Soil erosion has become a critical environmental concern exacerbated through human activities and climate change challenges. Accurate modeling and evaluation of soil erosion susceptibility are essential for sustainable land management, particularly in arid and semi-arid areas. In this context, a study based on the Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) was conducted to assess the soil erosion risk in the Gab & egrave;s region (SE Tunisia). The integration of AHP approach and GIS techniques, will allow assessing and evaluating the lateral variation of the erosion vulnerability and to the identification of the main conditioning factors. Several geospatial databases from the Gab & egrave;s region were used, including precipitation, land cover, slope, elevation, drainage density, Normalized Difference Vegetation Index (NDVI), lithology, soil type, and soil roughness, to define the dominant factors affecting soil erosion. The primary contributors to erosion vulnerability obtained using the AHP methodology correspond to slope, elevation, and soil depth, with percentage contributions of 19%, 18%, and 15%, respectively. The combination of AHP and GIS methodologies illustrated a final map showing the lateral variation of the erosion risk, considering that 63% of the Gab & egrave;s region presented a moderate risk and 37% a high to very high erosion risk. The spatial distribution of erosion risk indicates that insufficient rainfall, limited vegetation cover, and soil texture are significant contributing factors, particularly associated with inadequate soil conservation practices. To ensure model performance, validation was performed with soil organic carbon (SOC) distribution as an erosion-resistance proxy, indicating a significant negative correlation between SOC levels and erosion intensity. Additionally, the AHP-GIS model displayed strong predictive accuracy, with an AUC value of 0.88, confirming its resilience. This study demonstrated the effectiveness of AHP and GIS methodologies for soil erosion risk assessment, particularly in arid regions, offering valuable insights for targeted land management strategies focused on soil conservation and natural resource sustainability.Graphical AbstractThis study proposed a robust methodological framework for assessing soil susceptibility to erosion by combining multisource remote sensing, GIS analysis, and advanced decision-making approaches. The integration of high- resolution optical and radar satellite data, digital elevation models (DEM), climatic parameters, and field observations enables the extraction of key environmental indicators that influence erosion processes. The methodology is based on the analysis of ten determining factors, including slope, altitude, drainage density, precipitation, land use, NDVI, soil roughness, lithology, soil depth, and soil type. The application of the Analytic Hierarchy Process (AHP) within a multi-criteria decision-making (MCDM) framework allows the weighting of these variables and the generation of an erosion sensitivity map. To ensure the robustness of the model, cross-validation was carried out using a soil organic carbon (SOC) distribution map, which served as an independent reference for the assessment of erosive zones. This validation strengthens the reliability of the results and ensures consistency between theoretical modelling and ground reality. A major contribution of this study lies in the use of Sentinel-1 radar data, which enhances the characterization of soil roughness, a parameter often underestimated in erosion studies. The integration of SAR radar imagery improves the spatial accuracy of erosion risk mapping by reinforcing the detection of structural variations in soil. This evolving and reproducible methodological framework enables the effective monitoring of soil erosion, particularly in arid and semi-arid areas. The results provide a strategic decision- making tool for sustainable land management and the development of conservation policies tailored to the current environmental challenges.