Abstract. This paper presents the development of the European Flood Alert System (EFAS), which aims at increasing preparedness for floods in trans-national European river basins by providing local water authorities with mediumrange and probabilistic flood forecasting information 3 to 10 days in advance. The EFAS research project started in 2003 with the development of a prototype at the European Commission Joint Research Centre (JRC), in close collaboration with the national hydrological and meteorological services. The prototype covers the whole of Europe on a 5 km grid. In parallel, different high-resolution data sets have been collected for the Elbe and Danube river basins, allowing the potential of the system under optimum conditions and on a higher resolution to be assessed. Flood warning lead-times of 3-10 days are achieved through the incorporation of medium-range weather forecasts from the German Weather Service (DWD) and the European Centre for Medium-Range Weather Forecasts (ECMWF), comprising a full set of 51 probabilistic forecasts from the Ensemble Prediction System (EPS) provided by ECMWF. The ensemble of different hydrographs is analysed and combined to produce early flood warning information, which is disseminated to the hydrological services that have agreed to participate in the development of the system. In Part 1 of this paper, the scientific approach adopted in the development of the system is presented. The rational of the project, the systems set-up, its underlying components, basic principles and products are described. In Part 2, results of a detailed statistical analysis of the performance of the system are shown, with regard to both probabilistic and deterministic forecasts.

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Abstract. Since 2005 the European Flood Alert System (EFAS) has been producing probabilistic hydrological forecasts in pre-operational mode at the Joint Research Centre (JRC) of the European Commission. EFAS aims at increasing preparedness for floods in trans-national European river basins by providing medium-range deterministic and probabilistic flood forecasting information, from 3 to 10 days in advance, to national hydro-meteorological services.This paper is Part 2 of a study presenting the development and skill assessment of EFAS. In Part 1, the scientific approach adopted in the development of the system has been presented, as well as its basic principles and forecast products. In the present article, two years of existing operational EFAS forecasts are statistically assessed and the skill of EFAS forecasts is analysed with several skill scores. The analysis is based on the comparison of threshold exceedances between proxy-observed and forecasted discharges. Skill is assessed both with and without taking into account the persistence of the forecasted signal during consecutive forecasts.Skill assessment approaches are mostly adopted from meteorology and the analysis also compares probabilistic and deterministic aspects of EFAS. Furthermore, the utility of different skill scores is discussed and their strengths and shortcomings illustrated. The analysis shows the benefit of incorporating past forecasts in the probability analysis, for medium-range forecasts, which effectively increases the skill of the forecasts.

Early and effective flood warning is essential to initiate timely measures to reduce loss of life and economic damage. The availability of several global ensemble weather prediction systems through the “THORPEX Interactive Grand Global Ensemble” (TIGGE) archive provides an opportunity to explore new dimensions in early flood forecasting and warning. TIGGE data has been used as meteorological input to the European Flood Alert System (EFAS) for a case study of a flood event in Romania in October 2007. Results illustrate that awareness for this case of flooding could have been raised as early as 8 days before the event and how the subsequent forecasts provide increasing insight into the range of possible flood conditions. This first assessment of one flood event illustrates the potential value of the TIGGE archive and the grand‐ensembles approach to raise preparedness and thus to reduce the socio‐economic impact of floods.