M. D. Anto Praveena

Objective: To assess groundwater pollution vulnerability in the Chennai Metropolitan Region using a fuzzy logic-based model integrated with Geographic Information System (GIS) tools, overcoming the limitations of conventional index-based approaches in handling uncertainty and diverse data types. Methods: Seven parameters, depth to water table, net recharge, soil texture, aquifer media, hydraulic conductivity, slope, and land use/land cover, were processed through triangular and trapezoidal fuzzy membership functions. The Mamdani inference method and expert-defined IF–THEN rules generated a continuous Vulnerability Index (VI) from 0 to 100, later classified into five vulnerability zones. The model’s performance was checked using nitrate data from 100 groundwater samples and evaluated with ROC analysis. Sensitivity analysis measured the influence of each parameter. Results: High and very high vulnerability zones, mainly along coasts, floodplains, and urban areas with shallow aquifers, aligned with nitrate hotspots, while inland crystalline regions showed low risk. ROC analysis (AUC ~0.93) showed high prediction accuracy, and sensitivity tests proved the fuzzy logic–GIS model was reliable for mapping groundwater contamination risk. Conclusion: Fuzzy logic–GIS integration is an effective, adaptable approach for groundwater vulnerability mapping in complex hydrogeological settings. The resulting map provides a spatially explicit decision-support tool for targeted land-use control, wastewater management, and nitrate pollution reduction, with applicability to other coastal urban aquifers.