Assessment of water quality using multivariate analysis�a case study on the Brahmaputra River, Assam, India

Chemical composition of river water is vital to assessment of water quality for irrigation, agriculture and domestic usage. Chemical attributes of riverine water primarily governed by natural weathering of rocks have become overshadowed by increasing range of anthropogenic activities. Progressive pollution of the river waters are critical as rivers in floodplain zones recharge ground water; a vital source of drinking water in India. The degree of impact of the anthropogenic activities within the surface waters of the developing countries has expanded significantly amid the past decades. Hence identification and quantification of natural as well as anthropogenic impact and understanding the source of contaminant is fundamental. In addition continuous monitoring of river water quality is required in order to maintain freshwater assets. The Brahmaputra River is the lifeline of Assam. People residing along its bank directly or indirectly are heavily dependent on the river for their livelihood. Majority of the population in the region is dependent on an agricultural economy. In the present study different multivariate statistical techniques such as cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) were applied for evaluation of spatial and temporal variations of water quality of the Brahmaputra River for two years (2011�2014) by monitoring nine sampling sites from upstream to downstream along the Assam stretch. The present study highlights the usefulness and need of multivariate statistical assessment of the database in identification of main process that influence the water quality of the river and probable source of contamination.