Assessing the impacts of climate change and tillage practices on stream flow, crop and sediment yields from the Mississippi River Basin

This study evaluated climate change impacts on stream flow, crop and sediment yields from three different tillage systems (conventional, reduced 1 close to conservation, and reduced 2 close to no-till), in the Big Sunflower River Watershed (BSRW) in Mississippi. The Soil and Water Assessment Tool (SWAT) model was applied to the BSRW using observed stream flow and crop yields data. The model was calibrated and validated successfully using monthly stream flow data (2001-2011). The model performances showed the regression coefficient (R-2) from 0.72 to 0.82 and Nash-Sutcliffe efficiency index (NSE) from 0.70 to 0.81 for streamflow; R-2 from 0.40 to 0.50 and NSE from 0.72 to 0.86 for corn yields; and R-2 from 0.43 to 0.59 and NSE from 0.48 to 0.57 for soybeans yields. The Long Ashton Research Station Weather Generator (LARS-WG), was used to generate future climate scenarios. The SRES (Special Report on Emissions Scenarios) A1B, A2, and B1 climate change scenarios of the Intergovernmental Panel on Climate Change (IPCC) were simulated for the mid (2046-2065) and late (2080-2099) century. Model outputs showed slight differences among tillage practices for corn and soybean yields. However, model simulated sediment yield results indicated a large difference among the tillage practices from the corn and soybean crop fields. The simulated future average maximum temperature showed as high as. 4.8 degrees C increase in the BSRW. Monthly precipitation patterns will remain un-changed based on simulated future climate scenarios except for an increase in the frequency of extreme rainfall events occurring in the watershed. On average, the effect of climate change and tillage practice together did not show notable changes to the future crop yields. The reduced tillage 2 practices showed the highest responses of erosion control to climate change followed by the reduced tillage 1 and conventional tillage in this study. (C) 2016 Elsevier B.V. All rights reserved.