Articles | Volume 22, issue 7
https://doi.org/10.5194/nhess-22-2381-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-2381-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jul 2022
Research article |
| 19 Jul 2022
| 19 Jul 2022
Developing a framework for the assessment of current and future flood risk in Venice, Italy
Julius Schlumberger
CORRESPONDING AUTHOR
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Steinweg 1, 2628 CN Delft, the Netherlands
Deltares, Boussinesqweg 1, 2629 HV Delft, the Netherlands
Christian Ferrarin
ISMAR – Marine Science Institute, CNR – National Research Council of Italy, Castello 2737/F, 30122, Venice, Italy
Sebastiaan N. Jonkman
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Steinweg 1, 2628 CN Delft, the Netherlands
Manuel Andres Diaz Loaiza
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Steinweg 1, 2628 CN Delft, the Netherlands
JBA Consulting, St Philip's Courtyard, B46 3AD, Birmingham, United Kingdom
Alessandro Antonini
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Steinweg 1, 2628 CN Delft, the Netherlands
Sandra Fatorić
Faculty of Architecture and the Built Environment, Delft University of Technology, Julianalaan 134, 2628 BL Delft, the Netherlands
Related authors
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771, https://doi.org/10.5194/egusphere-2025-2771, 2025
This preprint is open for discussion and under review for Geoscience Communication (GC).
Short summary
Short summary
Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
Julius Schlumberger, Tristian Stolte, Helena Margaret Garcia, Antonia Sebastian, Wiebke Jäger, Philip Ward, Marleen de Ruiter, Robert Šakić Trogrlić, Annegien Tijssen, and Mariana Madruga de Brito
EGUsphere, https://doi.org/10.5194/egusphere-2025-850, https://doi.org/10.5194/egusphere-2025-850, 2025
Short summary
Short summary
The risk flood of flood impacts is dynamic as society continuously responds to specific events or ongoing developments. We analyzed 28 studies that assess such dynamics of vulnerability. Most research uses surveys and basic statistics data, while integrated, flexible models are seldom used. The studies struggle to link specific events or developments to the observed changes. Our findings highlight needs and possible directions towards a better assessment of vulnerability dynamics.
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771, https://doi.org/10.5194/egusphere-2025-2771, 2025
This preprint is open for discussion and under review for Geoscience Communication (GC).
Short summary
Short summary
Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
Julius Schlumberger, Tristian Stolte, Helena Margaret Garcia, Antonia Sebastian, Wiebke Jäger, Philip Ward, Marleen de Ruiter, Robert Šakić Trogrlić, Annegien Tijssen, and Mariana Madruga de Brito
EGUsphere, https://doi.org/10.5194/egusphere-2025-850, https://doi.org/10.5194/egusphere-2025-850, 2025
Short summary
Short summary
The risk flood of flood impacts is dynamic as society continuously responds to specific events or ongoing developments. We analyzed 28 studies that assess such dynamics of vulnerability. Most research uses surveys and basic statistics data, while integrated, flexible models are seldom used. The studies struggle to link specific events or developments to the observed changes. Our findings highlight needs and possible directions towards a better assessment of vulnerability dynamics.
Christian Ferrarin, Debora Bellafiore, Alejandro Paladio Hernandez, Irina Dinu, and Adrian Stanica
EGUsphere, https://doi.org/10.5194/egusphere-2025-606, https://doi.org/10.5194/egusphere-2025-606, 2025
Short summary
Short summary
We implemented a hydrodynamic model to the entire Danube Delta region consisting of the river network, coastal lagoons and part of the prodelta coastal sea. The model was applied to investigate the water distribution among the river branches, the dynamics of the coastal sea in front of the delta, the renewal capacity of the lagoons, the processes regulating the water exchange among the different water bodies and the potential impacts of lagoon-sea reconnection solutions.
Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
Nat. Hazards Earth Syst. Sci., 25, 335–351, https://doi.org/10.5194/nhess-25-335-2025, https://doi.org/10.5194/nhess-25-335-2025, 2025
Short summary
Short summary
Deep learning methods are increasingly used as surrogates for spatio-temporal flood models but struggle with generalization and speed. Here, we propose a multi-resolution approach using graph neural networks that predicts dike breach floods across different meshes, topographies, and boundary conditions with high accuracy and up to 1000× speed-ups. The model also generalizes to larger more complex case studies with just one additional simulation for fine-tuning.
Roderik van de Wal, Angélique Melet, Debora Bellafiore, Paula Camus, Christian Ferrarin, Gualbert Oude Essink, Ivan D. Haigh, Piero Lionello, Arjen Luijendijk, Alexandra Toimil, Joanna Staneva, and Michalis Vousdoukas
State Planet, 3-slre1, 5, https://doi.org/10.5194/sp-3-slre1-5-2024, https://doi.org/10.5194/sp-3-slre1-5-2024, 2024
Short summary
Short summary
Sea level rise has major impacts in Europe, which vary from place to place and in time, depending on the source of the impacts. Flooding, erosion, and saltwater intrusion lead, via different pathways, to various consequences for coastal regions across Europe. This causes damage to assets, the environment, and people for all three categories of impacts discussed in this paper. The paper provides an overview of the various impacts in Europe.
