational Regional ET Monitoring System(ETWatch) and Its ValidationWu, Bingfang 1 ; Yan, Nana 1 ; Zhu, Weiwei 1 ; Xiong, Jun 11. Institute of remote sensing applications, ChineseAcademy of Sciences, Beijing, ChinaCompared to water balance method or in situmeasurements, an operational integrated monitoringmethod of regional surface evapotranspiration (ET) fromremote sensing data is essential and the only approach toobtain regional ET dataset. ETWatch has originally beendeveloped as an integrated operational software system forregional ET monitoring, on request of the Hai Basincommission(Figure 1). ETWatch is an applicable ET156Figure 2: ETWatch Processing Flowchart

Yebra, MartaRemote sensing canopy conductance for combinedwater and carbon studiesYebra, Marta 1 ; van Dijk, Albert I. 1 ; Leuning, Ray 2 ; Huete,Alfredo 31. Land and Water, CSIRO, Canberra, ACT, Australia2. Marine and Atmospheric Research, CSIRO, Canberra,ACT, Australia3. University Technology of Sydney, Sydney, NSW, AustraliaAccumulation and storage of carbon in trees is onemethod of carbon sequestration which may help offsetincreasing atmospheric CO2 concentrations. However,changing land use can affect water resources availability,especially in a dry continent like Australia. Compared withpasture or grasslands, a mature forest uses more water perunit land area. The biological nexus between carbon andwater occurs through the stomatal pores in plant leaves.Stomata open to allow CO2 into the plant forphotosynthesis but at the same time, water vapour escapesto the atmosphere. In this study we use remotely sensed data(RS) to assess the trade-off between carbon sequestrationand water yields for alternative land use options in Australia,focusing on the role of canopy conductance (Gc). Thisproperty is highly variable in space and dynamic in time. Themethod is developed using measurements at flux towers.Data from several FLUXNET sites are used to invert thePenman-Monteith equation and obtain surfaceconductance, from which data are selected that are assumedto represent Gc. Gc is then regressed against a number ofdifferent MODIS vegetation indices and products. Leaveone-outvalidation is used to evaluate the alternativeregression models and select the one with the bestperformance across all sites. The residual unexplainedvariation in Gc is investigated through comparison to landcover type and regression to meteorological variables such asavailable energy and VPD.Yong, BinEvolving TRMM-based Multi-satellite Real-TimePrecipitation Estimation Methods: Their Impactson Hydrologic Prediction Using the VariableInfiltration Capacity Model in a High LatitudeBasinYong, Bin 1 ; Hong, Yang 2 ; Ren, Liliang 1 ; Gourley, Jonathan J. 3 ;Huffman, George J. 4 ; Xu, Hanwei 11. State Key Lab of Hydrology, Hohai University, Nanjing,China2. School of Civil Engineering and Environmental Sciences,University of Oklahoma, Norman, OK, USA3. National Severe Storm Laboratory, NOAA, Norman, OK,USA4. Laboratory for Atmospheres, NASA, Greenbelt, MD, USAThe real-time availability of satellite-derivedprecipitation estimates provides hydrologists an opportunityto improve current hydrologic prediction capability andmanagement of local water resources for medium to largeriver basins. Due to the availability of new satellite data andupgrades to the precipitation algorithms, the TropicalRainfall Measuring Mission (TRMM) MultisatellitePrecipitation Analysis real-time estimates (TMPA-RT) havebeen undergoing several important revisions over the pastten years. In this study, the changes of the relative accuracyand hydrologic potential of TMPA-RT estimates over itsthree major evolving periods were evaluated and intercomparedat daily, monthly and seasonal scales in thehigh-latitude Laohahe basin in China. Assessment resultsshow that the performance of TMPA-RT in terms ofprecipitation estimation and streamflow simulation wassignificantly improved after 3 February 2005 from theTMPA-RT inception (i.e. Period I). Overestimation duringwinter months was noteworthy and consistent, which issuggested to be a consequence from interference of snowcover to the passive microwave retrievals. Rainfall estimatedby the new version 6 of TMPA-RT starting from 1 October2008 (i.e. Period III) to present has higher correlations withindependent rain gauge observations and tends to performbetter in detecting rain compared to the prior periods,although it suffers larger mean error and relative bias. Aftera simple bias correction, this latest dataset of TMPA-RTexhibited the best capability in capturing hydrologicresponse among the three tested periods. In summary, thisstudy demonstrated that there is an increasing potential inthe use of TMPA-RT in hydrologic streamflow simulationsover its three algorithm upgrade periods, but still withsignificant challenges during the winter snowing events. Weexpect the results reported here will offer hydrologic users ofTMPA-RT data a better understanding of their errorcharacteristics and potential utilization for variousoperational hydrological applications in high-latitudebasins. Looking into the future, the evaluation frameworkdeveloped herein can apply to new satellite precipitationproducts such as the forthcoming 3B42RT Version 7datasets and future GPM-era products, especially for basinswithin the high-latitude bands.157

