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|Title:||Cascading Model Uncertainty From Medium Range Weather Forecasts (10 Days) Through a Rainfall-Runoff Model to Flood Inundation Predictions Within the European Flood Forecasting System (EFFS)|
|Authors:||PAPPENBERGER Florian; BEVEN K.j.; HUNTER N.m.; BATES Paul; GOUWELEEUW Ben; THIELEN DEL POZO JUTTA; DE ROO ARIE|
|Citation:||HYDROLOGY AND EARTH SYSTEM SCIENCES vol. 9 p. 381-393|
|Publisher:||European Geosciences Union|
|Type:||Articles in Journals|
|Abstract:||The political pressure on the scientific community to provide medium to long term flood forecasts has increased in the light of recentflooding events in Europe. Such demands can be met by a system consisting of three different model components (weather forecast, rainfall–runoff forecast and flood inundation forecast) which are all liable to considerable uncertainty in the input, output and model parameters.Thus, an understanding of cascaded uncertainties is a necessary requirement to provide robust predictions. In this paper, 10-day aheadrainfall forecasts, consisting of one deterministic, one control and 50 ensemble forecasts, are fed into a rainfall–runoff model (LisFlood) forwhich parameter uncertainty is represented by six different parameter sets identified through a Generalised Likelihood Uncertainty Estimation(GLUE) analysis and functional hydrograph classification. The runoff of these 52 * 6 realisations form the input to a flood inundation model(LisFlood-FP) which acknowledges uncertainty by utilising ten different sets of roughness coefficients identified using the same GLUEmethodology. Likelihood measures for each parameter set computed on historical data are used to give uncertain predictions of flow hydrographsas well as spatial inundation extent. This analysis demonstrates that a full uncertainty analysis of such an integrated system is limited mainlyby computer power as well as by how well the rainfall predictions represent potential future conditions. However, these restrictions may beovercome or lessened in the future and this paper establishes a computationally feasible methodological approach to the uncertainty cascade problem.|
|JRC Institute:||Institute for Environment and Sustainability|
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