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Introducing Biological Indicators into CCME WQI Using Variable Fuzzy Set Method

Author

Listed:
  • Yan Feng

    (Nanchang University
    Hohai University)

  • Qian Bao

    (Hydrology Bureau of Changjiang Water Resources Commission)

  • Liu Chenglin

    (Nanchang University)

  • Wei Bowen

    (Nanchang University)

  • You Zhang

    (Hohai University)

Abstract

The biological indicators are rarely used in CCME WQI, for the objective thresholds of most biological indicators are ambiguous. To solve this problem, this study establishes an improved CCME WQI model based on variable fuzzy set theory. The water quality of Wuli Lake is assessed as an illustration; and the result shows that its water quality condition is “fair”, and more measures should be adopted to control the internal phosphorus releasing and the reproduction of cyanobacteria in summer and autumn. Moreover, compared with the conventional CCME CQI, the improved CCME WQI is more comprehensive, for it not only takes the aquatic physic-chemical condition into consideration, but also introduces the biological indicators into evaluation.

Suggested Citation

  • Yan Feng & Qian Bao & Liu Chenglin & Wei Bowen & You Zhang, 2018. "Introducing Biological Indicators into CCME WQI Using Variable Fuzzy Set Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2901-2915, June.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:8:d:10.1007_s11269-018-1965-x
    DOI: 10.1007/s11269-018-1965-x
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    References listed on IDEAS

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    1. X. Wang & R. Zhao & Y. Hao, 2011. "Flood Control Operations Based on the Theory of Variable Fuzzy Sets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(3), pages 777-792, February.
    2. Xin-Yu Wan & Ping-An Zhong & Emmanuel Appiah-Adjei, 2014. "Variable Sets and Fuzzy Rating Interval for Water Allocation Options Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2833-2849, August.
    3. Yuankun Wang & Dong Sheng & Dong Wang & Huiqun Ma & Jichun Wu & Feng Xu, 2014. "Variable Fuzzy Set Theory to Assess Water Quality of the Meiliang Bay in Taihu Lake Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 867-880, February.
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    Cited by:

    1. Yudan Dou & Xiaolong Xue & Zebin Zhao & Xiaowei Luo & Ankang Ji & Ting Luo, 2018. "Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China," IJERPH, MDPI, vol. 15(9), pages 1-20, September.

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