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.
摘要：
在气候变暖和增湿的背景下，高精度的降雨侵蚀力制图对于准确评估青藏高原（TP）区域土壤侵蚀至关重要。尽管高时空分辨率的网格化降水数据为降雨侵蚀率制图提供了基础，当直接从网格化降水数据中计算降雨侵蚀度时，降雨的空间异质性随着时间粒度的降低而增加，会导致更大的误差。在这项研究中,建立了站点尺度转换系数，以便使用每小时数据计算的降雨侵蚀力可以转换为使用每分钟数据计算的降雨侵蚀力。建立了基于第三极网格化降水数据集（TPHiPr）的高分辨率小时降水数据的修正模型，用于计算降雨侵蚀力。结果表明，使用TPHiPr获得的原始计算结果存在明显的低估，但两组结果之间有很强的相关性。模型修正后，纳什-萨克利夫效率系数（从-0.39到0.80）和百分比偏差（从-63.95％到0.37％）有了显着改善。TPHiPr有效地描述了TP上降雨侵蚀力的空间特征。它准确地反映了喜马拉雅山北翼和横断山脉干热山谷的雨影区域。在喜马拉雅山东部南部的热带雨林地区，它还显示出很高的降雨侵蚀力值。在1981年至2020年期间，TP的降雨侵蚀力总体趋势有所增加，其中65.91％的地区呈增加趋势，22.25％的地区呈显着增加趋势，表明水蚀的风险加剧。这些发现表明，40年高空间分辨率的降雨侵蚀力数据集可以为定量了解TP上的土壤侵蚀提供准确的数据支持。
