Projections of rainfall erosivity in climate change scenarios for mainland China

This study focuses on improving the accuracy of projections for future rainfall erosivity by selecting five CMIP6based and bias-adjusted Global Climate Models (GCMs) in China. These models provide more precise estimations of rainfall erosivity under two future periods (2041-2065 and 2076-2100) and two emission scenarios (SSP1RCP2.6 and SSP5-RCP8.5). The evaluation of the models' performance involved comparing their estimations of two erosivity indices, namely the annual average rainfall erosivity (R-factor) and the extreme storm EI30 with a 10-year return period (10-year storm EI), with reference erosivity maps of China interpolated from hourly observations at 2381 stations. The results indicate that three models, GFDL-ESM4, IPSL-CM6A-LR, and UKESM1-0LL, outperform the others in terms of higher Nash-Sutcliffe efficiencies and better spatial correlation, especially in regions prone to water erosion. However, it was observed that the R-factor and 10-year storm EI estimated using Multi-Model Ensembles (MMEs) were significantly underestimated for the historical period due to scaling differences. To address this issue, bias-correction factors were determined for each grid cell to improve future projections. The medians of these correction factors were found to be 0.80 for the R-factor and 0.66 for the 10year storm EI. Overall, the study projects an increase in rainfall erosivity for most regions in China. Under the SSP1-RCP2.6 and SSP5-RCP8.5 scenarios, the R-factor is expected to rise by 18.9% and 19.8% for the near-term and 26.0% and 46.5% for the long-term, respectively. Similarly, the 10-year storm EI is projected to increase by 14.2% and 17.4% for the near-term and 14.9% and 45.0% for the long-term, respectively. These projected increases are primarily attributed to the elevated probability of extreme precipitation events, highlighting the need for enhanced soil and water conservation measures in China to mitigate the challenges posed by global warming.