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Spatial and statistical assessment of groundwater quality in semi-urban Delhi; India using PCA and WQI
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DOI：10.3389/frwa.2026.1875214.png)
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Abstract
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An integrated statistical and geospatial assessment was conducted to investigate groundwater quality in the semi-urban areas of Delhi. Groundwater quality was evaluated using the Water Quality Index (WQI) derived from nine key physicochemical parameters. The analysis revealed that; with the exception of alkalinity; most parameters exceeded the permissible limits recommended by the Bureau of Indian Standards for drinking water. Spatial analysis of WQI demonstrated that nearly 76.0% of the study area (141.68 km2 out of 186.39 km2) was characterized by WQI values exceeding 100; indicating poor to very poor groundwater quality and rendering the water unsuitable for direct human consumption without appropriate treatment. The correlation matrix revealed strong positive correlations among sulphate; chloride; magnesium; hardness; and calcium; indicating that these parameters are likely controlled by similar geochemical processes and may originate from common natural or anthropogenic sources. Principal Component Analysis (PCA) identified three significant components that collectively accounted for 79.457% of the total variance in the dataset. Among these; PC1 explained 47.414% of the variance; followed by PC2 and PC3; which contributed 18.598 and 13.445%; respectively. These results demonstrate that a limited number of underlying factors effectively govern the hydrochemical characteristics of groundwater in the study area. Hierarchical Cluster Analysis (HCA); performed using SPSS version 16.0; grouped the physicochemical parameters into two distinct clusters according to their similarity patterns. The first cluster consisted of hardness and chloride; indicating a strong association and possible common source or controlling process. The second cluster comprised the remaining parameters; suggesting that they are influenced by related hydrogeochemical factors. This clustering pattern provides further evidence of the interrelationships among groundwater quality parameters and their governing geochemical processes.
Keywords:
geospatial analysis
groundwater quality
principal component analysis (PCA)
water quality index (WQI)
hierarchical cluster analysis (HCA)
hydrochemical characterisation
semi-urban Delhi
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