Application of Multivariate Statistical Techniques in Determining the Spatial Temporal Water Quality Variation of Ganga and Yamuna Rivers Present in Uttarakhand State, India

Abstract

Primary monitoring of 18 water quality parameters for rivers Ganga and Yamuna of Uttarakhand State was carried out to study the seasonal variation of these parameters, identify potential sources of pollution, and clustering of monitoring stations with similar characteristics. Wilcoxon signed-rank test, Paired t test and multivariate statistical techniques—principal component analysis (PCA) and cluster analysis (CA) were used to analyse the collected data. Separate analyses were conducted for summer and winter periods. The Wilcoxon signed-rank test and paired t test revealed seasonal variability in the data set with high pollution levels during summer period as compared to winter period. The CA grouped 15 monitoring stations of river Ganga and 5 monitoring stations of river Yamuna into 2 clusters of similar characteristics. The PCA resulted in the identification of four major sources of pollution for river Ganga, and three for river Yamuna. The findings of the study provide useful information in interpretation of complex datasets and for water quality assessment, identification of pollution sources/factors and understanding of temporal and spatial variations of water quality for effective river water quality management.