Spatial Estimation of Soil Erosion Using RUSLE Model: A Case Study of Sangareddy Telangna State, India

Abstract

Soil erosion is a major environmental challenge that affects agricultural productivity, water quality, and land management. To address this issue, accurate estimation and spatial mapping of soil erosion rates are essential for effective soil conservation planning and management. This study focuses on utilizing the Revised Universal Soil Loss Equation (RUSLE) model to estimate and map soil erosion rates in the Sangareddy district of Telangana State, India. The RUSLE model integrates several factors contributing to soil erosion, including rainfall erosivity, soil erodibility, slope length and steepness, cover management factor, and conservation practices. These factors were derived from geospatial datasets, including rainfall records, soil characteristics, topographic data, land use/land cover maps, and conservation practices information. By applying the RUSLE model, the study estimates the average annual soil erosion rates across the Sangareddy district. The spatial distribution of soil erosion is then mapped using geographic information system (GIS) techniques, providing valuable insights into the area’s most susceptible to erosion. These findings can inform decision-makers and land managers in prioritizing and implementing appropriate soil conservation strategies to mitigate erosion and protect valuable soil resources. The spatial estimation of soil erosion using the RUSLE model provides a scientific basis for land-use planning, conservation program implementation, and policy formulation to promote sustainable land management practices. It highlights the need for effective erosion control measures, such as contour farming, terracing, afforestation, and appropriate land use practices, in order to minimize soil erosion and preserve the soil quality in Sangareddy and similar regions.