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Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas
Authors:Sisi Li  Margaret Gitau  David Bosch  Bernard A Engel  Liang Zhang  Yun Du
Affiliation:1. Key Laboratory for Environment and Disaster Monitoring and Evaluating, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China;2. Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA;3. University of Chinese Academy of Sciences, Beijing, China;4. USDA‐ARS Southeast Watershed Research Lab, Tifton, GA, USA
Abstract:A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km2 Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.
Keywords:infiltration excess run‐off  non‐point source pollution  saturation excess run‐off  soil moisture  soil topographic index  spatially distributed model
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