Rainfall erosivity mapping over mainland China based on high density hourly rainfall records

Tianyu Yue, S. Yin, Yun Xie, Bofu Yu, Baoyuan Liu
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引用次数: 9

Abstract

Abstract. Rainfall erosivity represents the effect of rainfall and runoff on the average rate of soil erosion. Maps of rainfall erosivity are indispensable for soil erosion assessment using the Universal Soil Loss Equation (USLE) and its successors. To improve current erosivity maps based on daily rainfall data for mainland China, hourly rainfall data from 2381 stations for the period 1951–2018 were collected to generate the R factor and the 1-in-10-year EI30 maps (available at https://dx.doi.org/10.12275/bnu.clicia.rainfallerosivity.CN.001; Yue et al., 2020). Rainfall data at 1-min intervals from 62 stations (18 stations) were collected to calculate rainfall erosivities as true values to evaluate the improvement of the new R factor map (1-in-10-year EI30 map) from the current maps. Both the R factor and 1-in-10-year EI30 decreased from the southeastern to the northwestern, ranging from 0 to 25300 MJ mm ha−1 h−1 a−1 for the R factor and 0 to 11246 MJ mm ha−1 h−1 for the 1-in-10-year EI30. New maps indicated current maps existed an underestimation for most of the southeastern areas and an overestimation for most of the middle and western areas. Comparing with the current maps, the R factor map generated in this study improved the accuracy from 19.4 % to 15.9 % in the mid-western and eastern regions, from 45.2 % to 21.6 % in the western region, and the 1-in-10-year EI30 map in the mid-western and eastern regions improved the accuracy from 21.7 % to 13.0 %. The improvement of the new R factor map can be mainly contributed to the increase of data resolution from daily data to hourly data, whereas that of new 1-in-10-year EI30 map to the increase of the number of stations from 744 to 2381. The effect of increasing the number of stations to improve the interpolation seems to be not very obvious when the station density was denser than about 10 · 103 km2 1 station.
基于高密度时雨量记录的中国大陆降雨侵蚀力制图
摘要降雨侵蚀力表示降雨和径流对土壤侵蚀平均速率的影响。降雨侵蚀力图对于使用通用土壤流失方程(USLE)及其后续方法进行土壤侵蚀评估是必不可少的。为了改进目前基于中国大陆日降雨数据的侵蚀力图,收集了1951-2018年2381个站点的逐时降雨数据,生成了R因子和10年1次的EI30图(可在https://dx.doi.org/10.12275/bnu.clicia.rainfallerosivity.CN.001;Yue等人,2020)。利用62个站点(18个站点)的1 min间隔降水数据,计算降雨侵蚀率作为真值,评价新R因子图(1-in-10年EI30图)相对于现有图的改进。R因子和1- 10年EI30从东南向西北递减,R因子为0 ~ 25300 MJ mm ha−1 h−1 a−1,1- 10年EI30为0 ~ 11246 MJ mm ha−1 h−1。新地图表明,目前的地图对大多数东南部地区估计不足,对大多数中西部地区估计过高。与现有的R因子图相比,本研究生成的R因子图将中西部和东部地区的准确率从19.4%提高到15.9%,将西部地区的准确率从45.2%提高到21.6%,将中西部和东部地区的10年1次EI30图的准确率从21.7%提高到13.0%。新R因子图的改进主要表现在数据分辨率从日数据提高到逐时数据,而新1- 10年EI30图的改进主要表现在站点数从744个增加到2381个。当站点密度大于10·103 km2 / 1站点时,增加站点数对插值的改善效果不明显。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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