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One of the most pressing environmental issues of the 21st century is land degradation in fragile watersheds where acute sediment aggradation, erosion, and flooding have become everyday occurrences. Previous attempts to prioritise sub-watersheds have been plagued with uncertainty. Addressing this problem therefore requires identifying erosion-prone areas, specifically at the sub-watersheds level, and reducing the uncertainty of outcomes to a minimum. In this study, an ensemble of seven multi-criteria decision-making (MCDM) models was developed to prioritise the sub-watersheds of the Anambra Basin against erosion risk. These MCDM models, namely MOORA (multi-objective optimisation based on ratio analysis), GRA (grey relational analysis), CoCoSo (combined compromise solution), CODAS (combinative distance-based assessment), TOPSIS (a technique for order preference by similarity to ideal solution), COPRAS (complex proportional assessment), and VIKOR (VieKriterijumsko KOmpromisno Rangiranje), were coupled with the Analytical Hierarchical Process (AHP) and Geographic Information System (GIS) with 23 geomorphometric parameters to provide an integrated sub-watershed ranking. The accuracy of the models was tested using Spearman's rank correlation and geometric mean to compute a uniform sub-watershed ranking. The results indicate that sub-watershed H has the highest aggregate ranking across the MCDM models, making it the top priority for erosion mitigation projects. Furthermore, the model validation assessment shows that the MOORA and COPRAS models returned similar results with the aggregated ranks and possess the most significant rank correlation coefficients, indicating the highest predictive accuracy. This study can be utilised by decision-makers in data-sparse regions for sustainable watershed management in the face of erosion risks.

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