Optimization of conditioning factors for groundwater potential zonation using GIS-based single parameter and map removal sensitivity analysis in Alipurduar district of West Bengal, India

Groundwater potential zonation is crucial for sustainable groundwater resource management, especially in regions with high groundwater demand. This study presents a novel approach using GIS-based sensitivity analyses to optimize the causative factors of groundwater potential zones (GPZ) in the Alipurduar district, West Bengal, India. Twelve groundwater conditioning factors, including lithology, geomorphology, land use and land cover, lineament density, drainage density, slope, rainfall, topographic wetness index, normalized difference vegetation index, topographic position index, roughness, and curvature, were considered to prepare the GPZ. The analytical hierarchical process method was employed to calculate the corresponding normalized rates and weights for thematic layers. Thematic maps were accumulated using a weighted sum technique to produce the GPZ map, which was verified through overlay analysis with observed dug well data. The study also demonstrates the effectiveness of GIS-based single parameter and map removal sensitivity analysis in optimizing the conditioning factors used in groundwater potential zonation. Lithology was identified as the most influential parameter, with a mean effective weight of 45% and a mean variation of 1.6% in GPZ. The receiver operating characteristic curve exhibited a good prognostic accuracy of 81%. This research provides valuable recommendations for selecting appropriate conditioning factors for groundwater resource assessment and management. Moreover, it offers practical insights into groundwater resource assessment and management in data-scarce regions, showcasing the application of GIS technology in groundwater potential zonation.