Youssouf Koussoube ¹, Issan Ki ^1,2, Noura Dahri ³, ¹ Universite Joseph KI-ZERBO, Burkina Faso, ² Universite Daniel OUEZZIN-COULIBALY, Burkina Faso, ³ University of Sfax, Tunisia

It is vital to map groundwater recharge potential if we are to manage water resources sustainably. This is particularly important in regions where hydrological stress is increasing. In this context, multi-criteria decision-making (MCDM) techniques that combine remote sensing and GIS have become valuable tools for spatial analysis and environmental assessment. Among these techniques, people use the Analytic Hierarchy Process (AHP) most widely. Saaty developed it in 1980. It has a structured approach to integrating multiple factors influencing recharge. However, the subjectivity involved in assigning criterion weights and defining class boundaries remains a major limitation, often leading to uncertainty in the resulting maps.To address this issue, the present study incorporates a Monte Carlo–based probabilistic approach into the AHP framework to quantify and reduce the influence of subjective judgments. This integration allows a more robust and objective evaluation of groundwater recharge potential by accounting for variability in expert opinions. Applied to the Niger Basin, the method demonstrates improved reliability in delineating areas with favourable recharge conditions, validated through piezometric data from observation wells. Overall, the AHP– Monte Carlo hybrid model enhances the credibility of recharge potential mapping by providing a more transparent and data-driven assessment of spatial uncertainty. These areas are located in the north and south of the basin, in the localities of Gorom Gorom, Dori, Bogandé, Gayérie and Diapaga.Furthermore, the AUC value of 0.757 recorded by the AHP model, compared to a slightly higher value of 0.763 recorded by the MC-AHP model, proves the superior performance of the latter.

Remote sensing and GIS, AHP method, Monte Carlo method, Recharge potential, Niger basin.