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Rainfall erosivity is an important indicator for quantitatively representing the erosive power of rainfall. This study expanded three satellite-based precipitation products (SPPs) for estimating and mapping rainfall erosivity in a subtropical basin in China and evaluated their performance at different rainfall erosivity intensities, seasons, and spaces. The results showed that the rainfall erosivity data from GPM-IMERG had the smallest errors compared to the estimates from rain gauge data on monthly and seasonal scales, while data from PERSIANN-CDR and TRMM 3B42 significantly underestimated and slightly overestimated rainfall erosivity, respectively. The three SPPs generally presented different strengths and weaknesses in different seasons. TRMM 3B42 performed best in summer, with small biases, but its performance was less satisfactory in winter. The precision of estimates from GPM-IMERG was higher than that from TRMM 3B42; the biases, especially in winter, were significantly reduced. For different intensities, PERSIANN-CDR overestimated light rainfall erosivity but underestimated heavy rainfall erosivity. In terms of space, TRMM 3B42 and GPM-IMERG correctly presented the spatial pattern of rainfall erosivity. However, PERSIANN-CDR tended to be less skillful in describing its spatial maps. Outcomes of the study provide an insight into the suitability of the SPPs for estimating and mapping rainfall erosivity and suggest possible directions for further improving these products. [ABSTRACT FROM AUTHOR]

Soil erosion is one of the most critical environmental hazards in the world. Understanding the changes in rainfall erosivity (RE) and erosivity density (ED), as well as their affecting factors, at local and catchment scales in the context of climate warming is an important prerequisite of soil erosion prevention and soil loss risk assessment. The present study identified the variability and trends of RE and ED in terms of both time and space in the Ganjiang River catchment over the period of 1960-2012, and also analyzed and discussed the impact of climate change. The results show that RE and ED in the catchment had great monthly variations and high year-to-year variability. Both presented long-term increasing trends over the entire study period. The highest RE and ED were observed in June and in the eastern and northeast parts of the catchment, which indicated that June was the most susceptible month for soil erosion in this area and the lower reaches of the Ganjiang River was the riskiest area for soil erosion. Finally, the East Asian summer monsoon and climate change were highly correlated with changes in RE and ED. [ABSTRACT FROM AUTHOR]

Rainfall erosivity (RE) is a significant indicator of erosion capacity. The application of Tropical Rainfall Measuring Mission (TRMM) rainfall products to deal with RE estimation has not received much attention. It is not clear which temporal resolution of TRMM data is most suitable. This study quantified the RE in the Poyang Lake basin, China, based on TRMM 3B42 3-hourly, daily, and 3B43 monthly rainfall data, and investigated their suitability for estimating RE. The results showed that TRMM 3-hourly product had a significant systematic underestimation of monthly RE, especially during the period of April–June for the large values. The TRMM 3B42 daily product seems to have better performance with the relative bias of 3.0% in summer. At the annual scale, TRMM 3B42 daily and 3B43 monthly data had acceptable accuracy, with mean error of 1858 and −85 MJ∙mm/ha∙h and relative bias of 18.3% and −0.85%, respectively. A spatial performance analysis showed that all three TRMM products generally captured the overall spatial patterns of RE, while the TRMM 3B43 product was more suitable in depicting the spatial characteristics of annual RE. This study provides valuable information for the application of TRMM products in mapping RE and risk assessment of soil erosion. [ABSTRACT FROM AUTHOR]