Global rainfall erosivity changes between 1980 and 2017 based on an erosivity model using daily precipitation data

Abstract

Rainfall erosivity (R) is the most important factor affecting soil erosion. It is crucial to estimate it on a global scale to identify the potential soil erosion risk area and to develop mitigation strategies. On a large scale, R is often estimated based on available precipitation data, such as annual, monthly and daily rainfall. Compared with the rainfall erosivity model driven by monthly and annual rainfall data, the daily erosivity model can provide more information about intense erosive events, producing more accurate results. Given the climate variability in different regions, regional parameters are needed when applying the daily erosivity model on a global scale. However, regional parameter estimation is a challenge, and few studies have addressed this.Here, we present a method for parameterising the daily erosivity model for different regions of the world by generating equations for estimating the required parameters of the model in each climate zone. This was based on a literature review to collect the data sites with estimated parameter values globally. We then applied the model to compare the global average annual and monthly rainfall erosivity changes between 1980–1999 (P1) and 2000–2017 (P2). The results showed that globally, average annual R decreased in all climate zones in P2, except for a substantial increase in Df (Cold without dry season), located in high latitudes of the northern hemisphere. At the monthly scale, except for the region 40-70°N, all regions experienced a considerable decrease. Even though the global total annual and monthly rainfall erosivity was reduced between 1980 and 2017, the risk of extreme daily erosivity is high. The acceptable agreements between the values estimated in our model, estimated from high-resolution rainfall data and retrieved from the literature, indicate that the present approach could assess the effects of climate change on soil erosion on a global scale, particularly regarding extreme rainfall events.