Watershed Based Spatial Modeling of Soil Loss Using RUSLE Model, GIS and Remote Sensing Techniques: The Case of Gulufa Watershed, Dabus River Basin, West Ethiopia

Abstract

So il erosion is a serious environmental and long lasting problem resulting in both on-site and off-site effects that has political, environmental, economic and societal implications in Ethiopia as a country and is a common challenge for agricultural production. The aim of this study was to estimate annual soil loss using Revised Universal Soil Loss Equation (RUSLE) model within Geographic Information Systems (GIS) environment to quantify the actual soil loss of Gulufa watershed. Accordingly, rainfall data from rainfall stations, soil data from Dabus River basin digital soil map, slope steepness and length from Digital Elevation Model and Sentinel-2 image were used as input datasets to generate factor maps. Raster calculator was used to interactively calculate actual soil loss of these factors. The results showed that the actual annual soil loss ranges from 0 to 439.22 ton/ ha/ year with the mean annual soil loss of 21.24 ton/ha/yr. Based on annual soil loss rates, the area suffers from a low to moderate annual soil loss covered about 73.39% (8986.32 ha) whereas high to very severe soil loss covered about 26.6% (3258.15 ha) of the study area. Among the 13 sub watersheds, five (35.1%) were experienced annual soil loss more than the watershed’s mean (21.24 ton/ha/year) are given priority from 1-4 whereas eight sub watersheds soil loss (64.9%) were less than the mean which is given the last 5-6 ranks. The study demonstrates that Revised Universal Soil Loss Equation together with Geographic In formation Systems and remote sensing are useful tools to estimate soil loss over small areas. Th erefore, spatial modeling of soil loss and prioritization of proneness areas from high to very severe soil loss is recommended to be intervened soil and water conservation plan for the prioritized sub watersheds.