Mianyang City is located in the varied topographic areas of Sichuan Province in southwestern China and is characterized by a complex geological background. This area is prone to disasters and its varied topography is inconvenient for emergency water storage and supply. Groundwater is essential for alleviating the demand for water and post-disaster emergency water supply in this area. This study applied AHP to integrate remote sensing, geological and hydrological data into GIS for the assessment of groundwater potential, providing a plan for the rational exploitation of groundwater and post-disaster emergency water supply in the area. Nine factors, including the spring calibration related to groundwater, were integrated by AHP after multicollinear checks. As a result, the geology-controlled groundwater potential map was classified into five levels with equal intervals. All the results were validated using borehole data, indicating the following: the areas with yield rates of $<1\mathrm{t}/\mathrm{d}·\mathrm{m}$, 1–20 $\mathrm{t}/\mathrm{d}·\mathrm{m}$, and 20–400 $\mathrm{t}/\mathrm{d}·\mathrm{m}$ accounted for 2.66%, 36.1%, and 39.62%, respectively, whereas the areas with yield rates of 400–4000 $\mathrm{t}/\mathrm{d}·\mathrm{m}$ and $>4000\mathrm{t}/\mathrm{d}·\mathrm{m}$ accounted for only 20.88% and 0.75% of the overall area. The flexibility of this quick and efficient method enables its application in other regions with a similar geological background.

The Gannan region is situated in Ganzhou City, Jiangxi Province, China, and has a complicated geological background. Seasonal droughts significantly jeopardize the water security of the local population. Groundwater is essential to alleviate the region’s water needs. In this research, the groundwater potential (GWP) of the Gannan region was assessed using the Soil and Water Assessment Tool (SWAT) and the Analytical Hierarchical Process (AHP). The groundwater recharge and rainfall estimated by the SWAT model exhibited notable inconsistencies regarding their spatial distribution. Eight groundwater potential assessment factors (lithology, fault density, land use, slope, convergence index, drainage density, rainfall, and groundwater recharge) were constructed by integrating remote sensing, geological, and SWAT output data. Two GWP maps were constructed by an overlay analysis based on the obtained weights using the AHP, with the rainfall and groundwater recharge assigned the same weight to calculate the GWP with the other six factors separately. Each map was split into five classes: excellent, good, moderate, poor, and very poor. Data from 23 wells and 42 springs were collected to validate the two maps by correlation analysis between the GWP and flow rates of wells and springs. The correlation analysis result indicates that the GWP calculated by the recharge (R² = 0.8 and 0.74, respectively) is more accurate than the GWP calculated by the rainfall (R² = 0.21 and 0.48, respectively) and can provide a theoretical basis for groundwater management and exploration in the area.