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REVIEW PAPER
Lake Eutrophication Evaluation Based
on Fuzzy Set-pair Clustering Method
1
School of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000 China
2
National Key Laboratory of Water Disaster Prevention,Nanjing Hydraulic Research Institute, Nanjing 210029 China
3
Anhui Engineering Research Center of Green Building and Digital Construction, Anhui 241000 China
4
School of Architecture and Civil Engineering, Anhui Polytechnic University,
Wuhu, Anhui 241000 China
Submission date: 2024-05-24
Final revision date: 2024-06-20
Acceptance date: 2024-06-30
Online publication date: 2024-10-29
Publication date: 2025-06-06
Corresponding author
Ming Zhang
School of Architecture and Civil Engineering, Anhui Polytechnic University, Middle of Beijing Road No.8, 241000, Wuhu, China
School of Architecture and Civil Engineering, Anhui Polytechnic University, Middle of Beijing Road No.8, 241000, Wuhu, China
Pol. J. Environ. Stud. 2025;34(4):4499-4511
KEYWORDS
TOPICS
ABSTRACT
The problem of water eutrophication is getting worse in our country these days. In order to reduce
eutrophication, the essential step is the evaluation of water quality. It analyzes the utilization of lake
eutrophication according to the main components and corresponding water quality standards for lake
eutrophication. Thereby, it can provide scientific basis for the development, utilization, planning,
and management of water resources. In this study, the fuzzy set pair clustering assessment method
is combined with combination weight to reduce the impacts of random errors in eutrophication
monitoring data and the fuzziness of lake eutrophication definitions on the consistency and reliability
of lake eutrophication evaluations. The fuzzy set pair clustering assessment method （FSPCAM）is
used to evaluate the eutrophication of 20 typical lakes and reservoirs in China. The results that were
obtained during the study matched those from other evaluation methods. It was concluded, based on
the analysis, that the lakes were severely polluted. By processing the data, the presented methodology
can obtain a better detection of eutrophication levels with less time required. Therefore, more reliable
information by fuzzy set pair clustering assessment method can be provided to the decision makers,
e.g., lake management authorities.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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