Statistical and hydrodynamic models for the operational forecasting of floods in the Venice Lagoon |
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| Authors: | Jos Vieira Jakob Fns Giovanni Cecconi |
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| Institution: | José Vieira, Jakob Føns,Giovanni Cecconi |
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| Abstract: | The risk of flooding in Venice has increased strongly since the beginning of the century. To reduce the damage to the city and the negative impact on the activities in the lagoon, an accurate flood warning system is necessary. This system will also be fundamental during the construction and for the efficient operation of storm surge barriers covering the three existing inlets of the lagoon. In this context new operational statistical and hydrodynamic models have been developed. Forecast winds and pressure fields which constitute basic information for the warning system have been obtained through an ad hoc Limited Area Meteorological model. It has been demonstrated that, provided that this information is available on an operational basis, the implementation of a flood warning system for Venice using the models developed is feasible. The statistical model, which is based on a multiple regression technique, extends the forecasting range of the model presently in operation at the Centro Previsioni e Segnalazioni Maree del Comune di Venezia, from 3 hrs up to 24 hrs, and presents good accuracy (estimated mean absolute errors smaller than 10 cm) for short-term forecasts up to 9 hrs. The hydrodynamic model includes all the physical processes important for the simulation of water levels and currents in coastal and marine environments. The model set-up adopted covers the entire Adriatic Sea, with a grid spacing of 6 km. Special attention has been given to the positioning of the open boundary and to the correct reproduction of the main free oscillation of the Adriatic, which is responsible for the possible recurrence of flooding after the main storm has passed. The inclusion of this model in a flood warning system is mainly intended for long-term forecasts (> 24 hrs), and can typically be used to forecast up to 3–4 days ahead, with an estimated mean absolute error smaller than 20 cm. |
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