Evaluation of groundwater artificial recharge potential in the western Huaibei Plain, China

To mitigate groundwater overexploitation and support the scientifically informed siting of artificial recharge infrastructure in the western Huaibei Plain, this study develops a multi-criteria evaluation framework for recharge suitability, focusing on the western portion of the Huaibei Plain. The framework integrates five hydrogeologically significant indicators: Groundwater table depth, saturated thickness of the primary aquifer, hydraulic conductivity, precipitation infiltration coefficient, and proximity to perennial rivers. Indicator weights were determined through a hybrid weighting strategy—combining the analytic hierarchy process, criteria importance through intercriteria correlation, and coefficient of variation methods—to balance subjective judgment with objective data-driven variance. These weights were spatially implemented using ArcGIS-based multi-criteria decision analysis to generate a continuous recharge suitability index map. The integrated weights derived from the hybrid approach are 0.222, 0.254, 0.173, 0.185, and 0.166 for the respective indicators. Recharge suitability was classified into four ordinal categories—high, moderate, low, and unsuitable—using the natural breaks optimization method. High and moderate potential zones collectively occupy 32.93% of the study area and are predominantly located in Funan, Qiaocheng, Guoyang, and Mengcheng counties—regions identified as priority candidates for artificial recharge project implementation. A sensitivity analysis confirms the stability and reliability of the zoning outcomes under parameter perturbation. By quantitatively identifying dominant controlling factors, delineating spatially explicit potential classes, and pinpointing priority implementation zones, this study establishes a transferable methodological framework. It directly supports sustainable groundwater management in the western Huaibei Plain and offers actionable guidance for optimizing recharge infrastructure placement. Moreover, the approach demonstrates broad applicability for recharge potential assessment and integrated water resources planning in hydrologically similar alluvial plain settings.