A hybrid modeling framework for groundwater contamination risk: Optimized AHP-DRASTIC and BME - Muyuan Lu; Yuan Liu; Guijian Liu; Guanyu Wang; Yongli Li; Peiwei Sun (Environmental Chemistry and Ecotoxicology)
The assessment of groundwater contamination risk is crucial, especially in regions like northern Anhui, where complex geological conditions and limited groundwater sources coexist. This study proposes a cost-effective approach integrating groundwater vulnerability and functional value to evaluate contamination risk. The AHP-DRASTIC model was optimized by incorporating the spatial distribution of fluoride (F−) and dissolved inorganic nitrogen (DIN), which enhanced its sensitivity to key pollutants. Results show that urban centers and industrial zones had high economic values, while urban peripheries and agricultural areas exhibited higher functional values. The southern and southwestern parts of Huai river basin and its upstream areas showed the lowest contamination risks, making them ideal candidates for prioritized protection. The Bayesian Maximum Entropy (BME) method was used to generate trend forecasts of potential contamination risks, effectively identifying high-risk zones, with areas of relatively high contamination risk accounting for over 15 %. Despite the influences of hydrogeological heterogeneity and pollutant diffusion patterns, the BME method improves the accuracy of high-risk zone recognition, offering a scientific basis for effective groundwater resource management, pollution control, and regional water resource protection.