LAUSR

There is a growing need for reliable medium to extended range hydrological forecasts in water and environmental management (e.g. hydro-power and agricultural production). The objective of this paper is a first assessment of the skill of hydrological forecasts based on Numerical Weather Predictions (NWPs) in comparison to the skill of forecasts based on climatology for monthly forecasts with daily resolutions and to identify possibilities of improvement by post-processing the hydrological forecasts. Various hydrological relevant model variables, such as the surface and subsurface runoff and the soil water content, will be analysed for entire Switzerland. The spatially aggregated predictions of these variables are compared to daily simulations and to long-term daily averages of simulations driven by meteorological observations (i.e. climatology). Besides this comparison of forecasts with simulations for model variables without direct measurements available, the skill of the monthly stream-flow forecasts is estimated at four catchments with discharge measurements. Additionally post-processing methods have been applied to remove bias and dispersion errors and to estimate the predictive uncertainty of the stream-flow. Some results of various verification measures like variants of the Geometric Mean for ratios of spatial aggregates and the Continuous Rank Probability Skill Score (CRPSS) will be shown. Apart from the indication of a strong diversity of upper limits of the forecast skill depending on catchment characteristics, the results of NWPs are generally superior to climatological predictions and could be applied gainfully for various kinds of long-term water management planning.