Abstract
The resultant calibration parameter values and simulation accuracy of hydrologic models such as the 2005 Soil and Water Assessment Tool (SWAT2005) depend on how well spatial input parameters describe the characteristics of the study area. The objectives of this study were to (1) investigate the effect of soils dataset resolution (State Soil Geographic Database and Soil Survey Geographic Database) on SWAT2005 streamflow simulation performance and calibration parameters using four precipitation datasets and (2) determine the best combination of soil and precipitation datasets for the Cobb Creek, Lake Creek, and Willow Creek subwatersheds within the Fort Cobb Reservoir Experimental watershed, Oklahoma. SWAT2005 was calibrated and validated for streamflow for the three subwatersheds using the State Soil Geographic Database and the Soil Survey Geographic Database for each of the four available precipitation datasets with different spatial resolutions. The four sources of rainfall data included the National Weather Service's network of Cooperative Observer Program weather stations, statewide Oklahoma Mesonet, USDA Agricultural Research Service's weather station network (MICRONET), and National Weather Service Next Generation Radar (NEXRAD) precipitation estimates. The model performance was assessed using the Nash-Sutcliffe efficiency coefficient and percent bias statistics. During both the calibration and validation periods, there were no significant differences in the model monthly performance statistics between the higher resolution Soil Survey Geographic Database and the lower resolution State Soil Geographic Database across subwatersheds, irrespective of the rainfall dataset used. However, the model performed better when the NEXRAD and MICRONET precipitation datasets were used. There were slight to large differences in the resultant calibration parameter values depending on the calibration parameter, the precipitation data used, and the subwatershed. Large differences in the simulated surface runoff and deep aquifer recharge due to soils dataset resolution could lead to significant differences in the simulated water quality components such as sediments and nutrients. This is important because significant differences in simulated sediments and/or nutrients could lead to significantly different outcomes in terms of the impacts of a given conservation practice for studies like the Conservation Effects Assessment Project. Due to the lack of measured data to validate the simulated water balance components, it was recommended to use both the fine and coarse resolution soil datasets in combination with the finer spatial resolution precipitation datasets and the simulated water balance components of interest reported as a range.
Footnotes
Daniel N. Moriasi is a hydrologist, and Patrick J. Starks is a soil scientist at the USDA Agricultural Research Service (ARS) Grazinglands Research Laboratory, El Reno, Oklahoma.
- © 2009 by the Soil and Water Conservation Society
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