An identification source of variation on the water quality pattern in the Malacca River basin using chemometric approach

被引:1
|
作者
Hua, Ang K. [1 ]
机构
[1] Univ Putra Malaysia, Seri Kembangan, Malaysia
关键词
hierarchical cluster analysis; discriminant analysis; principal component analysis; multiple linear regression analysis; SPATIAL VARIATION ASSESSMENT;
D O I
10.24425/aep.2018.124575
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Malacca River basin experienced river water pollution which caused a major deterioration to the ecosystems and environmental health. This study is carried out to assess the water quality data and identify the pattern of water pollution sources in the study area, and also to develop a predictive performance of water quality in the Malacca River basin. A chemometric approach using a combination of HCA. DA. PCA. and MLR, was applied into twenty water quality variables from nine sampling stations that were collected from January until December of 2015 in the river basin. HCA pointed out three clusters, namely Cluster 1 (C1) with low pollution source, Cluster 2 (C2) with moderate pollution source, and Cluster 3 (C3) with high pollution source. In the DA analysis, the results showed 21 variables, 12 variables, and 9 variables for standard mode, forward stepwise mode, and backward stepwise mode, respectively. Meanwhile. the PCA indicated that the main source of pollutants is detected from residential. industrial. commercial, agricultural. animal livestock, as well as forest land. Among the three models developed from MLR analysis, C3 with a high pollution source is detected to be the most suitable model to be used for the prediction of Water Quality Index in the Malacca River basin. This study proposed for an effective river water quality management by having new water quality monitoring network to be designed for more practical use in order to reduce time and effort, as well as cost saving purposes.
引用
收藏
页码:111 / 122
页数:12
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