Water eutrophication evaluation based on multidimensional trapezoidal cloud model

Abstract

In recent years, the water quality of lakes has been deteriorating, and the water eutrophication phenomenon is particularly serious. Therefore, it is of great significance to evaluate the water eutrophication of lakes accurately to achieve water protection management. Numerous mechanistic or data-driven methods have been proposed to perform evaluations of the water eutrophication status. However, issues with these methods must still be solved, such as the use of unreasonable thresholds for the water eutrophication levels based on arbitrary numerical values and inaccurate threshold intervals in the water eutrophication evaluation criteria. To solve these problems, an integrated water eutrophication evaluation algorithm is proposed in this study. An evaluation model based on a multidimensional trapezoidal cloud model is first established, where numerical intervals are employed to characterize the thresholds of different water eutrophication levels instead of arbitrary numerical values. The Atanassov’s interval-value intuition language numbers are introduced to identify the model parameters, which are calculated based on the data of a specific lake rather than relying on inaccurate classification threshold intervals. Finally, the water quality data of Qionghai were used to validate the proposed method. Experimental results showed that this method can provide a more accurate and reasonable evaluation of water eutrophication compared with other methods.