GIS-based soil loss estimation using revised universal soil loss equation


  • Ekundayo Adesina
  • Oluibukun Ajayi
  • Joseph Odumosu
  • Abel Illah


Soil Erosion Estimation, GIS, RUSLE, Remote Sensing, Digital Elevation Models


Soil loss estimation plays a vital role in the management and conservation of land and water resources, offering vital insights for watershed-level development in various regions. This study focuses on the development of a soil loss model for Bosso Local Government Area in Minna, Nigeria, utilizing the Revised Universal Soil Loss Equation (RUSLE). Integration of Landsat images, Digital Elevation Models (DEM), rainfall and precipitation records, and soil erodibility factors was employed to estimate the average annual soil erosion within the study area. The individual parameters of the RUSLE model were integrated into the ArcGIS environment using the raster calculator in the Arc toolbox. The results reveal that an alarming 6672.83 tonnes per hectare per year of soil are lost annually in the study area. This rate of soil erosion raises concerns about the sustainability of agricultural practices in the study area. The findings underscore a critical absence of conservation practices or plans to combat and mitigate soil erosion in the region. In light of these findings, it is imperative that local government authorities, in collaboration with various ministries, take immediate action to promote and enforce conservation measures aimed at combating soil erosion within the area.