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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    Title :

    The water quality management in the Nakdong River watershed using multivariate statistical techniques


    Contributors:
    Han, Suhee (author) / Kim, Eungseock (author) / Kim, Sangdan (author)

    Published in:

    Publication date :

    2009-03-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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