Risk-based corrective action (RBCA) is rapidly becoming the method of choice for remediating contaminated groundwater sites. In situ bioremediation will likely be an important part of RBCA: At a minimum, the potential for natural attenuation to reduce risks without the expense of engineered remediation measures must be evaluated. If natural attenuation is not sufficient, measures to increase the rate of in situ bioremediation may be cost-effctive for reducing risks. In this paper, a management model is presented that simulataneously predicts risk and proposes cost-effective options for reducing risk to acceptable levels under conditions of uncertainty. The model combines a noisy genetic algorithm with a numerical fate and transport model and an exposure and risk assessment model. Results from an application to a site from the literature show that, for the site considered, meeting a target risk level that is an order of magnitude more protective did not significantly increase the mean total remediation cost because the additional pumping required was inexpensive relative to the other remediation costs. Moreover, time-dependent costs associated with monitoring and the remedial system were significant for this application, illustrating the potential importance of identifying tradeoffs among these costs and pumping.
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