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Article

Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis

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State Agency for Agriculture, Environment and rural Areas Schleswig-Holstein (LLUR), Department 41 River Ecology, Hamburger Chaussee 25, 24220 Flintbek, Germany
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Leichtweiß-Institute for Hydraulic Engineering and Water Resources (LWI), Department Hydrology, Water Management and Water Protection, Technische Universität Braunschweig, Beethovenstraße 51 a, 38106 Braunschweig, Germany
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Institute for Circular Economy Development, Vietnam National University-Ho Chi Minh City, 01 Marie Curie, VNU Campus, Linh Trung, Thu Duc District, Ho Chi Minh City 71308, Vietnam
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Center of Water Management and Climate Change, Institute for Environment and Resources, Vietnam National University-Ho Chi Minh City, Ho Chi Minh City 71308, Vietnam
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Faculty of Resources & Environment, University of Thu Dau Mot, 06 Tran Van On Street, Binh Duong 75151, Vietnam
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School of the Environment and Chemistry Department, Trent University, Peterborough, ON K9L 0G2, Canada
*
Authors to whom correspondence should be addressed.
Academic Editors: Alessandro Bergamasco, Hong Quan Nguyen, Gabriella Caruso, Qianguo Xing and Eleonora Carol
Water 2021, 13(10), 1330; https://doi.org/10.3390/w13101330
Received: 31 March 2021 / Revised: 28 April 2021 / Accepted: 5 May 2021 / Published: 11 May 2021
Temporal and spatial water quality data are essential to evaluate human health risks. Understanding the interlinking variations between water quality and socio-economic development is the key for integrated pollution management. In this study, we applied several multivariate approaches, including trend analysis, cluster analysis, and principal component analysis, to a 15-year dataset of water quality monitoring (1999 to 2013) in the Thi Vai estuary, Southern Vietnam. We discovered a rapid improvement for most of the considered water quality parameters (e.g., DO, NH4, and BOD) by step trend analysis, after the pollution abatement in 2008. Nevertheless, the nitrate concentration increased significantly at the upper and middle parts and decreased at the lower part of the estuary. Principal component (PC) analysis indicates that nowadays the water quality of the Thi Vai is influenced by point and diffuse pollution. The first PC represents soil erosion and stormwater loads in the catchment (TSS, PO4, and Fetotal); the second PC (DO, NO2, and NO3) determines the influence of DO on nitrification and denitrification; and the third PC (pH and NH4) determines point source pollution and dilution by seawater. Therefore, this study demonstrated the need for stricter pollution abatement strategies to restore and to manage the water quality of the Thi Vai Estuary. View Full-Text
Keywords: cluster analysis (CA); long-term monitoring; nutrient pollution; principal component analysis (PCA); water quality assessment cluster analysis (CA); long-term monitoring; nutrient pollution; principal component analysis (PCA); water quality assessment
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MDPI and ACS Style

Lorenz, M.; Nguyen, H.Q.; Le, T.D.H.; Zeunert, S.; Dang, D.H.; Le, Q.D.; Le, H.; Meon, G. Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis. Water 2021, 13, 1330. https://doi.org/10.3390/w13101330

AMA Style

Lorenz M, Nguyen HQ, Le TDH, Zeunert S, Dang DH, Le QD, Le H, Meon G. Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis. Water. 2021; 13(10):1330. https://doi.org/10.3390/w13101330

Chicago/Turabian Style

Lorenz, Malte, Hong Quan Nguyen, Trong Dieu Hien Le, Stephanie Zeunert, Duc Huy Dang, Quang Dung Le, Huyen Le, and Günter Meon. 2021. "Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis" Water 13, no. 10: 1330. https://doi.org/10.3390/w13101330

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