Integration of GIS and Remote Sensing with RUSLE Model for Estimation of Soil Erosion

Globally, soil erosion is a significant problem contributing to nutrient loss, water quality degradation, and sand accumulation in bodies. Currently, various climate factors are affecting the natural resources entire worldwide. Agricultural intensification, some other human impacts all contribute erosion, which issue. Management conservation efforts watershed can benefit from study. Modeling establish scientific accurate method calculate sediment output below variety of circumstances. The measured loss tolerance was compared risk (T value).In this study, GIS remote sensing techniques have been integrated with Revised Universal Soil Loss Equation (RUSLE) model estimate Mayurakshi river basin eastern India. To determine erosion-prone areas, rainfall, land use, cover maps, as well digital elevation (DEM), were used input. annual area estimated be 4,629,714.8 tons. Accordingly, study categorized into five severity classes: very low (40.92%), (49%), moderate (6.5%), high (2.4%) (1.18%) classes. rates ranged slight throughout majority region. section basin’s lower plain has discovered least affected by loss. results helpful management practices development program area.