The U.S. Geological Survey’s National Water Quality Assessment topical study Transport of Natural and Anthropogenic Contaminants (TANC) to Supply Wells produced four detailed simulation models of ground-water flow. These models were similar in level of effort—they all were produced with similar budgets, time frames, and purpose. The purpose of the models was to estimate areas contributing recharge (ACRs) to public-supply wells, which are essential to understanding the relation between land use and drinking-water quality. Simulation models commonly are used to estimate ACRs, but the effects of uncertainty in the models often are not considered. The four models evaluated in this study represent very different hydrogeologic settings in California, Connecticut, Florida, and Nebraska. Despite the difference in settings, preliminary results show similarities in sources of model uncertainty that affect the simulated ACRs. Several techniques were used to quantify uniqueness and uncertainty in model predictions, including alternative parameterization, stochastic hydraulic conductivity, stochastic heterogeneity, and Monte Carlo simulation using regression-based parameter estimation. Monte Carlo results indicate that parameter uncertainty affects predicted travel times and that longer travel times lead to greater uncertainty in the estimated ACR. This result can be used to predict the probability of sampling various combinations of water from different sources to a well.