Groundwater quality assessment using chemometric analysis in the Adyar River, South India

Abstract

A multivariate statistical technique has been used to assess the factors responsible for the chemical composition of the groundwater near the highly polluted Adyar River. Basic chemical parameters of the groundwater have been pooled together for evaluating and interpreting a few empirical factors controlling the chemical nature of the water. Twenty-three groundwater samples were collected in the vicinity of the Adyar River. Box-whisker plots were drawn to evaluate the chemical variation and the seasonal effect on the variables. R-mode factor analysis and cluster analysis were applied to the geochemical parameters of the water to identify the factors affecting the chemical composition of the groundwater. Dendograms of both the seasons gives two major clusters reflecting the groups of polluted and unpolluted stations. The other two minor clusters and the movement of stations from one cluster to another clearly bring out the seasonal variation in the chemical composition of the groundwater. The results of the R-mode factor analysis reveal that the groundwater chemistry of the study area reflects the influence of anthropogenic activities, rock-water interactions, saline water intrusion into the river water, and subsequent percolation into the groundwater. The complex geochemical data of the groundwater were interpreted by reducing them to seven major factors, and the seasonal variation in the chemistry of water was clearly brought out by these factors. The higher concentration of heavy metals such as Fe and Cr is attributed to the rock-water interaction and effluents from industries such as tanning, chrome-plating, and dyeing. In the urban area, the Pb concentration is high due to industrial as well as urban runoff of the atmospheric deposition from automobile pollution. Factor score analysis was used successfully to delineate the stations under study with the contributing factors, and the seasonal effect on the sample stations was identified and evaluated.