Assessment of river water quality in Pearl River Delta using multivariate statistical techniques

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• 作者：Xiaoyun Fan ; Baoshan Cui ; ^{cuibs67@yahoo.com} ; ^{cuibs@bnu.edu.cn} ; Hui Zhao ; Zhiming Zhang ; Honggang Zhang
• 关键词：Water quality ; principal component analysis ; cluster analysis ; Pearl River Delta
• 刊名：Procedia Environmental Sciences
• 出版年：2010
• 出版时间：2010
• 年：2010
• 卷：2
• 期：Complete
• 页码：1220-1234
• 全文大小：1320 K

文摘

The Pearl River Delta (PRD) region is one of the most industrialized areas in China, and the river water is increasingly deteriorated due to anthropogenic pollution from the rapid economic development. Principal component analysis (PCA) and cluster analysis (CA) were used to identify characteristics of water quality and to assess water quality spatial pattern in this region. The results of PCA for three regions showed that the first four components of PCA analysis showed 85.52 % and 89.25 % of the total variance in the data sets of North River region and West River region, respectively, the first three components showed 84.63 % of variance for data set of East River region. Results of CA based on the station score of PCA were that stations of North River region, East River region and West River region were grouped into four, three and four clusters, respectively corresponding to severe pollution, moderate pollution, light pollution (except for East River region) and good water quality, which indicated the similarity and dissimilarity of the river water quality. Since, the results suggest that PCA and CA techniques are useful tools for assessment of water quality and management of water resources.