An integrated stochastic-fuzzy modeling approach for the risk assessment of groundwater pollution

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 model developed was applied to a manganese-contaminated groundwater system caused by the infiltration of manganic wastewater from the manganic 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.