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Assessment of River Water Quality Based on an Improved Fuzzy Matter-Element Model

Author

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  • Yumin Wang

    (School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Weijian Ran

    (School of Glasgow, University of Electronic Science and Technology, Chengdu 610054, China)

  • Lei Wu

    (School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Yifeng Wu

    (School of Energy and Environment, Southeast University, Nanjing 210096, China)

Abstract

In this paper, an improved fuzzy matter-element (IFME) method was proposed, which integrates the classical matter-element (ME) method, set pair analysis (SPA), and variable coefficient method (VCM). The method was applied to evaluate water quality of five monitor stations along Caoqiao River in Yixing city, Jiangsu Province, China. The levels of river water quality were determined according to fuzzy closeness degree. Compared with the traditional evaluation methods, the IFME method has several characteristics as follows: (i) weights were determined by the VCM method, which can reduce workload and overcome the adverse effects of abnormal values, (ii) membership degrees were defined by SPA, which can utilize monitored data more scientifically and comprehensively, and (iii) IFME is more suitable for seriously polluted rivers. Overall, these findings reinforce the notion that an integrated approach is essential for attaining scientific and objective assessment of river water quality.

Suggested Citation

  • Yumin Wang & Weijian Ran & Lei Wu & Yifeng Wu, 2019. "Assessment of River Water Quality Based on an Improved Fuzzy Matter-Element Model," IJERPH, MDPI, vol. 16(15), pages 1-11, August.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:15:p:2793-:d:254872
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    References listed on IDEAS

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    1. Mohamad Fulazzaky, 2009. "Water Quality Evaluation System to Assess the Brantas River Water," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(14), pages 3019-3033, November.
    2. Yumin Wang & Weijian Ran, 2019. "Comprehensive Eutrophication Assessment Based on Fuzzy Matter Element Model and Monte Carlo-Triangular Fuzzy Numbers Approach," IJERPH, MDPI, vol. 16(10), pages 1-17, May.
    3. Singh, Kunwar P. & Basant, Ankita & Malik, Amrita & Jain, Gunja, 2009. "Artificial neural network modeling of the river water quality—A case study," Ecological Modelling, Elsevier, vol. 220(6), pages 888-895.
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    Cited by:

    1. Cheng Zhan & Mingjing Guo & Jinhua Cheng & Hongxia Peng, 2022. "Evaluation of Resources and Environment Carrying Capacity Based on Support Pressure Coupling Mechanism: A Case Study of the Yangtze River Economic Belt," IJERPH, MDPI, vol. 20(1), pages 1-21, December.

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