Assessment of groundwater quality in Karur block of Tamil Nadu using multivariate techniques: A case study

Abstract

In this case study, multivariate statistical techniques, such as principal component analysis, factor analysis and cluster analyses were applied for evaluation of temporal/spatial variations in the groundwater quality. These techniques were employed for the better interpretation of large complex water quality data set monitored in the four seasons from twenty five groundwater locations of Karur block, Tamil Nadu during the year 2012. The water samples were characterized for the physico-chemical parameters such as temperature, pH, total alkalinity, electrical conductivity, total hardness, calcium ions, magnesium ions, total dissolved solids, fluorides, chlorides and sulphates. The data obtained were subjected to principal component analysis (PCA) for simplifying its interpretation and to define the parameters responsible for the main variability in water quality variance. The results of principal component analysis evinced that all the parameters equally and significantly contributed to water quality variations in the study area in all the seasons. Hierarchical cluster analysis grouped twenty five sampling stations into three clusters (i.e.) relatively less polluted (LP), moderately polluted (MP) and highly polluted (HP) sites based on the similarity of water quality characteristics. The water quality index (WQI) of these groundwater samples ranged from 47 to 107, 53 to 96 and 45 to 94 in post-monsoon, summer and pre-monsoon seasons, respectively. This investigation revealed that the groundwater of the study area needs some degree of water treatment before consumption. Thus, this study demonstrates the usefulness of