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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #340975
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Use of high resolution remotely sensed evapotranspiration retrievals for calibration of a process-based hydrologic model in data-poor basins

Author
item AMIR, SHARIFI - University Of Maryland
item SUN, L. - US Department Of Agriculture (USDA)
item Anderson, Martha
item McCarty, Gregory
item Crow, Wade
item Gao, Feng
item Sadeghi, Ali

Submitted to: European Geophysical Society Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 5/2/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Calibration of process-based hydrologic models is a challenging task in data-poor basins, where monitored hydrologic data are scarce. In this study, we present a novel approach that benefits from remotely sensed evapotranspiration (ET) data to calibrate a complex watershed model, namely the Soil and Water Assessment Tool (SWAT), for flow predictions at daily scales. The ET retrievals come from the disaggregated Atmosphere Land Exchange Inverse model (DisALEXI), which provides ET estimates daily at 30m resolution by fusing satellite information from several platforms. In this method, an efficient optimization algorithm is implemented to find an optimal combination of SWAT parameter values that leads to convergence between SWAT and DisALEXI ET estimates. The proposed method was applied to a 290 km2 watershed located on the Delmarva Peninsula, USA. Results show that when SWAT was calibrated under the proposed method, daily flow predictions improved significantly in comparison to the uncalibrated model.