Improvement of satellite‐based rainfall product CHIRPS in estimating rainfall erosivity on the Loess Plateau

Abstract

AbstractSatellite‐based rainfall products have great potential for estimating rainfall erosivity, as they can provide continuous spatiotemporal distribution of precipitation estimates over large areas, especially for monitoring in areas with complex terrain and extreme climates. This paper uses the daily rainfall derived from the satellite‐based CHIRPS product on the GEE platform and Zhang's daily rainfall erosivity model to calculate the rainfall erosivity on the Loess Plateau during the period of 1981–2020. The accuracy of rainfall erosivity for the CHIRPS product is evaluated by comparing the results to estimates from national meteorological stations, and then the calculation formula of rainfall erosivity is optimized to improve the accuracy of rainfall erosivity based on CHIRPS products. The results show that the annual average rainfall of the CHIRPS product at the locations of national meteorological stations in 1981–2020 is 473.7 mm, which is 6.8% higher than that observed by the meteorological stations. The multi‐year average value of daily rainfall and the yearly average rainfall both for days with rainfall larger than or equal to 12 mm are 15.9% and 18.2% greater than those of the meteorological stations, respectively, and eventually resulting in an overestimation of rainfall erosivity on the Loess Plateau by 44.0%. The annual mean rainfall erosivity interpolated based on meteorological stations and calculated from the gridded CHIRPS product in 1981–2020 is 1344.2 MJ·mm/(hm2·h) and 2013.7 MJ·mm/(hm2·h), respectively. This result suggests that rainfall erosivity estimated by gridded CHIRPS product is overestimated by 49.8%, of which 46.1% is due to the overestimation of erosive rainfall in gridded CHIRPS and 3.7% is caused by site density and interpolation. Satellite‐based CHIRPS product is similar to the observations of meteorological stations in total rainfall and trends, but differs in rainfall frequency and intensity, which is an important reason for the difference in rainfall erosivity between satellite‐based rainfall products and meteorological stations. The CHIRPS‐based rainfall erosivity calculated using the optimized parameters reduces the overestimation from 49.8% to 3.2%, greatly reducing the satellite‐based rainfall erosivity estimation error.