<p>With the increasing risks of land and infrastructure degradation, modeling water erosion has become a crucial tool for identifying priority areas for effective land management. In this study, potential soil erosion risk (PSER) was mapped using a GIS-based approach combined with the Analytical Hierarchy Process (AHP), which facilitates decision-making through pairwise comparisons structured in a matrix, allowing the weighting of factors involved in the erosion process. Seven key factors—slope (SL), rainfall (RA), drainage density (Dd), fractional vegetation cover (FVC), land use/land cover (LU/LC), soil (SO), and lithology (LI)—were selected due to their decisive role in initiating, controlling, and accelerating water erosion processes. The integration of these factors within a GIS environment, using the weighted overlay method, enabled mapping and classification of PSER into four levels (very high, high, moderate, and low) across the Upper Ouergha Basin (UOB). The spatial distribution of PSER reveals a predominance of high and very high-risk classes, which account for 50.5% of the study area. These high-risk zones are likely to generate substantial sediment loads that may be transported toward downstream hydraulic infrastructures. Model evaluation using the ROC (Receiver Operating Characteristic) curve yielded an AUC (Area Under the Curve) of 0.82, indicating good predictive performance. This finding highlights the reliability of the adopted approach and confirms the relevance of the selected factors in capturing the spatial variability of PSER. The integration of these findings into state-led watershed planning programs could help reduce the rate of soil fertility degradation in agricultural lands. Moreover, it provides an effective tool for mitigating reservoir siltation, particularly given the strategic importance of dams in managing water resources during periods of both scarcity and excess.</p>