An Innovative Approach for Groundwater Quality Assessment with the Integration of Various Water Quality Indexes with GIS and Multivariate Statistical Analysis—a Case of Ujjain City, India

In India, a majority of the populace relies on groundwater for drinking. For this, the determination of groundwater quality (GWQ) is of great importance. The water quality index (WQI) is an effective technique that determines the suitability of water for drinking. In the present study, 54 groundwater samples consisting of eight physicochemical parameters were evaluated to assess water quality using four indexing methods: Numerow’s pollution index (NPI), Weighted Arithmetic Water Quality Index (WA WQI), Groundwater Quality Index (GWQI), and the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). A Geographic Information System (GIS) was employed to outline the spatial distribution maps of eight physicochemical parameters and WQI maps using the Inverse Distance Weighted (IDW) technique. Multivariate statistical analysis such as correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were used for the evaluation of large and complicated groundwater quality data sets in the study. The results of the WQI indicate that 43% (NPI), 96% (WAWQI), 74% (GWQI), and 94% (CCME WQI) of groundwater samples had poor to unsuitable drinking water quality. Using Karl Pearson’s correlation matrix, correlation analysis reveals a strong positive correlation of 0.9996 between EC and TDS. The application of PCA resulted in three major factors with a total variance of 72.5%, explaining the causes of water quality degradation. With the help of dendrogram plots, CA classifies eight groundwater parameters and 54 sampling locations into three major clusters with similar groundwater characteristics. According to the integrated approach of different water quality indexes with GIS, it is concluded that samples from wards 20, 44, and 47 are the most common and in the excellent-to-good category, and samples from wards 17, 34, and 43 are the most common and in the poor-to-very poor category. In view of the above, it is recommended to monitor the physicochemical parameters on a regular basis in order to safeguard groundwater resources and to prioritize management strategies in order to maintain the drinking quality of water.