Evaluation and Quantification of Pollution Caused by Open Drains in Ganges River Basin Using Multivariate Cluster Analysis
The colossal expansion and pace of global development have completely deteriorated the water quality of major river basins of the world such as Amazon, Ganges, Nile etc. Rivers have become receivers of wastewater discharged from industrial, agricultural and domestic sectors. Ganges river basin of India is considered as one of the heavily polluted river basin with 144 open drains entering into the river body without proper treatment. Therefore, monitoring and analysing the water quality of these drains and their sources is essential not only to suggest proper treatment procedures but also to ensure sustainability of the river ecosystem. The present study conducts an exhaustive quality analysis of 85 drains carrying both industrial and domestic sewage, either directly into river Ganges or indirectly through tributaries (Kali-East, Ram Ganga and Pandu) in ‘Haridwar to Kanpur’ stretch. Multivariate technique namely Principal Component Analysis (PCA) and Cluster Analysis (CA) have been employed using ‘Analyse it’ software to evaluate the intensity and sources of pollution. The methodology generates monoplots and two dimensional biplots to identify the relationships among pollutants and their sources. Finally, quality assessment of drains has been performed by calculating the water quality index of each drain, and sensitivity analysis is carried out to evaluate the effect of critical water quality parameters. Results direct the policy makers to identify the industries responsible for polluting the drains above critical levels and further measures are suggested to improve the deteriorating quality of drains.
Astel, A., Tsakovski, S., Simeonov, V., Reisenhofer, E., Piselli, S. and P. Barbieri (2008). Multivariate classification and modeling in surface water pollution estimation. Anal. Bioanal. Chem., 390: 1283-1292.
Bhutiani, R., Khanna, D.R., Kulkarni, D.B. and M. Ruhela (2016). Assessment of Ganga river ecosystem at Haridwar, Uttarakhand, India with reference to water quality indices. Applied Water Science, 6(2): 107-113.
Bora, M. and D.C. Goswami (2017). Water quality assessment in terms of water quality index (WQI): Case study of the Kolong River, Assam, India. Applied Water Sci., 7: 3125-3135.
CPCB (2013). Pollution Assessment: River Ganga. Central Pollution Control Board (CPCB), New Delhi, India.
CPCB (2016). Restoration/rejuvenation of River Ganga suggestions/proposals for phase-i, segment ‘b’ (Haridwar down to Kanpur down). Central Pollution Control Board (CPCB), New Delhi, India.
Das, P. and K.R. Tamminga (2012). The Ganges and the GAP: An Assessment of Efforts to Clean a Sacred River. Sustainability, 4: 1647-1668. doi:10.3390/su4081647
Jan, F.A., Ishaq, M., Ihsanullah, I. and S.M. Asimc (2010). Multivariate statistical analysis of heavy metals pollution in industrial area and its comparison with relatively less polluted area: A case study from the City of Peshawar and district Dir Lower. Journal of Hazardous Materials,
176: 609-616.
Lermontov, A., Yokoyama, L., Lermontov, M. and M.A.S. Machado (2009). River quality analysis using fuzzy water quality index: Ribeira do Iguape river watershed, Brazil. Ecological Indicators, 9(6): 1188-1197.
Pandey, J. and R. Singh (2015). Heavy metals in sediments of Ganga River: Up- and downstream urban influences. Applied Water Science, 7(4): 1669-1678. doi:10.1007/ s13201-015-0334-7
Rawat, M., Ramanathan, AL. and V. Subramanian (2009). Quantification and distribution of heavy metals from small-scale industrial areas of Kanpur city, India. Journal of Hazardous Materials, 172: 1145-1149.
Simeonova, P. and V. Simeonov (2007). Chemometrics to evaluate the quality of water sources for human consumption. Microchim. Acta, 156: 315-320.
Srinivas, R., Singh, A.P. and R. Sharma (2017). A scenario- based impact assessment of trace metals on ecosystem of river Ganges using multivariate analysis coupled with fuzzy decision-making approach. Water Resources Management, 31(13): 4165-4185.