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.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China under the contract No. 51409139 and No. 51709142, and Hubei Provincial Natural Science Foundation of China under the contract No. 2017CFB312, and the Natural Science Foundation of Water Resources Department of Hunan Government under the contract No. 201723041.
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Feng, Y., Bao, Q., Chenglin, L. et al. Introducing Biological Indicators into CCME WQI Using Variable Fuzzy Set Method. Water Resour Manage 32, 2901–2915 (2018). https://doi.org/10.1007/s11269-018-1965-x
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DOI: https://doi.org/10.1007/s11269-018-1965-x