Published March 28, 2016
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Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

  • 1. Faculty of Civil Engineering and Geosciences, Department of Water Management, Delft University of Technology, Stevinweg 1, Delft 2628 CN, The Netherlands
  • 2. Delft University of Technology
  • 3. FutureWater, Costerweg 1V, Wageningen 6702 AA, The Netherlands
  • 4. UNESCO-IHE, Westvest 7, Delft 2611 AX, The Netherlands
  • 5. Faculty of Hydrology and Water Resources, Thuy Loi University, 175 Tay Son, Dong Da, Ha Noi, Vietnam
  • 6. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USA
  • 7. University of Maryland, College Park
  • 8. Hydrology and Remote Sensing Labaratory, USDA-ARS, Beltsville, MD 20705, USA
  • 9. USGS EROS Center, North Central Climate Science Center, Colorado State University, Fort Collins, CO 80523, USA
  • 10. Colorado State University

Description

With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P) and land use/land cover (LULC) is currently being expanded with the application of actual evapotranspiration (ETact) algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.
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