Soil loss modeling by blending RUSLE with GIS and remote sensing under land use/land cover change and climate change scenarios: the case of Qelem Wolega, Ethiopia

The primary objective of this study was to estimate soil loss in the Kellem Wolega Zone of Ethiopia under various land use and land cover change (LULCC) and climate change scenarios. To achieve this, the Revised Universal Soil Loss Equation (RUSLE) model was integrated with geographic information systems (GIS) and remote sensing techniques to calculate annual soil loss. The land cover analysis involved supervised image classification using the maximum likelihood technique in ERDAS IMAGINE 2014, utilizing Landsat 4-5TM data from 1994 and 2009, as well as Landsat 8 OLI data from 2023. Climate projections were derived from CMIP6 Global Circulation Models (GCMs) via the Copernicus Climate Data Store, specifically focusing on the SSP2-4.5 and SSP5-8.5 Shared Socioeconomic Pathways. Using observed rainfall data from 1995 to 2014 provided by the Ethiopian Meteorological Institute as a baseline, future precipitation patterns for the study area were projected and bias-corrected using CMhyd software. Under current land use and climatic conditions, the study identified a mean soil loss of 55.9 tons per hectare per year, totaling 62,670,446 tons across the 981,718-hectare study area. Furthermore, the analysis indicates that under the climate change scenarios of SSP2-4.5 and SSP5-8.5, the mean annual soil loss is projected to increase significantly to 98.4 and 104.4 tons per hectare per year, respectively, by the year 2037.