Yoon, YeosangAn ensemble-based approach for estimating riverbathymetry from SWOT measurementsYoon, Yeosang 1, 5 ; Durand, Michael 2, 5 ; Merry, Carolyn 1 ;Clark, Elizabeth 3 ; Andreadis, Konstantinos 4 ; Alsdorf,Douglas 2, 51. Department of Civil and Environmental Engineering andGeodetic Science, The Ohio State University, Columbus,OH, USA2. School of Earth Sciences, The Ohio State University,Columbus, OH, USA3. Department of Civil and Environmental Engineering,University of Washington, Seattle, WA, USA4. Jet Propulsion Laboratory, California Institute ofTechnology, Pasadena, CA, USA5. Byrd Polar Research Center, The Ohio State University,Columbus, OH, USARiver discharge is an important element in many aspectsof water resources management; however, global gaugingnetworks are sparse and even have been in decline. Over thepast decade, researchers have been trying to better estimateriver discharge using remote sensing techniques tocomplement the existing in situ gage networks. Theupcoming Surface Water and Ocean Topography (SWOT)mission will directly provide simultaneous spatial mappingof inundation area and inland water surface elevation data(i.e., river, lakes, wetlands, and reservoirs), both temporallyand spatially, with the Ka-band Radar Interferometer; thismission is planned to launch in 2019. With theseobservations, the SWOT mission will provide informationfor characterizing river discharge at global scales. A key toestimating river discharge via Manning’s equation orhydrodynamic model is river bathymetry. Because SWOTwill measure water surface elevation (WSE), not the truedepth to the river bottom, the cross-sectional flow area willnot be fully measured. Note that the SWOT sensor candirectly measure the changes in water depth and crosssectionalarea above the lowest measured WSE, but absoluteriver depths will not be observed. Here, we focus onestimating river bathymetry for retrieving river dischargefrom the SWOT using a data assimilation algorithm coupledwith a hydrodynamic model. In this study, we assimilatedsynthetic SWOT observations into the LISFLOOD-FPhydrodynamic model using a local ensemble batchsmoother, simultaneously estimating river bathymetry andflow depth. First-guess estimates of bathymetry were derivedassuming a uniform spatial depth with spatially correlateddownstream variability. SWOT observations were obtainedby sampling a “true” LISFLOOD-FP simulation based on theSWOT instrument design; the “true” discharge boundarycondition was derived from USGS gages. The first-guessdischarge boundary conditions were produced by theVariable Infiltration Capacity model, with dischargeuncertainty controlled via precipitation uncertainty. Havingrealistically described uncertainties in discharge andbathymetry, we evaluate the ability of a data assimilation158algorithm to recover bathymetry and discharge using SWOTobservations.You, YaleiThe Proportionality between Surface Rainfall andVertically Integrated Water and Its Implications toSatellite Rainfall RetrievalYou, Yalei 1 ; Liu, Guosheng 11. Florida State University, Tallahassee, FL, USAThe correlation between the surface rainrate and thewater path is investigated by using the Tropical RainfallMeasuring Mission (TRMM) Precipitation Radar (PR) data.The results showed that the proportionality between thesurface rainrate and the water path varies both seasonallyand spatially. Specifically, over land the proportionally of icewater path and surface rain changes little in the tropicalregions, such as central Africa. In contrast, it changesdramatically over desert regions and monsoon-affected areas.In terms of spatial variation, it is found that theproportionality between ice water path and surface rainratehas much larger changes around Sahara desert areas. Inaddition, the proportionality between the water path andsurface rainrate has also been investigated. It seems that thelargest difference is between Sahara desert regions and otherplaces. It is likely that the lower part of the rainfall profiledominate the overall total water path. Over ocean, theproportionality between ice (liquid) water path and surfacerainrate also demonstrates similar seasonally and spatiallyvariations. These results indicate that localized methodsmaybe employed under different conditions due to the sameamount of water path corresponding to quite differentsurface rainrate.Yu, XuanUsing NLDAS-2 for Initializing IntegratedWatershed Models: Model Spin-up for theAirMOSS CampaignYu, Xuan 1 ; Duffy, Christopher 1 ; Bhatt, Gopal 1 ; Crow, Wade 2 ;Shi, Yuning 31. Civil & Environmental