Assessing the Eutrophication of Shengzhong Reservoir Based on Grey Clustering Method

Abstract

Abstract Reservoir water environment is a grey system. The grey clustering method is applied to assessing the reservoir water environment to establish a relatively complete model suitable for the reservoir eutrophication evaluation and appropriately evaluate the quality of reservoir water, providing evidence for reservoir management. According to China’s lakes and reservoir eutrophication criteria and the characteristics of China’s eutrophication, as well as certain evaluation indices, the degree of eutrophication is classified into six categories with the utilization of grey classified whitening weight function to represent the boundaries of classification, to determine the clustering weight and clustering coefficient of each index in grey classifications, and the classification of each clustering object. The comprehensive evaluation of reservoir eutrophication is established on such a foundation, with Sichuan Shengzhong Reservoir as the survey object and the analysis of the data attained by several typical monitoring points there in 2006. It is found that eutrophication of Tiebian Power Generation Station, Guoyuanchang and Dashiqiao Bridge is the heaviest, Tielusi and Qinggangya the second, and Lijiaba the least. The eutrophication of this reservoir is closely relevant to the irrational exploitation in its surrounding areas, especially to the aggravation of the non-point source pollution and the increase of net-culture fishing. Therefore, it is feasible to use grey clustering in environment quality evaluation, and the point lies in the correct division of grey whitening function