Modeling soil erosion severity and prioritization of erosion-prone areas in Takacha watershed, Southern Ethiopia

Abstract

Soil erosion is a major form of land degradation with serious environmental and socioeconomic impacts, particularly on agricultural sustainability. Thus, soil erosion risk assessment is crucial to inform policymakers and support effective mitigation measures. This study assessed soil erosion by using primary and secondary data with Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information Systems (GIS). Primary data were collected through field observations and ground-truth data collection across the study area to support the assessment and validation of land use/land cover and soil erosion-related parameters. Secondary data sources were utilized to model the physical parameters, including topography, rainfall erosivity, soil erodibility, land use/land cover, slope length and steepness, and conservation-support practices. rainfall erosivity (R) was derived from long-term rainfall data obtained from the National Meteorological Agency of Ethiopia, soil erodibility (K) from national soil maps, topographic factors (LS) from a digital elevation model (DEM), and cover-management (C) from land use/land cover data generated from 30 m resolution satellite imagery, while support practice (P) was assigned based on existing land management practices and slope classes. The findings revealed considerable spatial variability in erosion rates, with annual soil loss ranging from 0.0 to 265.3 ton ha−1 yr−1and an average of 31.5 ton ha−1 yr−1. Severity classifications revealed that 20.7% of the watershed experienced low erosion, 65.3% faced moderate erosion, 9.5% experienced high erosion, and 4.5% experienced very high erosion. These results illustrate that, although the majority of the watershed is relatively stable, certain zones are at high risk of erosion, necessitating urgent intervention. This highlights the need for targeted conservation strategies in vulnerable areas to combat ongoing land degradation and promote sustainable agricultural practices. Future studies should consider long-term monitoring and more detailed soil assessments to enhance understanding.