Assessment of groundwater quality for drinking purposes using hybrid approaches standard weights, trapezoidal fuzzy number-AHP, water quality index and GIS: a case study of Chennai district, Tamil Nadu, India

Groundwater is a vital resource for human consumption and industrial activities. However, anthropogenic activities have become a major source of groundwater contamination, posing a significant environmental concern due to increasing pollution levels. Approximately 90% of the population in the study area depends on groundwater for domestic and other purposes. Therefore, maintaining groundwater quality is essential for ensuring safe drinking water and protecting public health. Accordingly, the present study focuses on Chennai District, Tamil Nadu, India. The analyzed groundwater quality parameters include total dissolved solids, nitrate, calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, fluoride, pH, and electrical conductivity. Parameter weights were determined using the Trapezoidal Fuzzy Number Analytic Hierarchy Process (TRFN-AHP) and standard weighting methods. The main objective of this study is to evaluate groundwater quality for drinking purposes using a hybrid approach standard weights, TRFN-AHP, Water Quality Index (WQI), and Geographic Information System (GIS). Spatial distribution maps of groundwater quality parameters and WQI were generated using the Inverse Distance Weighting (IDW) interpolation method in ArcGIS. The WQI values, ranging from 50 to 300, were classified into five categories: excellent, good, poor, very poor, and unsuitable for drinking purposes. The results based on standard weights revealed that 7.90% of the samples were classified as excellent groundwater quality, 65.82% as good groundwater quality, 21.73% as poor groundwater quality, 1.95% as very poor groundwater quality, and 2.60% as unsuitable for drinking purposes. Similarly, the TRFN-AHP method revealed that 7.10% of the samples were classified as excellent groundwater quality, 62.82% as good groundwater quality, 25.93% as poor groundwater quality, 0.70% as very poor groundwater quality, and 3.45% as unsuitable for drinking purposes. To evaluate predictive performance, Area Under the Curve (AUC) was used. The obtained AUC value was 0.76 for the WQI based on standard weights, whereas the AUC value for the TRFN-AHP-based WQI was 0.87, indicating high predictive accuracy. The results indicate that the TRFN-AHP approach demonstrated improved performance for groundwater quality assessment. Furthermore, the hybrid TRFN-AHP approach showed effectiveness in evaluating groundwater quality through the WQI framework. By incorporating uncertainty and expert judgment into the weighting process, the method provided a more comprehensive assessment of groundwater quality conditions. The predictive performance of the TRFN-AHP-based WQI suggests its potential to identify spatial variations in water quality under the investigated conditions. Therefore, the proposed method may serve as a useful decision-support tool for groundwater quality assessment, monitoring, and sustainable water resource management.