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Soil erosion within watersheds is a common phenomenon worldwide, and many scientific efforts have been made to address this problem. The Revised Universal Soil Loss Equation (RUSLE) model has been widely employed in soil erosion estimation. However, several studies have highlighted its limitations and the need to account for some key aspects of soil erosion which are not considered in the model. This study explores the potential of utilizing locally dominant soil erosion driving factors alongside the RUSLE model for soil erosion susceptibility assessment within the OIO watershed. Landsat 8 OLI image for the year 2020, DEM, soil data, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets coupled with field observed datasets were employed to derive these factors. They include soil loss, sediment yield, sediment transport index, and runoff. Numerical rankings that represent the level of contribution of each factor and their attributes to soil erosion within the watershed were generated using the Fuzzy Analytical Hierarchy Process (FAHP). Each factor was reclassified according to these rankings and overlaid using the GIS-based weighted overlay technique to model soil erosion within the OIO watershed. Finally, we employed a statistical combination of the modelled soil erosion map and Hydrological Response Unit (HRU) to assess erosion susceptibility within the watershed. Initial results from the study highlighted the variabilities in annual soil loss (min: &lt; 6.0 t ha −1  yr −1 , max: ≥ 58.0 t ha −1  yr −1 , mean: 13.55 t ha −1  yr −1 ) and identified areas with high predispositions to soil loss within the OIO watershed. The annual sediment yield of the entire OIO watershed ranged between ≤ 14.04 to 715.10 t ha −1 yr −1  with an annual average of 14.88 t ha −1 yr −1 . In addition, the sediment transport index and runoff volume for the OIO watershed range between 0.00–69.07 and 0.00–70.00 mm, respectively. Five erosion susceptibility levels were delineated: very slight, slight, moderate, severe, and severe. They occupied 65.00%, 24.43%, 7.69%, 2.63%, and 0.23% of the watershed, respectively. Accuracy assessment conducted using the Receiver Operating Curve (ROC) showed that the soil erosion susceptibility map has an AUC value of 0.86, indicating acceptable results. Our methodological approach improves the RUSLE model, especially regarding preliminary soil susceptibility assessment for watershed development under typical data-scarce conditions.

An improved multi-criteria decision analysis approach for watershed soil erosion susceptibility assessment