Soil Erosion Risk Assessment Using Remote Sensing and GIS: An Integrated RUSLE-Frequency Approach - Ukah, Chinomso; Adieme, Mmelichukwu Oluebube; Ojukwu, Prosper Chinonso; Ebere, Nwobu Deborah; Udeh, Jennifer Ifeoma (PT. Teknologi Futuristik Indonesia, 2026)
Soil erosion is a major environmental challenge in tropical regions due to the interaction of intense rainfall, fragile soils, and unsustainable land use. This study assessed soil erosion risk in Agulu-Nanka, southeastern Nigeria, using an integrated GIS, remote sensing, Revised Universal Soil Loss Equation, and Frequency Ratio modeling approach to identify erosion hotspots and validate erosion susceptibility factors. It addresses the lack of localized, high-resolution soil erosion mapping and model validation using observed field erosion features in the study area despite existing regional erosion studies in Anambra State. Multi-source datasets were used to derive Revised Universal Soil Loss Equation factors and produce high-resolution erosion risk maps, which were validated using gully occurrence data. Results indicate extremely high rainfall erosivity (mean R = 110,562.09 MJ-MM/ha-hr-yr) and moderately to highly erodible soils (mean K = 1.39) as key erosion drivers. Steep slopes (LS > 4.00) more than doubled gully occurrence likelihood (FR = 2.21), while poorly vegetated and unmanaged areas recorded high susceptibility (FR > 2.0). Estimated soil loss reached 86.34 t/ha/yr, with high and very high-risk zones covering less than 4% of the area but posing significant threats to land productivity and infrastructure. The study confirms the multi-factorial nature of erosion in Agulu-Nanka and demonstrates the effectiveness of the RUSLE-FR framework for hotspot identification and evidence-based land use planning.