A general methodology for flood frequency estimation based on continuous simulation is here applied to a gauged site in the Czech Republic treated as if it was ungauged. In this implementation, stochastic temperature and precipitation models are used to drive TOPMODEL to simulate stream discharges. The coupled model parameters are varied randomly across specified ranges using Monte Carlo simulation. The results from a sample of 48,600 simulations each of length 100 years using an hourly time step are conditioned on low return period regionalized flood frequency, snow water equivalent, and flow duration curve information. Performance measures for each predicted variable are combined using fuzzy inference and simulations considered as nonbehavioral are rejected. 10,000-year simulations are made with the remaining 2281 behavioral simulations to produce prediction limits for flood magnitudes and other response variables at different return periods. The results are checked against a historical series of annual maximum discharges available at the site for a period before it was destroyed by the construction of a dam. The results compare well and appear to give more realistic prediction bounds than statistical extrapolations based on the Wakeby distribution, particularly at longer return periods.