属性识别模型在艾比湖水质评价中的应用  

Application of attribute recognition theory in water quality evaluation of Ebinur Lake

作　　者：吴荣 张霞[2] 黄海龙[2] 

机构地区：[1]新疆博尔塔拉蒙古自治州环境监测站,新疆博乐833400 [2]新疆农业大学草业与环境科学学院,新疆乌鲁木齐830052

出　　处：《干旱区地理》2009年第4期571-577,共7页Arid Land Geography

基　　金：国家科技支撑项目(2006BAD26130901)资助项目

摘　　要：根据新疆博尔塔拉蒙古自治州环境监测站对艾比湖5个代表性的监测断面最近5年的水质实测资料,结合熵权法和国家地表水环境质量标准系统地建立了属性识别模型,运用属性计算和属性得分详细评价了艾比湖的水质。模型评价结果表明:艾比湖的水质污染主要为氨氮、磷、砷的污染。就空间而言,湖心2水质较好,没有出现Ⅴ类水质,其次为喇叭口,博乐河口与精河河口水质较差;就时间而言,2003年各监测断面水质均属Ⅰ类,之后逐渐恶化,到2008年半数以上的监测断面属于Ⅴ类水质,且与改进密切值法的评价结果比较,结果较吻合。采用属性识别模型评价湖泊水质,概念清晰,计算简单,评价结果客观、合理,可以反映出艾比湖水质的现状,是湖泊水质评价中简便实用的评价方法之一。With the development of economy, water body pollution become more and more serious and the water quality deterioration has become an increasingly important issue. According to the water quality measured data of five monitoring sections from the environmental monitor station of the Xinjiang Bortala Mongol Autonomous Prefecture in recent five years, the entropy method is used to determine the weight of every evaluation index, this paper built the attribute distinction model systematically and evaluated water quality of the Ebinur Lake in detail combined the surface water environment quality standards （GB3838 -2002 ）. The model evaluation results indicated that, the water pollution was mainly ammonia nitrogen, phosphorus and arsenic pollution. In terms of spatial distribution, water quality at the center of the lake 2 water was best, and there was not Grade Ⅴ water, the followed was in the section of Labakou, water quality at the Jinghe estuary and Bole estuarywas the worst. In terms of temporal distribution, the water quality of five monitoring sections were Grade Ⅰ in 2003, and deteriorated gradually in the following years, more than half monitoring sections changed into Grade Ⅴ water quality until 2008. At the same time, this paper compared the model evaluation results with the evaluation results of the modified osculation value method, there were only one year deviation among 6 years, the two evaluation results coincided quite well. Based on entropy weight, it can obtain a weight considering every evaluation index objectively and make for decision-making scientifically. In order to further distinguish the differences from the samples of with the same water quality, this paper applied the theory of attribute recognition score to solve each sample scheduling problem. The score is lower, the water quality is worse. In a word, the evaluation results were conformed with the present situation of Ebinur lake water quality mostly. The calculation of attribute distinction model is simple, evaluation result is o

关 键 词：艾比湖 属性识别模型 水质评价 熵权法 

分 类 号：X824[环境科学与工程—环境工程]