Assessment of Variability of Rainfall Erosivity Using Different Rainfall Products

Soil erosion is a global issue that leads to loss of soil and nutrients thus affecting agricultural land. Rainfall erosivity, a critical factor influencing soil erosion, refers to the potential of rainfall to cause soil displacement and is commonly calculated using empirical equations. This study aims to estimate the spatial and temporal variations in rainfall erosivity over Kerala, India, using datasets including Indian Meteorological Department (IMD) station data, IMD gridded data, and two satellite precipitation products - Tropical Rainfall Measuring Mission (TRMM), and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Results show that CHIRPS significantly underestimates rainfall erosivity due to its difficulty in capturing high-intensity, localized rainfall typical in Kerala's mountainous regions. TRMM, while more reliable than CHIRPS, also underestimates erosivity to a lesser extent. The IMD gridded dataset, derived from station data, also exhibits interpolation-induced biases. Future projections of rainfall erosivity under two emission scenarios, SSP 2-4.5 and SSP 5-8.5, suggest a likely increase in erosivity, especially under the high-emission scenario. This increase emphasizes the need for proactive soil conservation strategies to mitigate future soil erosion risks. The study underscores the importance of accurate rainfall data in erosivity estimation and suggests that satellite data should be corrected before using it for erosivity estimation.