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Assessment of water quality in a subtropical alpine lake using multivariate statistical techniques and geostatistical mapping: a case study.

Liu WC, Yu HL, Chung CE - Int J Environ Res Public Health (2011)

Bottom Line: In order to understand the underlying physical and chemical processes as well as their associated spatial distribution in YYL, this study analyzes fourteen physico-chemical water quality parameters recorded at the eight sampling stations during 2008-2010 by using multivariate statistical techniques and a geostatistical method.Results show that four principal components i.e., nitrogen nutrients, meteorological factor, turbidity and nitrate factors, account for 65.52% of the total variance among the water quality parameters.The spatial distribution of principal components further confirms that nitrogen sources constitute an important pollutant contribution in the YYL.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil Disaster Prevention Engineering, National United University, Miao-Li 36003, Taiwan. w933821@hotmail.com

ABSTRACT
Concerns about the water quality in Yuan-Yang Lake (YYL), a shallow, subtropical alpine lake located in north-central Taiwan, has been rapidly increasing recently due to the natural and anthropogenic pollution. In order to understand the underlying physical and chemical processes as well as their associated spatial distribution in YYL, this study analyzes fourteen physico-chemical water quality parameters recorded at the eight sampling stations during 2008-2010 by using multivariate statistical techniques and a geostatistical method. Hierarchical clustering analysis (CA) is first applied to distinguish the three general water quality patterns among the stations, followed by the use of principle component analysis (PCA) and factor analysis (FA) to extract and recognize the major underlying factors contributing to the variations among the water quality measures. The spatial distribution of the identified major contributing factors is obtained by using a kriging method. Results show that four principal components i.e., nitrogen nutrients, meteorological factor, turbidity and nitrate factors, account for 65.52% of the total variance among the water quality parameters. The spatial distribution of principal components further confirms that nitrogen sources constitute an important pollutant contribution in the YYL.

Show MeSH
Spatial distribution of second principle component by ordinary kriging method on the measured data of February 14, 2009.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC3118881&req=5

f7-ijerph-08-01126: Spatial distribution of second principle component by ordinary kriging method on the measured data of February 14, 2009.

Mentions: The general characteristics can be seen in Figure 7 in which a clear increasing trend from south to north of principle component is shown.


Assessment of water quality in a subtropical alpine lake using multivariate statistical techniques and geostatistical mapping: a case study.

Liu WC, Yu HL, Chung CE - Int J Environ Res Public Health (2011)

Spatial distribution of second principle component by ordinary kriging method on the measured data of February 14, 2009.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3118881&req=5

f7-ijerph-08-01126: Spatial distribution of second principle component by ordinary kriging method on the measured data of February 14, 2009.
Mentions: The general characteristics can be seen in Figure 7 in which a clear increasing trend from south to north of principle component is shown.

Bottom Line: In order to understand the underlying physical and chemical processes as well as their associated spatial distribution in YYL, this study analyzes fourteen physico-chemical water quality parameters recorded at the eight sampling stations during 2008-2010 by using multivariate statistical techniques and a geostatistical method.Results show that four principal components i.e., nitrogen nutrients, meteorological factor, turbidity and nitrate factors, account for 65.52% of the total variance among the water quality parameters.The spatial distribution of principal components further confirms that nitrogen sources constitute an important pollutant contribution in the YYL.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil Disaster Prevention Engineering, National United University, Miao-Li 36003, Taiwan. w933821@hotmail.com

ABSTRACT
Concerns about the water quality in Yuan-Yang Lake (YYL), a shallow, subtropical alpine lake located in north-central Taiwan, has been rapidly increasing recently due to the natural and anthropogenic pollution. In order to understand the underlying physical and chemical processes as well as their associated spatial distribution in YYL, this study analyzes fourteen physico-chemical water quality parameters recorded at the eight sampling stations during 2008-2010 by using multivariate statistical techniques and a geostatistical method. Hierarchical clustering analysis (CA) is first applied to distinguish the three general water quality patterns among the stations, followed by the use of principle component analysis (PCA) and factor analysis (FA) to extract and recognize the major underlying factors contributing to the variations among the water quality measures. The spatial distribution of the identified major contributing factors is obtained by using a kriging method. Results show that four principal components i.e., nitrogen nutrients, meteorological factor, turbidity and nitrate factors, account for 65.52% of the total variance among the water quality parameters. The spatial distribution of principal components further confirms that nitrogen sources constitute an important pollutant contribution in the YYL.

Show MeSH