Rainfall erosivity in China based on CLDAS fusion precipitation
Received date: 2022-01-12
Revised date: 2022-03-04
Online published: 2022-10-20
Rain gauge data is still the most popular data for estimating rainfall erosivity. However, although this precipitation data is highly accurate, it is not suitable for estimating rainfall erosivity on a large, regional scale. It can only reflect the situation of rainfall erosivity in the area surrounding the weather station. Although satellite imagery can reflect the spatial and temporal distribution of precipitation, its application in various professional fields is limited by its poor accuracy. Fusion precipitation data is produced by fusing precipitation data from different sources, such as station precipitation, satellite precipitation, and radar precipitation, all on the same spatial and temporal scales. The advantage of combining multiple sources is that it produces data that more closely represents the true spatial distribution of precipitation. With the high temporal resolution CMA land data assimilation system (CLDAS) fusion precipitation, this study uses the EI60 model to assess rainfall erosion in China on different spatial and temporal scales and to determine the potential role of rainfall on soil erosion by precipitation, erosive rainfall, and precipitation erosion density. The article draws the following conclusions: (1) CLDAS rainfall erosivity is slightly lower than the rain gauge results but presents a very good regression relationship with rain gauge erosivity, with high correlation coefficients at different time scales, and a lower margin of error than the rainfall erosivity from the Climate Prediction Center Morphing (CMORPH) technique, which can accurately reflect the rainfall erosivity variation on a national scale. (2) In different rainfall zones, trends in rainfall erosivity, rainfall volume, and the number of erosive rainfall events from 2001 to 2020 are generally consistent, with sharp inter-annual fluctuations in high rainfall zones. (3) Spatially, Chinese rainfall erosivity is characterized by high values in the southeast coastal areas and low values in the northwest inland areas. Temporally, erosive rainfall is concentrated from May to August. Rainfall in summer and autumn results in greater erosive impacts on the soil. (4) The quantitative analysis of annual rainfall, annual erosion density, and annual storms shows that storm and rainfall erosion density are positively correlated. In other words, the more rainstorm events there are, the higher the rainfall erosion density and rainfall erosivity. This study can serve as a scientific reference for theoretical research on soil erosion and soil conservation practices in China.
Key words： rainfall erosivity; EI60 model; CLDAS fusion precipitation
Yujing LIANG , Runping SHEN , Chunxiang SHI , Yajie XING , Shuai SUN . Rainfall erosivity in China based on CLDAS fusion precipitation[J]. Arid Land Geography, 2022 , 45(5) : 1333 -1346 . DOI: 10.12118/j.issn.1000-6060.2022.019
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