Abstract
Kyeongan stream is one of the tributaries of the Paldang Reservoir which is the largest drinking water source in South Korea. It serves as one of the major contributors of pollution. In this study, the database obtained during the monitoring program was subjected to different multivariate statistical analyses (MVA) such as Cluster Analysis (CA) and Factor Analysis (FA) with a view to suggest a simplemethodological approach for analysis and interpretation of complex data sets. Using CA, data rendered a dendrogram grouping all the monitored streams into three statistically significant clusters (high pollution, moderate pollution and low pollution regions). Through CA, it is possible to design a future spatial sampling strategy in an optimal manner through reducing the number of sampling sites and cost without losing any significance of the outcome. FA for the three data sets evolved five VFs for LP and MP regions and four VFs for HP region. The eigenvalue is greater than 1, explaining 74.24, 76.84 and 78.25% of the total variance in respective water quality data sets. This included the organic pollution group (municipal and industrial effluents), nutrients group (agricultural runoff) and EC and solids (soil leaching and runoff process).
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References
Azzellino, A. et al. (2006). Combined use of the EPA-QUAL2E simulation model and factor analysis to assess the source apportionment of point and non point loads of nutrients to surface waters. Science of the Total Environment 371, 214–222.
Boyacioglu, H. (2006). Surface water quality assessment using factor analysis. WaterSA 32(3).
Clatworthy, J.D. et al. (2005). The use and reporting of cluster analysis in health psychology: A review. British Journal of Health Psychology 10, 329–358.
Eaton, A.D. et al. (2005). Standard Methods for the Examination of Water and Wastewater, 21st edn. APHA, AWWA and WEF.
Gupta, A.K. et al. (2005). Statistical analyses of coastal water quality for a port and harbour region in India. Environ. Monit. Assess. 102, 179–200.
Heir, J.F., Anderson, R.E., Tatham, R.L. and Black, W.L. (1995). Multivariate Data Analysis, Prentice-Hall, New Jersey.
Michlik-Acosta, L. (2005). Intervulnerability assessment: Shifting foci from generic indices to adaptive agents in assessing vulnerability to global environmental change: A pilot project in the Philippines. START.
Ouyang, Y. et al. (2006). Assessment of seasonal variations in surface water quality. Water Res. 40, 3800–3810.
Saffrean, K. (2001). Canadian Water Quality Guidelines for the Protection of Aquatic Life. CCME Water Quality Index 1, User’s Manual. Excerpt from Publication No. 1299, ISBN 1-96697-34-1.
San, O.M. et al. (2004). An Alternative extension of the k-means algorithm for clustering categorical data. Int. J. Appl. Math. Comput. Sci. 14(2), 241–247.
Shrestha, S. and Kazama, F. (2006). Assessment of surface water quality using multivariate statistical technique: A case study of the Fuji river basin, Japan. Envi. Modeling & Software 22, 464–475.
Singh, K., Malik, A. and Sinha, S. (2005). Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical technique: A case study. Ana. Chimica Acta 538, 355–374.
Yu, S., Shang, J., Zhao, J., Guo H. (2003). Factor analysis and dynamics of water quality of the Songhua Rover, Northeast China. Water Air Soil Pollt. 144, 159–169.
Zeng, X. and Rasmussen, T.C. (2005). Multivariate statistical characterization of water quality in Lake Lanier, Georgia, USA. J. Environ. Qual. 34, 1981–1991.
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Sevilla, J.B., Lee, C.H., Lee, B.Y. (2010). Assessment of Spatial Variations in Surface Water Quality of Kyeongan Stream, South Korea Using Multi-Variate Statistical Techniques. In: Sumi, A., Fukushi, K., Honda, R., Hassan, K. (eds) Sustainability in Food and Water. Alliance for Global Sustainability Bookseries, vol 18. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9914-3_5
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DOI: https://doi.org/10.1007/978-90-481-9914-3_5
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