[1] The widespread flood event that affected northeastern and central Italy in November 1966, causing severe damages to vast populated areas including the historical towns of Florence and Venice, is revisited with a modeling approach, made possible by the availability of the ECMWF global reanalysis (ERA-40). A simulated forecasting chain consisting of the ECMWF global model, forcing a cascade of two mesoscale, limited area meteorological models apt to reach a convective resolving scale (about 2 km), is used to predict quantitative precipitation. A hydrological model, nested in the finer-scale meteorological model, is used to reproduce forecasted flood hydrographs for different river basins of the investigated areas. Predicted precipitation is in general very sensitive to initial conditions, especially when associated with convective activity, such as over central Italy, in the Arno river basin. Orographically enhanced precipitation, e.g., the one predicted in the eastern Alps, is quite stable and in good agreement with observations. Hydrological forecasts, made separately in different river basins, reflect the accuracy of the simulated precipitation.

Hydraulic risk maps provide the baseline for land use and emergency planning. Accordingly, they should convey clear information on the potential physical implications of the different hazards to the stakeholders. This paper presents a vulnerability criterion focused on human stability in a flow specifically devised for rapidly evolving floods where life, before than economic values, might be threatened. The human body is conceptualized as a set of cylinders and its stability to slipping and toppling is assessed by forces and moments equilibrium. Moreover, a depth threshold to consider drowning is assumed. In order to widen its scope of application, the model takes the destabilizing effect of local slope (so far disregarded in the literature) and fluid density into account. The resulting vulnerability classification could be naturally subdivided in three levels (low, medium, and high) that are limited by two stability curves for children and adults, respectively. In comparison with the most advanced literature conceptual approaches, the proposed model is weakly parameterized and the computed thresholds fit better the available experimental data sets. A code that implements the proposed algorithm is provided.

Mesoscale Alpine Programme Demonstration of Probabilistic Hydrological and Atmospheric Simulation of Flood Events (MAP D-PHASE) is a forecast demonstration project aiming at demonstrating recent improvements in the operational use of end-to-end forecasting system consisting of atmospheric models, hydrological prediction systems, nowcasting tools and warnings for end-users. Both deterministic and ensemble prediction systems (EPSs) have been implemented for the European Alps (atmospheric models) and a selection of mesoscale river basins (hydrological models) in Central Europe. A first insight into MAP D-PHASE with focus on operational ensemble hydrological simulations is presented here.

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International audienceDemonstration of probabilistic hydrological and atmospheric simulation of flood events in the Alpine region (D-PHASE) is made by the Forecast Demonstration Project in connection with the Mesoscale Alpine Programme (MAP). Its focus lies in the end-to-end flood forecasting in a mountainous region such as the Alps and surrounding lower ranges. Its scope ranges from radar observations and atmospheric and hydrological modeling to the decision making by the civil protection agents. More than 30 atmospheric high-resolution deterministic and probabilistic models coupled to some seven hydrological models in various combinations provided real-time online information. This information was available for many different catchments across the Alps over a demonstration period of 6 months in summer/ fall 2007. The Web-based exchange platform additionally contained nowcasting information from various operational services and feedback channels for the forecasters and end users. D-PHASE applications include objective model verification and intercomparison, the assessment of (subjective) end user feedback, and evaluation of the overall gain from the coupling of the various components in the end-to-end forecasting system

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