Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)

Abstract

Abstract Water quality monitoring programs are indispensable for developing water conservation strategies, but elucidation of large and random datasets generated in these monitoring programs has become a global challenge. Rapid urbanization, industrialization and population growth pose a threat of pollution for the surface water bodies of the Assam, a state in northeastern India. This calls for strict water quality monitoring programs, which would thereby help in understanding the status of water bodies. In this study, the water quality of Baralia and Puthimari River of Assam was assessed using cluster analysis (CA), information entropy, and principal component analysis (PCA) to derive useful information from observed data. 15 sampling sites were selected for collection of samples during the period May 2016- June 2017. Collected samples were analysed for 20 physicochemical parameters. Hierarchal CA was used to classify the sampling sites in different clusters. CA grouped all the sites into 3 clusters based on observed variables. Water quality of rivers was evaluated using entropy weighted water quality index (EWQI). EWQI of rivers varied from 61.62 to 314.68. PCA was applied to recognise various pollution sources. PCA identified six principal components that elucidated 87.9% of the total variance and represented surface runoff, untreated domestic wastewater and illegally dumped municipal solid waste (MSW) as major factors affecting the water quality. This study will help policymakers and managers in making better decisions in allocating funds and determining priorities. It will also assist in effective and efficient policies for the improvement of water quality.