Soil Erosion Mapping and Severity Analysis Based on RUSLE Model on Welmel Catchments of Ganale-Dewa River Basin Bale Lowland South Eastern Ethiopia

Abstract

Soil erosion is a kind of environmental deterioration through decreased agricultural output, increased floods, and habitat loss, soil degradation has an impact on many people's livelihoods, either directly or indirectly. In many developing tropical nations throughout the world where soil and water conservation (SWC) planning and management initiatives are either ineffective or nonexistent, soil erosion is on the rise. Because there isn't precise scientific research that gives information, identifying locations that are susceptible to soil erosion is also insufficient. The Oromia area of Ethiopia, where the majority of livelihoods mainly rely upon agriculture, is home to the little-recognized watershed of Welmel. A thorough understanding of the spatial variability across various climatic zones, land uses, and soil erosion is crucial for the planning of successful SWC management approaches. Through the use of a geographic information system (GIS), remote sensing (RS), and numerous characteristics such as land uses, and climate, this study has attempted to identify prospective places in need of SWC techniques by undertaking a spatial modeling of soil erosion within the Welmel watershed's Genale Dawa basin. The revised universal soil loss equation (RUSLE), which was previously modified for Ethiopian circumstances, was utilized to predict potential soil loss after laboratory study and processing multiple input datasets in ArcGIS to get the requisite six RUSLE model input parameters. It made use of data from a digital elevation model (DEM) on interpolated rainfall erosivity (R), soil erodibility (K), plant cover (C), topography (LS), and conservation practices (P) from satellite pictures. The study demonstrates that the RUSLE using GIS taking into account various climates and land management practices provides a great advantage in that it enables one to spatially analyze multilayer data to identify areas that are susceptible to soil erosion and subsequently develop the be