A contamination source identification methodology should be continuously run in real time to provide timely information about contamination event status. The method should be robust with respect to uncertainty and variability in factors affecting the network hydraulic model. This work assesses the impact of hydraulic modeling errors on the performance of a source identification algorithm. Preliminary results evaluate the effect of demand estimation errors on the performance of the identification algorithm. Results suggest the source identification method can be robust to the types of errors investigated. It is stressed, however, that broader conclusions can not be drawn, because the tests consider only one network test case, and the true statistical characteristics of stochastic demands are unknown. Furthermore, the particular example chosen assumes optimistic scenarios for demand estimation. The results provide a methodology and motivation for continuing to investigate the true performance characteristics of real-time contamination source identification algorithms.