Estimation of Soil Loss using RUSLE, GIS, and Remote Sensing: A Case Study of Sangli District, Maharashtra

Accurate estimation of soil loss is essential for watershed managers and planners to identify the priority areas for soil and water conservation measures. This study was undertaken to estimate the average annual soil loss in the study area of Sangli district, Maharashtra by using the Revised Universal Soil Loss Equation (RUSLE) in conjunction with Geographic Information System (GIS) and Remote Sensing (RS) data. The five potential factors of RUSLE impacting soil erosion were estimated through remote sensing data, enabling a comprehensive and informed assessment of soil erosion. The results of the analysis revealed that the average annual soil loss from the study area varied between 0 t.ha^-1.yr^-1 and 202.10 t.ha^-1.yr^-1. Higher annual soil loss was estimated in the western part of the study area, which ranged from 15 t.ha^-1.yr^-1 to 25 t.ha^-1.yr^-1 as compared to other parts of the study area. The Sangali district, in general, can be categorised as a low erosion potential district (0-5 t.ha^-1.yr^-1). The generated information can be utilised for the implementation of soil and water management and conservation measures in the western part of Sangli district, where there is a large area under the forest and agricultural land.