Abstract

Climate change is predicted to impose great pressures on crop yield and water quantity and quality. However, the connections among agriculture, climate condition, and water quality are supported by scant studies because of different scales of focus. The present study aimed on the interactions of ... Show moreClimate change is predicted to impose great pressures on crop yield and water quantity and quality. However, the connections among agriculture, climate condition, and water quality are supported by scant studies because of different scales of focus. The present study aimed on the interactions of crop yield, climate change, and water quality at field scale. Using the Environmental Policy Integrated Climate (EPIC) model, and drawing on 12 dynamically downscaled regional climate model (RCM) simulations, the impacts of climate change on crop yield, surface runoff, subsurface drainage, and dissolved reactive phosphorus (DRP) losses were determined for a field in the Lake Erie basin under a corn-soybean rotation receiving solid cattle manure fertilization. The combined and individual impacts of different weather variables were evaluated with each of the 12 simulations. The mean cross-model climate change impacts included 16% and 14% increases in corn and soybean yield, respectively, as well as 4% rise and 22% decline in runoff and subsurface drainage DRP, respectively, resulting in an overall 11% decline in total DRP losses. An increase of temperature alone increased crop yields (12% for corn and 8% for soybean, respectively) as it decreased temperature stress resulted from delayed planting, which also decreased total DRP loss by 19%. Regardless of having a negligible impact on yield due to negligible water stress, increased precipitation increased total DRP loss by 15%. The research site could benefit from climate change in terms of both economic return and environmental quality, notwithstanding, greater attention should be paid to management practices with respect to soil DRP loss in surface runoff due to projected precipitation uncertainty. Show less