JGIS  Vol.7 No.2 , April 2015
Detection and Mapping of Water Quality Variation in the Godavari River Using Water Quality Index, Clustering and GIS Techniques
ABSTRACT
The objective of this research is to develop a tool for planning and managing the water quality of River Godavari. This is achieved by classifying the pollution levels of Godavari River into several categories using water quality index and a clustering approach that ensure simple but accurate information about the pollution levels and water characteristics at any point in Godavari River in Maharashtra. The derived water quality indices and clusters were then visualized by using a Geographical Information System to draw thematic maps of Godavari River, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Godavari River. This also provides an effective overview of those spots in the Godavari River where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment of the State’s water quality monitoring network. Three significant groups (less polluted, moderately and highly polluted sites) were detected by Cluster Analysis method. The results of Discriminant Analysis revealed that five parameters i.e. pH, Dissolved Oxygen (DO), Faecal Coliform (FC), Total Coliform (TC) and Ammonical Nitrogen (NH3-N) were necessary for analysis in spatial variation. Using discriminant function developed in the analysis, 100% of the original sites were correctly classified.

Cite this paper
Gupta, I. , Kumar, A. , Singh, C. and Kumar, R. (2015) Detection and Mapping of Water Quality Variation in the Godavari River Using Water Quality Index, Clustering and GIS Techniques. Journal of Geographic Information System, 7, 71-84. doi: 10.4236/jgis.2015.72007.
References
[1]   Central Pollution Control Board, Evaluation of Operation and Maintenance of Sewage Treatment Plants in India (2007). http://www.cpcb.nic.in

[2]   Central Pollution Control Board, Annual Report (2008-2009).
http://cpcb.nic.in/upload/AnnualReports//AnnualReport_37_ANNUAL_REPORT-08-09.pdf

[3]   Central Pollution Control Board, Environmental Atlas of India (2001) New Delhi.

[4]   Bierman, P., Lewis, M., Ostendorf, B. and Tanner, J. (2011) A Review of Methods for Analyzing Spatial and Temporal Patterns in Coastal Water Quality. Ecological Indicators, 11, 103-114.
http://dx.doi.org/10.1016/j.ecolind.2009.11.001

[5]   Einax, J.W., Truckenbrodt, D. and Kampe, O. (1998) River Pollution Data Interpreted by Means of Chemometric Methods. Microchemical Journal, 58, 315-324. http://dx.doi.org/10.1006/mchj.1997.1560

[6]   Gazzaz, N.M., Yusoff, M.K., Ramli, M.F., Aris, A.Z. and Juahir, H. (2012) Characterization of Spatial Patterns in River Water Quality Using Chemometric Pattern Recognition Techniques. Marine Pollution Bulletin, 64, 688-698. http://dx.doi.org/10.1016/j.marpolbul.2012.01.032

[7]   Guler, C., Thyne, G.D., McCray, J.E. and Turner, K.A. (2002) Evaluation of Graphical and Multivariate Statistical Methods for Classification of Water Chemistry Data. Hydrogeology Journal, 10, 455-474. http://dx.doi.org/10.1007/s10040-002-0196-6

[8]   Gupta, I., Dhage, S., and Kumar, R. (2009) Study of Variations in Water Quality of Mumbai Coast through Multivariate Analysis Techniques. Indian Journal of Marine Sciences, 38, 170-177.

[9]   Gupta, I., Salunkhe, A., Rohra, N. and Kumar, R. (2013) Chemometrics Data Analysis of Marine Water Quality of Maharashtra, West Coast of India. Indian Journal of Geo Marine Sciences, 42, 97-105.

[10]   Kovacs, J., Kovacs, S., Magyar, N., Tanos, P., Hatvani, I.G. and Anda, A. (2014) Classification into Homogeneous Groups Using Combined Cluster and Discriminant Analysis. Environmental Modeling & Software, 57, 52-59. http://dx.doi.org/10.1016/j.envsoft.2014.01.010

[11]   Santos-Roman, M.D., Warner, S.G. and Scatena, F. (2003) Multivariate Analysis of Water Quality and Physical Characteristics of Selected Watershed in Puerto Rico. Journal of the American Water Resources Association, 829-839. http://dx.doi.org/10.1111/j.1752-1688.2003.tb04408.x

[12]   Xu, H.S., Xu, Z.X., Wu, W. and Tang, F.F. (2012) Assessment and Spatiotemporal Variation Analysis of Water Quality in the Zhangweinan River Basin, China. Procedia Environmental Sciences, 13, 1641-1652. http://dx.doi.org/10.1016/j.proenv.2012.01.157

[13]   Zeng, X. and Rasmussen, T.C. (2005) Multivariate Statistical Characterization of Water Quality in Lake Lanier, Georgia, USA. Journal of Environmental Quality, 34, 1980-1991.
http://dx.doi.org/10.2134/jeq2004.0337

[14]   Abbasi, S.A. (2002) Water Quality Indices State-of-the-Art, Pondicherry University, Centre for Pollution Control & Energy Technology, Pondicherry.

[15]   Nemeth, T., Szabo, J., Pasztor, L. and Bakacsi, Z. (2002) Elaboration of a Complex GIS Application in a Catchment Area. Water Science and Technology, 45, 133-140.

[16]   Shaban, M., Urban, B., El-Saadi, A. and Faisal, M. (2010) Detection and Mapping of Water Pollution Variation in the Nile Delta Using Multivariate Clustering and GIS Techniques. Journal of Environmental Management, 91, 1785-1793. http://dx.doi.org/10.1016/j.jenvman.2010.03.020

 
 
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