Estimation of soil erosion using revised universal soil loss equation (RUSLE) and GIS in the Surma watershed, Omo Basin, Ethiopia
摘要
Soil erosion is a critical environmental issue, particularly in developing regions like Ethiopia, where agricultural practices and deforestation exacerbate land degradation. The Surma watershed in the Omo Basin is vital for local agriculture and biodiversity, yet comprehensive studies on soil erosion using advanced modeling techniques are limited. This study aims to estimate soil erosion in the Surma watershed using the GIS-based Revised Universal Soil Loss Equation (RUSLE) model, identifying critical areas susceptible to erosion and providing recommendations for land management. Data collection involved remote sensing imagery, topographic maps, and local meteorological data to assess key RUSLE parameters, including rainfall erosivity, soil erodibility, slope length, slope steepness, cover management, and supporting practices. GIS software was employed to analyze spatial data and compute soil loss across the watershed. The findings reveal a concerning distribution of soil erosion rates across the Surma watershed. Approximately 26.9% of the area experiences low erosion rates (0–5 ha−1 year−1), while 19.6% faces moderate erosion (5–10 ha−1 year−1). However, significant portions of the study area are classified under higher severity levels, with 15.6% experiencing high erosion (10–20 ha–1 year–1), 10.2% in the very high category (20–30 ha–1 year–1), and 10.9% classified as severe (30–45 ha–1 year–1). Alarmingly, 7% of the watershed is classified as extreme severe (>60 ha–1 year–1), indicating urgent attention is needed for soil conservation and management strategies to mitigate further degradation. The study demonstrates the value of the GIS-based RUSLE model for soil erosion assessment in the Surma watershed. It is recommended to implement soil conservation practices, enhance vegetation cover, and develop community awareness programs to mitigate soil erosion in the region. Future research should focus on long-term monitoring and adaptive management strategies to ensure sustainable land use.