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The quality of surface water is rapidly changing due to climatic variations, natural processes, and anthropogenic activities. The objectives of this study were to classify and analyze the surface water quality of 12 major rivers of Alberta on the basis of 17 parameters during the period of five years i.e., 2004-2008 using principal component analysis PCA, total exceedance model and clustering technique. Seven major principal components PCs with variability of about 89% were identified. These PCs were the indicators of watershed geology, mineralization and anthropogenic activities related to land use-cover. The seven dominant parameters revealed from the seven PCs were total dissolved solids TDS, true color TC, pH, iron Fe, fecal coliform FC, dissolved oxygen DO, and turbidity TUR. The normalized data of dominant parameters were used to develop a model for obtaining total exceedance. The exceedance values acquired from the total exceedance model were used to determine the patterns for the development of five clusters. The performance of the clusters was compared with the classes obtained in Canadian Water Quality Index CWQI. Cluster 1, cluster 2, cluster 3, cluster 4 and cluster 5 showed agreements of 85.71%, 83.54%, 90.22%, 80.74%, and 83.40% with their respective CWQI classes on the basis of the data for all rivers during 2004-2008. The water quality was deteriorated in growing season due to snow melting. This methodology could be applied to classify the raw surface water quality, analyze the spatio-temporal trends and study the impacts of the factors affecting the water quality anywhere in the world.


Alberta Rivers; Canadian Water Quality Index; Clustering; Geographic Information System; Pattern Recognition; Principal Component Analysis; River Water Quality

Cite this paper

T. Akbar, Q. Hassan and G. Achari -Clusterization of Surface Water Quality and Its Relation to Climate and Land Use-Cover,- Journal of Environmental Protection, Vol. 4 No. 4, 2013, pp. 333-343. doi: 10.4236-jep.2013.44040.

Autor: Tahir Ali Akbar, Quazi K. Hassan, Gopal Achari



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