Spatial assessment of soil erosion using GIS-integrated RUSLE in the Wolaita zone, Ethiopia
Abstract
Soil requires focused management to ensure long-term productivity and ecological balance. The Revised Universal Soil Loss Equation (RUSLE) is an effective empirical model that, when combined with Remote Sensing (RS) techniques and Geographical Information Systems (GIS), enables the analysis of annual soil loss by integrating RUSLE factors and indices within the ArcGIS environment. In the current study region, limited attempts have been made to assess annual soil loss rates, identify erosion hotspots, and provide spatially explicit evidence to guide soil and water conservation measures. However, most inhabitants heavily depend on agriculture for survival. The RUSLE model was applied, integrating GIS and RS, to understand erosion rates and the spatial distribution of erosion intensity. The input datasets were acquired from diverse sources, including NASA POWER, FAO DSMW, USGS Earth Explorer, and the European Space Agency (ESA) LULC, and analyzed using ArcGIS 10.8.2 software. The finding unveiled that about 43,890.3 ha (9.77%), 30,388.14 ha (6.76%), and 1,459.17 ha (0.32%) of the study region experience high, very high, and severe soil erosion intensity, which requires effective conservation and management practices, including contour farming, terracing, check dams, vegetative barriers, crop rotation, mulching, agroforestry systems, and participatory watershed management. The annual soil erosion rate extends from 0.18 to 486 tons ha-1 year-1, with higher erosion intensity (46.09 to 486 tons ha-1 year-1) observed in the western portion of the study region. These areas are characterized by low vegetation cover, receiving higher rainfall, and a lack of effective support practices and cover management mechanisms. The findings offer insights into local erosion risk hotspots and support national initiatives in sustainable watershed management, climate resilience, and food security. Land managers, experts, and decision-makers can utilize the study results to develop the most effective long-term soil conservation and restoration plans.