This study advances an integrated fuzzy-stochastic risk assessment (IFSRA) approach for the management of contaminated groundwater systems by systematically quantifying multiple uncertainties associated with site conditions and health impact criteria. The approach is based on fuzzy multi-attribute decision analysis, factorial designs, numerical modelling, and Monte Carlo simulation. The developed IFSRA is applied to a benzene-contaminated groundwater system. Twelve factorial experiments under different site conditions and 1,000 Monte Carlo simulation runs for each exposure variable were implemented. The results indicate that the IFSRA can effectively quantify health risks based on fuzzy and stochastic inputs as well as assess risk levels expressed as probability distribution functions under different possibility levels.