Engineering, Pennsylvania StateUniversity, University Park, PA, USA2. Remote Sensing Lab, United States Department ofAgriculture, Beltsville, MD, USA3. Meteorology, Pennsylvania State University, UniversityPark, PA, USAAirborne Microwave Observatory of Subcanopy andSubsurface (AirMOSS) investigation has been developed forhigh-resolution in time and space root-zone soil moistureand carbon estimation. AirMOSS will build an ultra-highfrequency (UHF) synthetic aperture radar (SAR) that has thecapability to penetrate through substantial vegetationcanopies and subsurface and retrieve information to thedepths as deep as 1.2m depending on the soil moisturecontent. To meet the high temporal and spatial resolution ofAirMOSS data Penn State Integrated Hydrologic Model(PIHM) – a fully-coupled physics-based hydrologic model is

used. PIHM has ability to simulate terrestrial hydrologicalprocess at watershed and river basin scales. The finitevolume based discretization and SUNDIALS basednumerical solution strategy of PIHM enables to capture thehigh frequency shallow groundwater, soil moisture andstream-reach interactions in the context of tightly-coupledintegrated modeling framework. NLDAS-2 land-surfaceforcing data set was used as climate input to the hydrologicmodel. In this application, vertical soil moistureredistribution and land-surface energy modules aredeveloped for assimilation of AirMOSS soil moistureobservation data and providing further information forsimulation of carbon dynamics. The first applications werethe Tonzi Site (38°2554N 120°5758W), in the UpperCosumnes River Watershed, and the Harvard Forest(42°3148N 72°1124W), including the East Branch FeverBrook, Headwaters East Branch Swift River and Mill BrookMillers River. A 59.4-km^2 catchment around Tonzi site andthree catchments(184-km^2) around Harvard Forest wereselected for soil moisture and energy transport simulation.Various processes representation specific to alpine regionhas been improved in PIHM to better simulate the datacollected through AirMOSS. Dynamic snow accumulationand melt are also implemented for cold season processes.The state-of-the–art remote sensing technology is meant tosupport calibration and validation of hydrologic modelingand future improvements in the carbon dynamics coupledwith the terrestrial water cycle.http://www.pihm.psu.edu/harvard_forest.htmlhttp://www.pihm.psu.edu/willow_creek.htmlZeng, YijianImpact of Land Model Physics on One-dimensionalSoil Moisture and Temperature Profile RetrievalZeng, Yijian 1, 2 ; Su, Bob 1 ; Wan, Li 2 ; Wen, Jun 31. Water Resources, ITC Faculty Univ of Twente, Enschede,Netherlands2. School of Water Resources and Environment, ChinaUniversity of Geosciences (Beijing), Beijing, China3. Key Laboratory of Land Surface Process and ClimateChange in Cold and Arid Region, Cold and Arid RegionsEnvironmental and Engineering Research Institute,Chinese Academy of Sciences, Lanzhou, ChinaSoil air flow is crucial in determining surfaceevaporation, which subsequently affects the atmosphericmodeling. However, most land surface models (LSMs)usually ignore the airflow and only employ the diffusionbasedsoil water and heat transport model. Consideringairflow needs to formulate a fully coupled soil water-vaporair-heattransport model. In order to assess the necessity ofincluding this highly nonlinear coupled model in the LSMs,the paper introduces three models with gradually-decreasedcomplexity to check how different model complexities canaffect the model performance in retrieving soil moisture andsoil temperature profiles. The results show that the mostcomplex model (i.e. coupled soil water-vapor-air-heattransport model) can perform better than other models inretrieving soil moisture when only soil moisture observationis available. For retrieving soil temperature, the mediumcomplex model (i.e. coupled soil water-vapor-heat transportmodel) stands out from the three models. The simplestmodel (i.e. diffusion-based soil water and heat transportmodel) can produce assimilation estimates of soiltemperature as satisfactory as the most complex model does;and, its assimilation estimate of soil moisture closely followsits simulation (e.g. open loop), which is not a properrepresentative of the observed truth. Nevertheless, the RMSEbetween its soil moisture assimilation estimates and theobservation is the lowest among the three models, whichmay be responsible for the popular use of the diffusionbasedmodel in the LSMs. It is suggested that there is anoptimal combination of the observation data and the modelphysics for retrieving soil states. Keywords: ModelComplexity; Data Assimilation; Land Surface Models;Ensemble Kalman FilterFigure1. The averaged assimilation estimates of soil temperature andsoil moisture over all observation intervals with surface moistureobservationsZhuang, QianlaiModeling the Effects of Land Use Change Due toBiofuel Development on Water Dynamics in theUnited