Evaluating rainfall erosivity on the Tibetan Plateau by integrating high spatiotemporal resolution gridded precipitation and gauge data

Abstract

High-precision rainfall erosivity mapping is crucial for accurately evaluating regional soil erosion on the Tibetan Plateau (TP) under the backdrop of climate warming and humidification. Although high spatiotemporal resolution gridded precipitation data provides the foundation for rainfall erosivity mapping, the increasing spatial heterogeneity of rainfall with decreasing temporal granularity can lead to greater errors when directly computing rainfall erosivity from gridded precipitation data. In this study, a site-scale conversion coefficient was established so that rainfall erosivity calculated using hourly data can be converted to rainfall erosivity calculated using per-minute data. A revised model was established for calculating the rainfall erosivity based on high-resolution hourly precipitation data from the Third Pole gridded precipitation dataset (TPHiPr). The results revealed a notable underestimation in the original calculation results obtained using the TPHiPr, but strong correlation was observed between the two sets of results. There was a significant improvement in the Nash–Sutcliffe coefficient of efficiency (from −0.39 to 0.80) and the Percent Bias (from −63.95 % to 0.37 %) after model revision. The TPHiPr effectively depict the spatial characteristics of rainfall erosivity on the TP. It accurately reflected the rain shadow area on the northern flank of the Himalayas and the dry-hot valley in the Hengduan Mountains. It also showed high rainfall erosivity values in the tropical rainforest area on the southern flank of the eastern Himalayas. The overall trend of rainfall erosivity has increased on the TP during the period 1981 to 2020, with 65.91 % of the regions exhibiting an increasing trend and 22.25 % showing significant increases, indicating an intensified risk of water erosion. These findings suggest that the 40-year-high spatial resolution rainfall erosivity dataset can provide accurate data support for a quantitative understanding of soil erosion on the TP.