水体富营养化驱动因子粗糙分析

基于水质污染因子及其污染特性存在不确定性的特点,将粗糙集理论应用于水质污染因子及特性分析,建立污染因子评价粗糙集数学模型.该模型仅依赖于数据本身提供的信息,挖掘污染因子之间不确定的分类关系,计算其对水体污染或水质富营养化的重要性即贡献率大小,科学、快速和客观地揭示水体污染中起主导作用的污染来源,为水体污染控制提供理论依据.应用数学模型分析巢湖12个监测点的水质数据,确定巢湖主要污染因子及其导致湖泊富营养化的贡献率,结果显示TP、COD、TN等是导致巢湖水体富营养化的重要因子,今后应控制巢湖入湖水体的总磷及其有机污染物含量,以改善巢湖水质富营养化状况.

Rough Analysis on Driving Factors of Eutrophic Water

Pollutant factors of water quality for rivers and lakes and their relationships are the key factors for water pollution control. Traditional theories based on ascertained maths are not appropriate to deal with them because of their unascertained information. The rough set theory as a new technically maths tool can analyse and mine unascertained information from water pollutant factors. And the maths model based on rough set theory is put forward in this paper to calculate the importance coefficients of pollutant factors and to discover hidden data from them. Then the maths model is used to analyse the water quality data of Chaohu Lake. The result shows that the pollutant factors such as TP and COD are the most important factors which describe correctly the contamination degree of Chaohu Lake. And it also points out that the future study of Chaohu Lake should be focused on reducing the concentration of TP, COD and TN so as to improve water quality of it.