Assessment of Pulsating Organic and Nutrient Load in a River System, Using Multivariate Statistical Techniques: A Case Study of the Mahanadi River in Odisha, India

Natural processes and the anthropogenic activities are the major source of surface water pollution. In recent years various statistical methods have been used to formulate environmental classification in river water systems. Multivariate statistical techniques, such as cluster analysis (CA), and principal component analysis (PCA)/factor analysis (FA) were applied for the assessment of organic and nutrient load in the Mahanadi river, Odisha (India). Agglomerative hierarchical cluster analysis (AHC) grouped sampling sites into three clusters, i.e., relatively less polluted (LP), moderately polluted (MP) and highly polluted (HP) sites, based on the similarity of water quality characteristics. Factor analysis/principal component analysis, applied to the data sets of the three different groups obtained from cluster analysis, resulted in three, two and one principal component (PC) respectively having Eigen value >1. The PCs obtained from factor analysis indicates that the increase in load of nutrients is mainly attributed to agriculture runoff, industrial effluents and regional anthropogenic activities. The magnitude of BOD with respect to total N and P demonstrates the intensity of organic pollution in the riverine water. Biplot between principal components establish the mode of association of parameters and their interrelationships for evaluating the water quality of the river system. This study represent the necessity and usefulness of multivariate statistical techniques for assessment of large and complex databases to extract better information about the water quality of surface water bodies, the design of sampling and analytical protocols and the effective measures to control/management of pollution load in the surface water.