Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

@article{Phung2015TemporalAS,
  title={Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.},
  author={Dung Phung and Cunrui Huang and Shannon Rutherford and Febi Dwirahmadi and Cordia Ming-Yeuk Chu and Xiaoming Wang and Minh Dat Nguyen and Nga Huy Nguyen and Cuong Manh Do and Trung Hieu Nguyen and T. A. Dinh},
  journal={Environmental monitoring and assessment},
  year={2015},
  volume={187 5},
  pages={229}
}
The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban… CONTINUE READING

10 Figures & Tables

Connections & Topics

Mentioned Connections BETA
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
The present study is an evaluation of temporal / spatial variations of surface water quality using multivariate statistical techniques , comprising cluster analysis ( CA ) , principal component analysis ( PCA ) , factor analysis ( FA ) and discriminant analysis ( DA ) .
All Topics