Assessment of Groundwater Potential Zones by Integrating Hydrogeological Data, Geographic Information Systems, Remote Sensing, and Analytical Hierarchical Process Techniques in the Jinan Karst Spring Basin of China

Abstract

Groundwater management in the Jinan Spring basin is hampered by its complex topography, overexploitation, and excessive urbanisation. This has led to springs drying up during dry seasons and a decrease in discharge in recent years. GIS and the AHP were employed to delineate groundwater potential zones using eight thematic layers: slope, geology, lineament density, topographic wetness index (TWI), rainfall, soil, drainage density, and land use/land cover (LULC). The model’s accuracy was assessed by comparing the findings to basin groundwater observation well data. We found that 74% of the observations matched the projected zoning. Further validation utilising the receiver operating characteristic (ROC) curve gave an AUC of 0.736. According to the study, 67.31% of the land has a good GWPZ, 5.60% has a very good one, 27.07% is medium, and 0.03% is low. Heavy rains throughout the rainy season raise water levels. Dry weather lowers water levels. This study’s conclusions will protect groundwater from climate change. Integrating hydrogeological data, GIS, remote sensing, and AHP approaches maximises data use, improves groundwater potential zone delineation, and promotes sustainable groundwater resource management decision making. This integrated method can help land use planners, hydrologists, and policymakers find optimal locations for water supply projects, establish groundwater management techniques, and reduce groundwater risks.