The Tibetan Plateau(TP)in China has been experiencing severe water erosion because of climate warming.The rapid development of weather station network provides an opportunity to improve our understanding of rainfall erosivity in the TP.In this study,1-min precipitation data obtained from 1226 weather stations during 2018-2019 were used to estimate rainfall erosivity,and subsequently the spatial-temporal patterns of rainfall erosivity in the TP were identified.The mean annual erosive rainfall was 295 mm,which accounted for 53％of the annual rainfall.An average of 14 erosive events occurred yearly per weather station,with the erosive events in the wet season being more likely to extend beyond midnight.In these cases,the precipitation amounts of the erosive events were found to be higher than those of the daily precipitations,which may result in implicit bias as the daily precipitation data were used for estimating the rainfall erosivity.The mean annual rainfall erosivity in the TP was 528 MJ mm·ha-1·h-1,with a broader range of 0-3402 MJ mm·ha-1·h-1,indicating a significant spatial variability.Regions with the highest mean annual rainfall erosivity were located in the forest zones,followed by steppe and desert zones.Finally,the precipitation phase records obtained from 140 weather stations showed that snowfall events slightly impacted the accuracy of rainfall erosivity calculation,but attention should be paid to the erosion process of snowmelt in the inner part of the TP.These results can be used as the reference data for soil erosion prediction in normal precipitation years.

State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing China;Institute of International Rivers and Eco-security,Yunnan University,Kunming China;CMA Earth System Modeling and Prediction Centre,Beijing China

[1]Yueli Chen;Xingwu Duan;Guo Zhang;Minghu Ding;Shaojuan Lu-.Rainfall erosivity estimation over the Tibetan plateau based on high spatial-temporal resolution rainfall records)[J].国际水土保持研究（英文）,2022(03):422-432

erosivity

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