This proposal outlines an ambitious effort to investigate state- of-the-art modeling technology in the context of a practical problem with national consequences. Risk management decisions in toxicology, health policy, environmental management, and related fields are often supported by complex mathematical models. These models are intended to predict the consequences of each alternative course of action. The model predictions depend on values specified by the potential users. However, these values are often not known with certainty. In failing to reflect uncertainty in parameter specification, the models may lead to inappropriate risk management decisions. The investigators propose to apply a set of hierarchical Bayesian methods to characterize uncertainty in models which predict the concentration of synthetic organic chemicals in surface waters. The ultimate goal is the creation of an expert system to assist users in selecting values of parameters in risk management models. The general class of problems is an important one, but one that has only been worked on by a few investigators. The research team is well trained and well versed in the relevant analytic tools. There is every reason to believe they will complete the project they propose successfully.
