Modelling the impact of climate change on soil erosion and sediment yield: a case study in a sub-tropical catchment, India

Abstract

Climate change most likely to increase the soil erosion (SE) and sediment yield (SY) rate by changing the rainfall–runoff erosivity in many locations worldwide. Global climate model output is commonly used to appraise the impact of climate change on SE and SY. However, determining the suitable climate model is challenging for the accurate simulation of future SE and SY. Therefore, The Revised Universal Soil Loss Equation (RUSLE) coupled with Sediment Delivery Ratio (SDR) model was used to estimate the SE and SY in the humid sub-tropical catchment. We also evaluated the high-resolution regional climate models (RCMs) using five statistical bias correction methods (linear scaling, empirical quantile mapping, quantile mapping with linear transformation, quantile mapping with smoothing spline, and quantile mapping with gamma distribution) for future simulation of the SE and SY. Our result suggests that quantile mapping with gamma distribution-based bias correction method and ICHEC-EC-EARTH-RCA model best project the changes in precipitation and consequently, the rainfall–runoff erosivity factor in the catchment. It is estimated that a 3.67–11.08% increase in rainfall–runoff erosivity may result in a 3.7–11.76% increase in SE and SY in the catchment under the representative concentration pathway (RCP) 4.5 and RCP 8.5 emission scenarios. In addition to this 1.6-thousand-hectare area will be included in high (10–20 t ha−1 year−1) to very severe (> 80 t ha−1 year−1) SE intensity class during the near (2020–2049) and far future (2070–2099) period. The result also revealed that the increasing rate of SE and SY will be observed in the sub-catchment numbers 10, 18, 20, 23, 24, 27, 29 located in the middle part of the catchment under the RCP 8.5 scenario. The result may help the policymakers to strengthen the conservation strategy and more informed decisions for the management of catchment in and around the area.