Predictive Analysis and Simulation Uncertainty of a Distributed Hydrological Model

Distributed hydrological models should pass through a careful calibration procedure backed by sensitivity, uncertainty and predictive analysis before they are utilized as a decision making aid in watershed management and scenario studies. This paper examines whether the uncertainty of the parameters of the spatially distributed hydrologic model WetSpa causes significant uncertainty in the model predictions. The WetSpa model is applied to the Torysa river basin, a rather large catchment located in Slovakia. Parameter estimation, sensitivity and predictive analysis of the model parameters are performed using a model‐independent parameter estimator, PEST. It is found that the correction factor for measured evaporation data has the highest relative sensitivity. Parameter uncertainty and predictive analysis give an insight of a proper parameter set and parameter uncertainty intervals and prove that the parameter uncertainty of the model does not result in a significant level of predictive uncertainty.