Rainfall erosivity index for monitoring global soil erosion

Rainfall erosivity (R) is commonly used to measure water and soil loss by representing the degree of rainfall-induced soil erosion. However, methods for calculating rainfall erosivity vary significantly regarding regional climatic and precipitation characteristics. How to quantitatively illustrate rainfall erosivity remains a key issue for soil erosion monitoring. In this paper, we summarize the basic principles in calculating rainfall erosivity, as well as the relationships and differences among mainstream methods. By referring to experiences gained from previous studies, this paper aims to better summarize and analyze the current rainfall erosivity estimation models and space–time distribution, so as to avoid the confused use of each estimation model as well as to proposes future researches. Currently, there is a widespread utilization of simple algorithms for rainfall erosivity estimation, and statistical methods like machine learning are also seen in such applications. Besides, while many have proposed to quantify local-scale rainfall erosivity, significant limitations are recognized for large-scale estimations. Future researches that emerge recently developed technologies such as remote sensing are expected to further improve rainfall erosivity estimation.