Spatial Estimation of Soil Erosion Using RUSLE Modeling: the Case of kaffa Zone, South western Ethiopia

Abstract

This research was administered to spatially predict the soil loss rate of kaffa zone using model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using Sentinel-2A satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36264.5tons ha-1 year-1, respectively. The result also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified a slight, moderate, high and very high with values ranging 0 to 15 ,15 to50,50 to 200, and > 200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides great advantage to spatially analyze multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.

Advancing Soil Erosion Assessment: Application of Remote Sensing and Geospatial Techniques in Bulango Ulu Reservoir Basin

“…Integrating data-driven approaches, like as the Universal Soil Loss Equation (USLE) or the Revised Universal Soil Loss Equation (RUSLE), allows for a comprehensive assessment of soil erosion dynamics (10). Researchers have demonstrated the usefulness of these models in guiding the formulation of sustainable land management practices and soil erosion control measures (2,(11)(12)(13)(14)(15)(16)(17). As soil erosion continues to be a global concern, the adoption of these mathematical tools holds significant promise for fostering resilient ecosystems and safeguarding precious soil resources.…”