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Assessing Climate Change Impacts on Water Balance, Runoff, and Water Quality at the Field Scale for Four Locations in the Heartland
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Transactions of the ASABE. 56(3): 883-900. (doi: 10.13031/trans.56.9134) @2013
Authors: Michael W. Van Liew, Song Feng, Tapan B. Pathak
Keywords: Model Calibration Hydrology Water Quality Climate Change SWAT.
This study employed the Soil and Water Assessment Tool (SWAT) to evaluate the impacts of projected future climate change scenarios on water balance, runoff, sediment, total nitrogen (N), and total phosphorus (P) at the field scale for four locations in the Heartland region: Sioux City (Iowa) and Columbus, Mullen, and Harrison (Nebraska). A conventional two-year corn-soybean rotation was assumed to be grown on each field. All fields were simulated identically in terms of topographic and cover/land management conditions. Model inputs for the fields differed in only three ways: the forcing conditions for existing and future climatic scenarios (SRES A2, A1B, and B1), soil and aquifer properties, and calibrated parameters at each location. Model simulations indicate that for the Columbus and Sioux City sites, where current average annual precipitation is about 740 and 650 mm, respectively, substantial increases in runoff and pollutant loadings from a corn-soybean crop rotation are projected to occur during the spring under future climate scenarios in comparison to existing conditions. At the Sioux City site, for example, increases in runoff of 213%, 124%, and 128% during the month of May are projected for the A2, A1B, and B1 scenarios, respectively, in comparison to the baseline condition. Very large increases in attendant sediment and nutrient losses are also projected for that month at the Sioux City site. Considerably greater attention in coming years will therefore likely be necessary to devise best management practices and adaptation strategies that can be effectively employed to conserve soil and water resources and to protect streams and receiving waters from the harmful effects of higher pollutant loadings. At the Harrison site, where average annual precipitation is less than 450 mm, increases in average annual evapotranspiration of 29, 31, and 46 mm under the A2, A1B, and B1 future climate scenarios are projected to occur for a corn-soybean crop. Relative to the baseline at this site, water requirements are projected to be 37, 39, and 32 mm greater, respectively, for the peak irrigation month of July under the A2, A1B, and B1 scenarios. For regions in western Nebraska with similar or lesser precipitation levels, these anticipated changes could exacerbate already existing challenges for agricultural producers who primarily rely upon groundwater for irrigation. SWAT was employed to simulate the impact of four best management practices (BMPs) on changes in sediment, total N, and total P under the baseline and future climate change scenarios for each site. These four treatments included conversion of the corn-soybean rotation to pasture, switchgrass, and no-till, and implementation of a 10 m wide edge-of-field buffer strip. At all four sites, the pasture and switchgrass BMPs reduced sediment and total P yields by 97% to 99% in comparison to the corn-soybean cover crop. Each of the BMP treatments employed in this study appears to hold promise in providing potential reductions in sediment and nutrients for the two eastern field sites. However, further analyses are needed to not only assess the impact of other types of BMPs, but their cost effectiveness and sustainability as well. Model simulations suggest that, for the Harrison site, moderate decreases in sediment, total N, and total P are projected to occur for the no-till BMP and modest decreases for the 10 m buffer strip BMP. Model simulations also suggest that, of the four BMP types, only the pasture and switchgrass treatments appear to provide appreciable reductions in sediment and nutrients at the Mullen site.(Download PDF) (Export to EndNotes)