The prediction of floods in Venice: methods, models and uncertainty (review article)

Umgiesser, Georg, Bajo, Marco, Ferrarin, Christian, Cucco, Andrea, Lionello, Piero, Zanchettin, Davide, Papa, Alvise, Tosoni, Alessandro, Ferla, Maurizio, Coraci, Elisa, Morucci, Sara, Crosato, Franco, Bonometto, Andrea, Valentini, Andrea, Orlić, Mirko, Haigh, Ivan D., Nielsen, Jacob Woge, Bertin, Xavier, Fortunato, André Bustorff, Pérez Gómez, Begoña, Alvarez Fanjul, Enrique, Paradis, Denis, Jourdan, Didier, Pasquet, Audrey, Mourre, Baptiste, Tintoré, Joaquín and Nicholls, Robert J. (2021) The prediction of floods in Venice: methods, models and uncertainty (review article). Natural Hazards and Earth System Science, 21 (8). pp. 2679-2704. ISSN 1684-9981

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Abstract

This paper reviews the state of the art in storm surge forecasting and its particular application in the northern Adriatic Sea. The city of Venice already depends on operational storm surge forecasting systems to warn the population and economy of imminent flood threats, as well as help to protect the extensive cultural heritage. This will be more important in the future, with the new mobile barriers called MOSE (MOdulo Sperimentale Elettromeccanico, Experimental Electromechanical Module) that will be completed by 2021. The barriers will depend on accurate storm surge forecasting to control their operation. In this paper, the physics behind the flooding of Venice is discussed, and the state of the art of storm surge forecasting in Europe is reviewed. The challenges for the surge forecasting systems are analyzed, especially in view of uncertainty. This includes consideration of selected historic extreme events that were particularly difficult to forecast. Four potential improvements are identified: (1) improve meteorological forecasts, (2) develop ensemble forecasting, (3) assimilation of water level measurements and (4) develop a multimodel approach.

Item Type: Article
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 02 Sep 2021 00:17
Last Modified: 21 Sep 2021 01:33
URI: https://ueaeprints.uea.ac.uk/id/eprint/81269
DOI: 10.5194/nhess-21-2679-2021

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