不确定信息下的水体污染因子粗糙分析

基于水体水质污染因子、污染物浓度等信息都存在着一定的不确定性,运用粗糙集理论的数学知识对水质污染程度和水质污染因子对水质污染的贡献率大小等不确定性问题进行了探讨.以巢湖为例,分析巢湖12个监测点位的水质监测数据及其分类关系,计算巢湖主要污染因子的重要性程度及其对湖泊水质富营养化的贡献率,结果表明运用粗糙集理论对巢湖水质监测数据的分析理论上是可行的,计算结果是可靠的.研究结果指出磷、耗氧有机物是最要重要的污染因子,对巢湖水质富营养化的贡献率占64.3%,控制巢湖水体中磷、耗氧有机物含量及接纳点源和面源的入湖负荷是改善巢湖水质富营养化状况最有效的途径.

Rough Analysis on Aquatic Pollutant Factors under Uncertainty

The paper takes advantage of approximately types of unascertained information based on rough set theory to study the relationships of aquatic pollutant factors. The contributing rates for some pollutant factors that describe the degree of water quality polluted are calculated by mathematical model based on rough set theory.The mathematical model is applied to analyze aquatic pollutant factors in Chaohu Lake.It is feasible and reliable to discover and mine knowledge from water quality database and to calculate the contributing rate for pollutant factors.The result shows that phosphorus and oxygen-consuming organics are the most important factors that lead to the eutrophication in Chaohu Lake,the contributing rate for them are 64.3% in all,and it also points that the most effective way to improve water quality in Chaohu Lake is to reduce loads of influent phosphorus and aerobic organic compounds.The result provides some important information for environment management and protection for Chaohu Lake.