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Water 2015, 7(9), 4821-4847; doi:10.3390/w7094821

Genetic Algorithm-Based Fuzzy Comprehensive Evaluation of Water Quality in Dongzhaigang

School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
Guangzhou Marine Geological Survey, Guangzhou 510760, China
Key Laboratory of Marine Mineral Resources, Ministry of Land and Resources, Guangzhou 510760, China
Author to whom correspondence should be addressed.
Academic Editor: Thilo Hofmann
Received: 4 July 2015 / Revised: 14 August 2015 / Accepted: 25 August 2015 / Published: 2 September 2015
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The concentrations of dissolved inorganic nitrogen (DIN; NO2–N, NH3–N, and NO3–N), PO43−–P, dissolved oxygen (DO), chemical oxygen demand (COD), five-day biological oxygen demand (BOD5), oil, Si, and seven heavy metals (Hg, Cr, Cu, As, Zn, Pb, and Cd) in seawater from the Dongzhaigang National Mangrove Nature Reserve of China in 2013 were determined. Except for the concentrations of the COD, BOD5, Cr, Hg, Cu, As, and Cd, each index in seawater were found to be over the limits of I-Class seawater standards. The index of organic pollution showed that the pollution level in this study area reached level 6; eutrophication levels indicated that the nutritional level reached level 4. According to the water quality index model, the sea area was slightly polluted by heavy metals. In a genetic algorithm-based fuzzy comprehensive evaluation, the results for organic pollutants, nutrients, and heavy metal pollution can be combined to evaluate the water quality as a whole. Results showed that the sea area in Dongzhaigang did not have a healthy water environment, but was seriously polluted by organic pollutants and nutrients. View Full-Text
Keywords: water quality; organic pollution; genetic algorithm; Dongzhaigang mangrove wetland water quality; organic pollution; genetic algorithm; Dongzhaigang mangrove wetland

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wen, J.; Li, F.; Zeng, X.; Shen, K.; He, H.; Liang, Y.; Gan, H.; Zhang, J.; Long, X.; Wei, Y. Genetic Algorithm-Based Fuzzy Comprehensive Evaluation of Water Quality in Dongzhaigang. Water 2015, 7, 4821-4847.

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