Environmetric Techniques Application in Water Quality Assessment: A Case Study in Linggi River Basin

Mohd Fadhil Kasim, Hafizan Juahir, Ismail Tawnie, Azman Azid, Ahmad Shakir Mohd Saudi, Saiful Samsudin, Mohd Ekhwan Toriman, Bashirah Mohd Fazli, Che Noraini Che Hasnam


In this research, determination of water quality status was carried out by using non-parametric Mann-Kendall analysis for the Linggi River Basin and for classification of the river, HACA and PCA has been used to classify the river to obtain the clearest picture of the water quality status. The dataset includes 6 parameters for 6 monitoring stations (1997 to 2012). Mann-Kendall trend analysis shows trend analysis indicate that significant improvement trend for all parameters studied except for BOD (WQ1 (P<0.1) and WQ6 (P<0.05)) and SS (WQ4 to WQ6 (P<0.05)) trend were shows the unhealthy significant trend. This indicates that even though the WQI getting good in trend, a few parameters such as BOD and SS need to be watched and enforcement by the local authority need to be done to make sure the WQI continuously getting better in the future. HACA grouped the six monitoring stations into three different clusters based on their similarities namely less pollution site (LPS), medium pollution site (MPS) and high pollution site (HPS). HACA indicate one station (WQ1) into group LPS, two stations into MPS (WQ2 and WQ3) and three stations into HPS (WQ4, WQ5 and WQ6) respectively. PCA was used to investigate the origin of each water quality variable based on the clustered region. Three principal components (PCs) were obtained with 75.3% total variation for HPS, 73.4% for MPS and 68.1% for LPS. The major pollution source for HPS are of anthropogenic source (municipal waste, domestic wastes) while for MPS the major source of pollution was from non point source pollution such as animal husbandry in livestock farm. For the LPS, major source comes from the sea tide effect (natural effect). The identification and classification of different region by this study will help the local authorities make better and more informed decisions about the improvement water quality program for the future.


Water Quality Index (WQI); Mann-Kendall; cluster analysis; principal component analysis; Linggi River

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DOI: http://dx.doi.org/10.11113/jt.v74.2963


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