Hybrid Fuzzy-Stochastic Modeling Approach for Assessing Environmental Risks at Contaminated Groundwater Systems

Abstract

The risk associated with a contaminated groundwater system often refers to the chance of damaging a human's health through various exposure pathways. In this study, a hybrid fuzzy-stochastic risk assessment (FUSRA) approach is developed for examining uncertainties associated with both source/media conditions and evaluation criteria in a groundwater quality management system. This is based on the fact that deterministic environmental guidelines are mostly impractical and cannot be implemented, due to the existence of many uncertain and complex factors. Fuzzy membership functions are then employed to quantify these uncertainties and complexities. A number of tasks have been undertaken, including Monte Carlo simulation for the fate of contaminants in subsurface, examination of contamination levels based on the simulation results, quantification of evaluation criteria using fuzzy membership functions, and risk assessment based on the combined fuzzy/stochastic inputs. The developed FUSRA is applied to a petroleum-contaminated groundwater system in western Canada. It is indicated that, with the expanded evaluation dimensions, the FUSRA can more effectively elucidate the relevant health risks. Reasonable results have been generated, which are useful for evaluating health risks resulting from subsurface toluene contamination. They also provide support for related remediation decisions.