摘要
水库水环境是一个灰色系统。将灰色聚类法应用到水库富营养评价中,是为了建立一种比较完善,适合于水库富营养化评价的模型,从而合理地评价库区的水质,为水库的管理提供依据。参照中国湖泊水库富营养化评价标准和水库的富营养化特点,选取评价指标,将富营养化程度分为6个级别,利用灰类白化权函数描述水体富营养化的等级界线,确定各指标在灰类中的聚类权以及聚类系数,确定各聚类对象的等级,在此基础上建立水库富营养化综合评价模型。以四川的升钟水库为研究对象,采用该水库具代表性监测点2006年的监测数据进行分析。结果表明,升钟水库的监测点中铁鞭电站、果园场、大石桥富营养化程度较重,铁路寺、青岗垭次之,李家坝最轻;该水库富营养化与周边的不合理开发密切相关,尤其是面源污染负荷的加重和网箱养鱼的增加,进一步加重了库区的水体富营养化。因此灰色聚类应用于环境质量评价中是可行的,关键是正确划分灰类白化函数。
Reservoir water environment is a grey system. Applying the grey clustering method to assessing the eutrophication of reservoir water is to establish a comparatively perfect model for reservoir eutrophication evaluation and give a sound assessment of the quality of reservoir water, thus, providing a ground for reservoir management. Taking ShengZhong Reservoir of Sichuan Province as the subject and selecting evaluation indices by referring to China＇s lakes and reservoirs eutrophication criteria and the characteristics of reservoir eutrophication, dividing the eutrophication into six categories and using the whitenization weight function to describe its grading sideline and determine the clustering weights, coefficients and their grades of the corresponding indices in the grey system, a comprehensive evaluation model was established in our study .Through the analysis of the data form several representative monitoring points in ShengZhong Reservoir region in 2006, the findings indicated that eutrophication in such places as Tiebian Hydropouer Station, Guoyuanchang and Dashiqiao corned the most, with Tielushi and Qinggangya secondary, and Lijiaba the least. The eutrophication of the reservoir was closely in relation to the irrational exploita- tion in its surrounding areas, especially to the non-point source pollutions and net fishery. Therefore, grey cluster is feasible for environmental quality assessment and key is the right dividing of whitenization weight function.
出处
《农业环境科学学报》
CAS
CSCD
北大核心
2008年第6期2407-2412,共6页
Journal of Agro-Environment Science
基金
国家自然科学基金(30470297)
关键词
水库富营养化
灰色聚类
聚类权
聚类系数
eutrophication of reservoir
grey clustering method
clustering weights
clustering coefficients
