We studied how best to handle uncertainty in hydrological models that simulate how rain becomes river flow. We tested a well-known Bayesian way to estimate uncertainty in model settings as well as in model design. This approach helps judge which models are better considering their uncertainty. However, considering uncertainty in model settings is not helpful to provide river flow forecasting, so costly Bayesian tuning is rarely justified for practical purposes.