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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
