Title: Swat Ungauged: Hydrological Budget and Crop Yield Predictions in the Upper Mississippi River Basin Authors
|Srinivasan, Raghavan -|
|Zhang, Xuesong -|
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 1, 2010
Publication Date: September 1, 2010
Citation: Srinivasan, R., Zhang, X., Arnold, J.G. 2010. SWAT ungauged: Hydrological budget and crop yield predictions in the Upper Mississippi River Basin. Transactions of the ASABE. 53(5):1533-1546. Interpretive Summary: The Upper Mississippi River Basin drains 490,000 square kilometers in Minnesota, Illinois, Indiana, Iowa, and Missouri. It contains some of the most fertile and productive farm land in the world. The application of fertilizer and manure also causes nitrogen and phosphorus in runoff that ultimately contributes to a hypoxic or dead zone in the Gulf of Mexico. In this study, the Soil and Water Assessment Tool (SWAT) was used to assess the impact of growing switchgrass on all agricultural land for biofuel production. Model results showed biofuel production potential and sustainability as well as environmental impacts. The study also showed that the SWAT model can generate reasonable results without calibration. This work gives policy makers a tool to identify the impact of agricultural land management in the Upper Mississippi River Basin on the hypoxic zone in the Gulf of Mexico.
Technical Abstract: Physically based, distributed hydrologic models are increasingly used in assessments of water resources, best management practices, and climate and land use changes. Model performance evaluation in ungauged basins is an important research topic. In this study, we propose a framework for developing Soil and Water Assessment Tool (SWAT) input data, including hydrography, terrain, land use, soil, tile, weather, and management practices, for the Upper Mississippi River basin (UMRB). We also present a performance evaluation of SWAT hydrologic budget and crop yield simulations in the UMRB without calibration. The uncalibrated SWAT model ably predicts annual streamflow at 11 USGS gauges and crop yield at a four-digit hydrologic unit code (HUC) scale. For monthly streamflow simulation, the performance of SWAT is marginally poor compared with that of annual flow, which may be due to incomplete information about reservoirs and dams within the UMRB. Further validation shows that SWAT can predict base flow contribution ratio reasonably well. Compared with three calibrated SWAT models developed in previous studies of the entire UMRB, the uncalibrated SWAT model presented here can provide similar results. Overall, the SWAT model can provide satisfactory predictions on hydrologic budget and crop yield in the UMRB without calibration. The results emphasize the importance and prospects of using accurate spatial input data for the physically based SWAT model. This study also examines biofuel-biomass production by simulating all agricultural lands with switchgrass, producing satisfactory results in estimating biomass availability for biofuel production.