湖泊水体富营养化评价与可持续发展研究  

Eutrophication Evaluation and Sustainable Development Countermeasure for Lake

作　　者：陈为国[1] 许文杰[2] 张晓平[2] 赵磊[3] 

机构地区：[1]济南工程职业技术学院建筑工程系,山东济南250200 [2]山东建筑大学理学院,山东济南250101 [3]山东大学土建与水利学院,山东济南250061

出　　处：《节水灌溉》2008年第6期47-49,52,共4页Water Saving Irrigation

摘　　要：参照中国湖泊富营养化评价标准,把湖泊水体富营养化程度划分为6个级别,选取Chl-a、TP、TN、CODMn和SD等5个指标为评价指标,根据实测数据建立指标及指标标准相对隶属度矩阵;综合考虑指标相对隶属度与指标权重,建立环境指标综合权重矩阵;应用多级模糊模式识别模型求得样本集对模糊概念"营养化"的相对隶属度矩阵;最后利用样本的级别特征值对湖泊水体进行富营养化评价。并以东昌湖为例进行了实例计算与分析,验证了此模型的准确性和实用性。最后,为东昌湖的保护与可持续发展提出建议。Referring to Chinese lakes eutrophication standard, the eutrophication degree of lake is divided into 6 grades in this paper. Five indexes, namely Chl-a, TP, TN , CODMn and SD, are selected as evaluation indexes. According to measured data, relative membership degree matrix of index and index standard are established. Then comprehensive weight matrix of environment indexes is established through the comprehensive consideration of relative membership degree of index and weight of index. The multi-grade fuzzy pattern recognition model is used to calculate the relative membership degree matrix of sample set to eutrophication, which is a fuzzy concept. And the grade eigenvalue is used to evaluate the eutrophication degree of lake water. The veracity and practicability of this model are proved through actual calculation and analysis, in which Dongchang Lake is taken as an example. In the end, several suggestions for the protection and sustainable development of Dongchang Lake are put forward.

关 键 词：湖泊水体富营养化 多级模糊模式识别模型 级别特征值 东昌湖 可持续发展 

分 类 号：X52[环境科学与工程—环境工程]