StatesZhuang, Qianlai 1 ; Qin, Zhangcai 1 ; Chen, Min 11. Earth & Atmospheric Sciences, Purdue University, WestLafayette, IN, USAIn the United States, agriculture has been under a greatpressure to have high productivity and the arable land couldbe further exploited to intensify its agriculture and biofuelcrops due to the rising demand of agricultural-based andcellulosic biofuels. The consequence of carbon sink or sourcestrengths and the supply deficit of fresh water associatedwith the land use change and growing biofuel crops is agreat concern. Existing field studies show that the water useefficiency of the biofuel crops including switchgrass andMiscanthus differ from food crops. How theevapotranspiration, soil moisture and water supply of foodcrops and biofuel crops will change under changing climateand land use is still not well studied. Here we present ourresearch results for the conterminous U.S. evaluated with amechanistic ecosystem model that was incorporated with anecosystem-level water use efficiency algorithm. The resultsare based on hypothetical assumptions with various land usescenarios of growing biofuel crops versus food crops withrespect to growing areas and irrigation areas. The study will159

provide a good understanding to (1) the amount of waterbeing transpired to the atmosphere due to different land usescenarios; (2) the soil water level and potential freshwater toaquatic system and water reservoirs from the arable landecosystems; and (3) the viability of growing biofuel crops inthe context of water supply and demand and potentialfeedbacks to the climate system.http://www.purdue.edu/eas/ebdlZreda, MarekMeasuring area-average soil moisture using mobilecosmic-ray detectorZreda, Marek 1 ; Zweck, Chris 1 ; Franz, Trenton 1 ; Rosolem,Rafael 1 ; Chrisman, Bobby 11. Dept Hydrol & Water Res, University of Arizona, Tucson,AZ, USASoil moisture at a horizontal scale of ca. 600 m averagedover depths of 15-70 cm can be inferred from measurementsof cosmic-ray fast neutrons above the ground surface. Theseneutrons are sensitive to water content changes, largelyinsensitive to soil chemistry, and their intensity is inverselycorrelated with hydrogen content of the soil. The stationarycosmic-ray soil moisture probe is being implemented in theCOsmic-ray Soil Moisture Observing System (COSMOS) toprovide continental-scale soil moisture data in real time. Amobile COSMOS probe, or the COSMOS rover, provides themeans to measure soil moisture averaged over swaths thathave the width equal to the footprint (600 m).Measurements along driving or flying routes enablemapping of soil moisture over large areas. The COSMOSrover is a larger version of the stationary COSMOS probe,and it has a GPS receiver to log the position. Neutronintensity is integrated over one minute and written to an SDcard along with pressure and position data. The drivingvelocity is usually slower than normal driving velocity, andranges from less than 30 km/h on bad roads to over 100km/h on good highways. For this range of velocities, oneminute of driving corresponds to the swath length ofbetween less than 500 m and more than 1700 m; thus, oneminute of driving gives average neutron intensity over aswath that is 600 m wide and 500-1700 m long. Neutrondata are converted to soil moisture using a calibrationfunction that is either theoretically computed or derivedfrom field soil calibration data. Soil moisture is the main,but not the only factor that determine local neutronintensity. The minor factors can be assessed by takingancillary measurements along the route (pressure), by takingsoil samples (lattice water and/or soil moisture), and byanalyzing the geometry (topography) and land cover (builtupenvironment, vegetation, surface water) along the route.Measurements obtained with a prototype cosmic-ray rover inHawaii, Arizona and Oklahoma show that the COSMOSrover is capable of generating soil moisture data quickly andinexpensively. Measurements over an area are suitable forcalibration and validation (cal/val) of satellite microwavesensors, such as those in the current SMOS mission and thefuture SMAP mission. A satellite microwave pixel of 40 kmby 40 km can be covered in less than a day of driving.Repeated surveys along the same routes can reveal temporalchanges in soil moisture, for example related to seasonal- orlonger-term climate change. The prototype of the rover savesdata to an SD card and the data processing is performedlater. There is a potential for the cosmic-ray rover to yieldsoil moisture data in real time, and either send them viabluetooth to a nearby computer in the rover vehicle or beamthem to a remote computer via Iridium satellite modem. Weare working on a new version of the rover with these andother improvements. If the instrument is ready we will showit at the meeting and then conduct a survey over the Islandof Hawaii with data beamed via satellite modem to theconference room.cosmos.hwr.arizona.edu160