Preprints
https://doi.org/10.5194/nhess-2020-361
https://doi.org/10.5194/nhess-2020-361

  17 Nov 2020

17 Nov 2020

Review status: a revised version of this preprint is currently under review for the journal NHESS.

The prediction of floods in Venice: methods, models and uncertainty

Georg Umgiesser1,2, Marco Bajo1, Christian Ferrarin1, Andrea Cucco3, Piero Lionello4, Davide Zanchettin5, Alvise Papa6, Alessandro Tosoni6, Maurizio Ferla7, Elisa Coraci7, Sara Morucci7, Franco Crosato7, Andrea Bonometto7, Andrea Valentini8, Mirko Orlic9, Ivan D. Haigh10, Jacob Woge Nielsen11, Xavier Bertin12, André Bustorff Fortunato13, Begoña Pérez Gómez14, Enrique Alvarez Fanjul14, Denis Paradis15, Didier Jourdan16, Audrey Pasquet16, Baptiste Mourre17, Joaquín Tintoré17, and Robert J. Nicholls18 Georg Umgiesser et al.
  • 1ISMAR-CNR, Institute of Marine Sciences, National Research Council, Venice, Italy
  • 2Marine Research Institute, Klaipeda University, Klaipeda, Lithuania
  • 3CNR—IAS, National Research Council, Institute for the study of Anthropic impacts and Sustainability in the marine environment, Oristano, Italy
  • 4DiSTeBA - University of Salento and CMCC, Lecce, Italy
  • 5Ca' Foscari, University of Venice, Venice, Italy
  • 6CPSM, Centro Previsione e Segnalazione Maree - Protezione Civile, Venice, Italy
  • 7ISPRA, Istituto Superiore per la Protezione e la Ricerca Ambientale, Venezia, Italy
  • 8Arpae-SIMC – Agency for Prevention, Environment and Energy of Emilia-Romagna, Hydro-Meteo-Climate Service, Bologna, Italy
  • 9Department of Geophysics, Faculty of Science, University of Zagreb, Croatia
  • 10School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, UK
  • 11DMI – Danish Meteorological Institute, Copenhagen, Denmark
  • 12UMR 7266 LIENSs, CNRS-La Rochelle University, 2 rue Olympe de Gouges, 17000 La Rochelle, France
  • 13Laboratório Nacional de Engenharia Civil, Lisbon, Portugal
  • 14Puertos del Estado, Madrid, Spain
  • 15Direction des Opérations pour la Prévision, Département Marine et Océanographie, Météo-France, Toulouse, France
  • 16Shom (Service hydrographique et océanographique de la Marine), Toulouse, France
  • 17SOCIB, Balearic Islands Coastal Observing and Forecasting System, Mallorca, Spain
  • 18Tyndall Centre for Climate Change Research, University of East Anglia. Norwich, UK

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 relies crucially on a good flood forecasting system in order to protect the extensive cultural heritage, their population, and their economic activities. Storm surge forecasting systems are in place to warn the population of imminent flood threats. In the future, it will be of paramount importance to increase the reliability of these forecasting systems, especially with the new MOSE mobile barriers that will be completed by 2021, and 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 European storm surge forecasting is reviewed. The challenges that lie ahead for Venice and its forecasting systems are analyzed, especially in view of uncertainty. Some extreme events that happened in the past and were particularly difficult to forecast are also described.

Georg Umgiesser et al.

 
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Georg Umgiesser et al.

Georg Umgiesser et al.

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Short summary
The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review in storm surge forecasting, starting from examples in Europe, and focusing on the Adriatic Sea and the Venice Lagoon. We discuss the physics of storm surge, as well as the particular aspects of Venice, and new techniques in storm surge modeling. We also give recommendations on how a future forecasting system should look like.
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