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.