基于随机-模糊模型的地下水污染风险评价

An Integrated Stochastic-fuzzy Modeling Approach for the Risk Assessment of Groundwater Pollution

提出了基于随机-模糊模型的地下水污染风险评价方法.该方法同时考虑了参数的随机性和模糊性,将地下水污染的环境风险定义为含水层'脆弱性'和地下水污染对人类健康'危害性'的乘积,运用模糊属性识别理论判断环境风险的等级.以长沙市黄兴镇蓝天化工厂锰渣场含锰废水下渗造成的地下水锰污染为例,分别计算了地下水锰污染的'脆弱性'和'危害性',并将其划分为'高'、'中-高'、'中'、'中-低'、'低'5个水平等级.结果表明,基于随机-模糊模型的地下水锰污染的环境风险介于'低-中'和'中'之间,与确定性模型中环境风险的计算结果有显著差别.

An integrated stochastic-fuzzy risk assessment model was developed to systematically quantify uncertainties. This model took into account both stochastic and fuzzy uncertainties associated with parameters. The environmental risk was defined as a combination of ＂vulnerability＂ and ＂hazard＂. Fuzzy attribute recognition method was used to classify the environmental risk. The modal developed was applied to a manganese-contaminated groundwater system caused by the infiltration of manganic wastewater from the manganie residues of Lantian Chemical Factory in Huangxing County, Changsha. The risk levels of both ＂vulnerability＂ and ＂hazard＂ were divided into five categories of ＂high＂, ＂medium-to-high＂, ＂medium＂, ＂medium-to-low＂ and ＂low＂. The results have shown that the risk level belongs to ＂medium-to-low＂ and ＂low＂, which is significantly different with the risk level calculated with certainty models.