Abstract
Since the river is inevitable for living, the importance of the management of water quality cannot be overemphasized. Therefore, reliable monitoring programs which reflect the spatial and temporal variations have to be set, but usually the water quality data are composed of vast amount of data matrix. Multivariate statistical techniques including factor analysis, cluster analyses, and principal component analysis known as suitable tools for obtaining consequentially reduced data and interpreting various parameters, are used in this study to provide an appropriate tool for analysis of water quality. The purpose of this study is to establish structural data set for better understanding of water qualities in the Nakdong River watershed systemically using multivariate statistical techniques which can provide simpler but clearer explanations without losing important information.
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Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W., Sharpley, A.N., and Smith, V.H. (1998). “Nonpoint pollution of surface waters with phosphorus and nitrogen.” Ecol. Appl., Vol. 8, pp. 559–568.
Chapman, D. (1992). Water quality assessment, In: Champman, D. (ED.), on behalf of UNESCO, WHO and UNEP, Champman & Hall, London.
Dixon, W. and Chriswell, B. (1996). “Review of aquatic monitoring program design.” Water Res., Vol. 30, pp. 1935–1948.
Eder, B.K., Davis, J.M., and Bloomfield, P. (1994). “An automated classification scheme designed to better elucidate the dependence of ozone on meteorology.” J. Appl. Meteorol., Vol. 33, pp. 1182–1199.
Helena, B., Pardo, R., Vega, M., Barrado, E., Fernandez, J.M., and Fernandez, L. (2000). “Temporal evolution of groundwater composition in an alluvial (Pisuerga river, Spain) by principal component analysis.” Water Res., Vol. 34, pp. 807–816.
Jarvie, H.P., Whitton, B.A., and Neal, C. (1998). “Nitrogen and phosphorus in east-coast British rivers: speciation, sources and biological significance.” Sci. Tot. Environ., Vol. 210/211, pp. 79–109.
Liu, C.W., Lin, K.H., and Kuo, Y.M. (2003). “Application of factor analysis in the assessment of ground water quality in a blackfoot disease area in Taiwan.” Sci. Tot. Environ., Vol. 313, pp. 77–89.
Panda U.C., Sundaray, S.K., Rath, P., Nayak, B.B., and Bhatta, D. (2006). “Application of factor and cluster analysis for characterization of river and estuarine water systems — A case study: Mahanadi River (India).” J. Hyd., Vol. 331, pp. 434–445.
Singh, K.P., Malik, A., Mohan, D., and Sinha, S. (2004). “Mutivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India) — a case study.” Water Res., Vol. 38, pp. 3980–3992.
UN (1992). Protection of inland waters against eutrophication, New York, ECE/ENVWA/26.
Vega, M., Pardo, R., Barrado, E., and Deban, L. (1998). “Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis.” Water Res., Vol. 32, pp. 3581–3592.
Voncina, D.B., Dobcnik, D., Novic, M., and Zupan, J. (2002). “Chemometric characterisation of the quality of river water.” Analytica. Chimica. Acta., Vol. 462, pp. 87–100.
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Han, S., Kim, E. & Kim, S. The water quality management in the Nakdong River watershed using multivariate statistical techniques. KSCE J Civ Eng 13, 97–105 (2009). https://doi.org/10.1007/s12205-009-0097-5
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DOI: https://doi.org/10.1007/s12205-009-0097-5