This paper presents an uncertainty evaluation method for rainfall-runoff models and applies it to model selection considering data availability. Simulating model users' parameter calibration processes with Monte Carlo simulation technique, this method evaluates parameter uncertainty and its propagation to model output. Uncertainty in simplified models are evaluated comparatively from an ideal model that takes into account detailed physical rainfall-runoff processes.
