Simulating site-specific impacts of climate change on soil erosion and surface hydrology in southern Loess Plateau of China

Proper spatial and temporal treatments of climate change scenarios projected by General Circulation Models (GCMs) are critical to accurate assessment of climatic impacts on natural resources and ecosystems. The objective of this study was to evaluate the site-specific impacts of climate change on soil erosion and surface hydrology at the Changwu station of Shaanxi, China using a new spatiotemporal downscaling method. The Water Erosion Prediction Project (WEPP) model and climate change scenarios projected by the U.K. Hadley Centre's GCM (HadCM3) under the A2, B2, and GGa emissions scenarios were used in this study. The monthly precipitation and temperature projections were downloaded for the periods of 1900–1999 and 2010–2039 for the grid box containing the Changwu station. Univariate transfer functions were derived by matching probability distributions between station-measured and GCM-projected monthly precipitation and temperature for the 1950–1999 period. The derived functions were used to spatially downscale the GCM monthly projections of 2010–2039 in the grid box to the Changwu station. The downscaled monthly data were further disaggregated to daily weather series using a stochastic weather generator (CLIGEN). The HadCM3 projected that average annual precipitation during 2010–2039 would increase by 4 to 18% at Changwu and that frequency and intensity of large storms would also increase. Under the conventional tillage, simulated percent increases during 2010–2039, compared with the present climate, would be 49–112% for runoff and 31–167% for soil loss. However, simulated soil losses under the conservation tillage during 2010–2039 would be reduced by 39–51% compared with those under the conventional tillage in the present climate. The considerable reduction in soil loss in the conservation tillage indicates the importance of adopting conservation tillage in the region to control soil erosion under climate change.