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

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