Using Multivariate Statistical Techniques to Assess Water Quality of the Saigon River, Vietnam

Thinh, Nguyen Vu Duc; Tuan, Le Quoc; Thao, Ngo Vy; Huynh, Nguyen Nhat

doi:10.3107/jesss.11.pp01

Cited by 1 publication

(2 citation statements)

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“…Therefore, it can be seen that surface water in the study area is unsuitable for irrigation purposes. The water quality index has the advantage of showing the status of water quality, thereby making choices for effective use and management of water resources [47][48][49][50][51]. Hierarchical cluster analysis (HCA) is performed from the data of 10 surface water quality parameters that vary by space and the results of HCA analysis are shown in Fig.…”

Section: B Water Quality Index (Vn_wqi) and Grouping Of Monitoring Lo...mentioning

confidence: 99%

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Surface Water Quality in Urban Areas in Southern Most Province of Vietnam

Hong,

Mi,

Giao

2023

IJESD

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This study aims to assess the influence of socioeconomic activities on surface water quality in the Ca Mau province. Water quality data were collected at 14 locations in 2021. Water quality index (VN_WQI), hierarchical cluster analysis (HCA), Pearson correlation and principal component analysis (PCA) were applied in the study. The results showed that the surface water quality was contaminated organic matters (TSS, BOD, COD) and coliform. Water quality was assessed from poor to medium levels by VN_WQI and the water quality is unsuitable for direct irrigation purposes. The results also showed that water quality at Ganh Hao river fork (S2) was the most polluted. HCA classified water quality into three groups based on the similarity of water quality parameters. Pearson correlation results indicated organic pollution, nutrients and microorganisms were mutually related. PCA explained 83.60% of the total variance with three PCs. Ten parameters were identified as the key water parameters influencing surface water quality and these parameters should be continuously monitored. The water pollution sources were possibly urban and market activities, production facilities discharge and salinity intrusion.

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Section: B Water Quality Index (Vn_wqi) and Grouping Of Monitoring Lo...mentioning

confidence: 99%

“…In PCA analysis, eigenvalues are often used to identify principal components (PCs) [61]. Principal components with eigenvalues greater than 1 should be retained, to explain the variability of information contained in the original data [19,51]. The scree plot (Fig.…”

Section: B Water Quality Index (Vn_wqi) and Grouping Of Monitoring Lo...mentioning

confidence: 99%