Multivariate Statistical Analysis of Ground Water in the Vicinity of Mahad Industrial Area of Konkan Region, India

Multivariate statistical techniques are very useful to show the complex correlation among many objects. An attempt was made to study the physico-chemical parameters of groundwater using multivariate statistical techniques such as principal component analysis (PCA), factor analysis and hierarchical cluster analysis. In this study, data of 31 parameters for 10 sampling locations determined during monsoon, winter and summer season of June, 2006 – May, 2007. Water Quality Index (WQI) values were found to be increasing during the seasons and indicate the deterioration of groundwater quality in summer season. Component loading in PCA for the parameters indicated changes in the values with respect to seasons. This study reveals that the seasonal water quality parameter variations must be considered to evaluate the pollution load and effect of parameters on water quality because the parameter that is important in contribution of water quality for one season may not be important for other seasons. Cluster analysis demonstrates that the groundwater character changes significantly with seasons. Multivariate statistical analysis and determinations of WQI values are very useful in hydrochemical studies.