Statistical modeling of groundwater quality for source and ionic relationships: A case study for drinking water quality

A study was conducted to check the ground water quality of the University of Engineering and Technology (UET) campus, Lahore during October 13, 2014 to November 10, 2014. For this purpose grab samples were collected from four tube wells and eight end users for five weeks. These samples were analyzed for chloride (Cl^-), total dissolve solids (TDS), fluoride (F^-), pH, electrical conductivity (EC) and heavy metals (Cr, Pb, Ni, Fe) using prescribed methods and Atomic Absorption Spectrophotometer, respectively. Statistical tools were used for the source and correlation of ground water quality. Symmetrical (Cl^-, pH, EC, F^-, TDS, Ni, Fe) and non-symmetrical (Cr, Pb) distribution was observed. The Spearman and Pearson correlation matrix showed a correlation among heavy metals and physical parameters. Analysis of Variance (ANOVA) results also supported this correlation. The Principal Component Analysis (PCA) and the Cluster Analysis (CA) data identified four sources of chemical species in ground water, i.e. landfill leachates, emissions from vehicles, seepage of industrial emissions and tanneries wastewater, which enhanced the levels of heavy metals contamination in groundwater. Enrichment factor (EF) also indicated anthropogenic activities for the elevated levels of heavy metals in the ground water. The mean concentration of Cr (0.52 mg L^-1), Pb (0.08 mg L^-1) and Ni (0.08 mg L^-1) were higher than the permissible values while that of Fe was within permissible limit for drinking purposes.