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http://dx.doi.org/10.17663/JWR.2019.21.3.215

Application of Multivariate Statistical Techniques to Analyze the Pollution Characteristics of Major Tributaries of the Nakdong River  

Park, Jaebeom (Daon Solution co., Ltd.)
Kal, Byungseok (Daon Solution co., Ltd.)
Kim, Seongmin (Nakdong River Environment Research Center, National Institute of Environmental Research)
Publication Information
Journal of Wetlands Research / v.21, no.3, 2019 , pp. 215-223 More about this Journal
Abstract
In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.
Keywords
Tributary; Correlation Analysis; Principal Component Analysis; Cluster Analysis;
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Times Cited By KSCI : 5  (Citation Analysis)
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