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

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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
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esilience to hydrological hazards a
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Alfieri, Joseph G.The Factors Influ
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Montana and Oregon. Other applicati
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accuracy of snow derivation from si
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seasonal trends, and integrate clou
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a single mission, the phrase “nea
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climate and land surface unaccounte
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esolution lidar-derived DEM was com
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further verified that even for conv
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underway and its utility can be ass
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Courault, DominiqueAssessment of mo
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used three Landsat-5 TM images (05/
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storage change solutions in the for
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Famiglietti, James S.Getting Real A
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can be thought of as operating in t
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mission and will address the follow
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Gan, Thian Y.Soil Moisture Retrieva
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match the two sets of estimates. Th
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producing CGF snow cover products.
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performance of the AWRA-L model for
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oth local and regional hydrology. T
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Euphorbia heterandena, and Echinops
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the effectiveness of this calibrati
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presents challenges to the validati
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long period time (1976-2010) was co
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has more improved resolution ( ) to
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in the flow over the floodplain ari
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Page 91 and 92: hydrologists, was initially assigne
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Page 103 and 104: Moller, DelwynTopographic Mapping o
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Page 111 and 112: approach to estimate soil water con
Page 113 and 114: Norouzi, HamidrezaLand Surface Char
Page 115 and 116: Painter, Thomas H.The JPL Airborne
Page 117 and 118: Pavelsky, Tamlin M.Continuous River
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Page 131 and 132: Selkowitz, DavidExploring Landsat-d
Page 133 and 134: Shahroudi, NargesMicrowave Emissivi
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Page 137: Sturm, MatthewRemote Sensing and Gr
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Page 145 and 146: Vanderjagt, Benjamin J.How sub-pixe
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Page 155 and 156: Xie, PingpingGauge - Satellite Merg
Page 157 and 158: Yebra, MartaRemote sensing canopy c
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