SURFACE WATER QUALITY ASSESSMENT USING MULTIVARIATE STATISTICAL TECHNIQUE AND WATER QUALITY INDEX (WQI) MODELLING IN THE UPPER GANGA RIVER, INDIASATISH PRASAD, RIDHI SALUJA, VARUN JOSHI AND J.K. GARGAbstract Upper Ganga river, a Ramsar site, is under the immense stress from anthropogenic activities. In the present study, spatial/temporal variability in the surface water quality of the Upper Ganga river was assessed over two years (2016-2018) using multivariate statistical technique and Water Quality Index (WQI) modelling. For 144 samples from eight sampling sites representing the summer, postmonsoon and winter seasons, twelve water quality parameters were analysed. Also, 48 samples were analysed for five heavy metals from eight sampling sites representing the summer and postmonsoon season of 2017. Cluster Analysis (CA) assembled sampling sites into three groups depending on similitude between them, allocating sites to regions of low contamination (LC), moderate contamination (MC) and high contamination (HC), further demonstrating the need for additional monitoring stations (one each at LC and HC cluster). Principal component analysis (PCA) of three distinct groups derived four latent factors for LC and HC region and three for MC region explaining 80.22, 75.47 and 69.81% of the variance, respectively. DA demonstrated that all parameters except for BOD represent most of the temporal variation, while pH, Flow, BOD and chlorophyll-a contribute towards the majority of the spatial variation. WQI values of the river extended between 92.01 â 474.54 amid summer and 60.18 â 416.75 amid post-monsoon, and were classified as poor demonstrating that the river water for the most of the stretch is unfit for drinking. |