Abstract
Water-induced soil erosion poses significant threats to land productivity, ecosystem health, and environmental sustainability in India. This study quantifies annual water erosion across India from 2001 to 2020 using a regionally enhanced Revised Universal Soil Loss Equation (RUSLE) framework. High-resolution remote sensing datasets and machine learning techniques were integrated to derive key RUSLE factors at the national scale. Model estimates were validated against observed sediment load data from 134 stations across major Indian river basins. Results indicate a long-term mean annual erosion rate of 12 t ha(-1) year(-1), substantially exceeding the global average. The erosion-affected area (> 10 t ha(-1) year(-1)) decreased slightly from 52 Mha in 2001 to 50 Mha in 2020, with Sen's slope indicating a small and statistically non-significant decline of -0.03 Mha year(-1). Erosion hotspots were identified in the Himalayan and northeastern mountain regions and the coastal plains of southern India. Increasing erosion trends were observed across the western plains, central highlands, and parts of the Deccan Plateau, while declining trends were mainly concentrated in the Indo-Gangetic Plains and parts of northeastern India. Basin-scale validation showed a strong long-term correlation between modeled and observed gross erosion (R-2 = 0.56), although model performance exhibited substantial interannual variability. This study demonstrates the effectiveness of combining empirical erosion modeling with dynamic, data-driven approaches to assess fine-scale erosion risks. The findings provide valuable guidance for prioritizing soil conservation strategies and highlight the urgent need for sustainable land management in erosion-prone regions across India.