Fuzzy pattern recognition model to water trophic grade in Chaohu Lake
模糊物元识别模型在巢湖水体富营养化评价中的应用研究

The research selected total phosphorus, total nitrogen, chlorophyll a,COD, BOD_5 ,DO and transparence as evaluation index. A fuzzy matter element model was used to recognize trophic state grades of 12 water quality monitoring stations distributed in Chaohu Lake from 2000 to 2007. Comparative analysis and validation were performed for the change and distribution area of trophic state and those of water quality monitoring indicators in Chaohu Lake at the same time. It could be concluded that recognition results correspond with the practical situation, and could well reflect change of the trophie state grade in spatial-temporal distribution. According to eutrophication evaluation results of Chaohu Lake, the eutrophication trend increased from 2000 to 2007. The fuzzy matter element calculation results showed that the eutrophication in west Chaohu Lake(1~#～6~#) was more serious than that of the east Chaohu Lake (7~#～12~#). The highest nearness degree of west Chaohu Lake was 0.9974,it was very near the nutritional status, but the highest nearness degree of east Chaohu Lake was 0. 5866.The eutrophication situation of east Chaohu Lake changed little from 2000 to 2007, but the west Chaohu Lake was opposition.