Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas. Issue 20 (30th August 2017)

• Record Type: Journal Article
• Authors: Li, Sisi; Gitau, Margaret; Bosch, David; Engel, Bernard A.; Zhang, Liang; Du, Yun
• Is Part Of: Hydrological processes. Volume 31:Issue 20(2017)
• Page Start: 3543
• Page End: 3557
• Publication Date: 2017-08-30
• Subjects: infiltration excess run‐off -- non‐point source pollution -- saturation excess run‐off -- soil moisture -- soil topographic index -- spatially distributed model; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.11276
• Languages: English
• ISSNs: 0885-6087

Abstract

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‐km 2 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.