ABSTRACT
The principal component analysis (PCA) employs the correlation matrix approach that rearranges the ground water quality data in such a manner so as to better explore the structure or process of the underlying system controlling/affecting the water composition. Furthermore, the values of ground water quality parameters were standardized before employing the PCA. In order to understand the dominant factors influencing the ground water quality of the aquifer system in the area, unit circle plots of different pairs of the significant PCs were plotted. This chapter aims at providing an overview of conventional and modern techniques used for the assessment of ground water quality and identification of natural and anthropogenic sources of ground water contamination. Furthermore, it includes a case study in a semi-arid region of India where the proposed approach is demonstrated by applying a methodology for combining factor scores of the PCA with geographical information system-based geo-statistical modeling precisely.
