Prediction uncertainty of conceptual rainfall-runoff models caused by problems in identifying model parameters and structure

The uncertainties arising from the problem of identifying a representative model structure and model parameters in a conceptual rainfall-runoff model were investigated. A conceptual model, the HBV model; was applied to the mo untainous Brugga basin (39.9 km(2)) in the Black Forest, southwestern Germa ny. In a first step, a Monte Carlo procedure with randomly generated parame ter sets was used for calibration. For a ten-year calibration period, diffe rent parameter sets resulted in an equally good correspondence between obse rved and simulated runoff. A few parameters were well defined (i.e, best pa rameter values were within small ranges), but for most parameters good simu lations were found with values varying over wide ranges. In a second step, model variants with different numbers of elevation and landuse zones and va rious runoff generation conceptualizations were tested. In some cases, repr esentation of more spatial variability gave better simulations in term of d ischarge. However, good results could be obtained with different and even u nrealistic concepts. The computation of design floods and low flow predicti ons illustrated that the parameter uncertainty and the uncertainty of ident ifying a unique best model variant have implications for model predictions. The flow predictions varied considerably. The peak discharge of a flood wi th a probability of 0.01 year(-1), for instance, varied from 40 to almost 6 0 mm day(-1). It was concluded that model predictions, particularly in appl ied studies, should be given as ranges rather than as single values.