Emmanouil Flaounas, Stavros Dafis, Silvio Davolio, Davide Faranda, Christian Ferrarin, Katharina Hartmuth, Assaf Hochman, Aristeidis Koutroulis, Samira Khodayar, Mario Marcello Miglietta, Florian Pantillon, Platon Patlakas, Michael Sprenger, and Iris Thurnherr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2809, https://doi.org/10.5194/egusphere-2024-2809, 2024
Short summary
Short summary
Storm Daniel (2023) is one of the most catastrophic ones ever documented in the Mediterranean. Our results highlight the different dynamics and therefore the different predictability skill of precipitation, its extremes and impacts that have been produced in Greece and Libya, the two most affected countries. Our approach concerns a holistic analysis of the storm by articulating dynamics, weather prediction, hydrological and oceanographic implications, climate extremes and attribution theory.
Hanqing Xu, Elisa Ragno, Sebastiaan N. Jonkman, Jun Wang, Jeremy D. Bricker, Zhan Tian, and Laixiang Sun
Hydrol. Earth Syst. Sci., 28, 3919–3930, https://doi.org/10.5194/hess-28-3919-2024, https://doi.org/10.5194/hess-28-3919-2024, 2024
Short summary
Short summary
A coupled statistical–hydrodynamic model framework is employed to quantitatively evaluate the sensitivity of compound flood hazards to the relative timing of peak storm surges and rainfall. The findings reveal that the timing difference between these two factors significantly affects flood inundation depth and extent. The most severe inundation occurs when rainfall precedes the storm surge peak by 2 h.
Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 27, 4227–4246, https://doi.org/10.5194/hess-27-4227-2023, https://doi.org/10.5194/hess-27-4227-2023, 2023
Short summary
Short summary
To overcome the computational cost of numerical models, we propose a deep-learning approach inspired by hydraulic models that can simulate the spatio-temporal evolution of floods. We show that the model can rapidly predict dike breach floods over different topographies and breach locations, with limited use of ground-truth data.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
Short summary
Short summary
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Marco Bajo, Christian Ferrarin, Georg Umgiesser, Andrea Bonometto, and Elisa Coraci
Ocean Sci., 19, 559–579, https://doi.org/10.5194/os-19-559-2023, https://doi.org/10.5194/os-19-559-2023, 2023
Short summary
Short summary
This work uses a hydrodynamic model which assimilates in situ data to reproduce tides, surges, and seiches in the Mediterranean basin. Furthermore, we study the periods of the barotropic modes of the Mediterranean and Adriatic basins. This research aims to improve the forecasting and reanalysis for operational warning and climatological studies. It aims also to reach a better knowledge of these sea level components in this area.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
Short summary
Short summary
The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 26, 4345–4378, https://doi.org/10.5194/hess-26-4345-2022, https://doi.org/10.5194/hess-26-4345-2022, 2022
Short summary
Short summary
Deep learning methods have been increasingly used in flood management to improve traditional techniques. While promising results have been obtained, our review shows significant challenges in building deep learning models that can (i) generalize across multiple scenarios, (ii) account for complex interactions, and (iii) perform probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in deep learning to flood mapping.
Manuel Andres Diaz Loaiza, Jeremy D. Bricker, Remi Meynadier, Trang Minh Duong, Rosh Ranasinghe, and Sebastiaan N. Jonkman
Nat. Hazards Earth Syst. Sci., 22, 345–360, https://doi.org/10.5194/nhess-22-345-2022, https://doi.org/10.5194/nhess-22-345-2022, 2022
Short summary
Short summary
Extratropical cyclones are one of the major causes of coastal floods in Europe and the world. Understanding the development process and the flooding of storm Xynthia, together with the damages that occurred during the storm, can help to forecast future losses due to other similar storms. In the present paper, an analysis of shallow water variables (flood depth, velocity, etc.) or coastal variables (significant wave height, energy flux, etc.) is done in order to develop damage curves.
Christopher H. Lashley, Sebastiaan N. Jonkman, Jentsje van der Meer, Jeremy D. Bricker, and Vincent Vuik
Nat. Hazards Earth Syst. Sci., 22, 1–22, https://doi.org/10.5194/nhess-22-1-2022, https://doi.org/10.5194/nhess-22-1-2022, 2022
Short summary
Short summary
Many coastlines around the world have shallow foreshores (e.g. salt marshes and mudflats) that reduce storm waves and the risk of coastal flooding. However, most of the studies that tried to quantify this effect have excluded the influence of very long waves, which often dominate in shallow water. Our newly developed framework addresses this oversight and suggests that safety along these coastlines may be overestimated, since these very long waves are largely neglected in flood risk assessments.
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-614, https://doi.org/10.5194/hess-2021-614, 2021
Manuscript not accepted for further review
Short summary
Short summary
Deep Learning methods have been increasingly used in flood mapping as an alternative to traditional modeling techniques. While promising results have been obtained, our review shows significant challenges in building Deep Learning models that can generalize across multiple scenarios, account for complex interactions, and provide probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in Deep Learning.
Davide Zanchettin, Sara Bruni, Fabio Raicich, Piero Lionello, Fanny Adloff, Alexey Androsov, Fabrizio Antonioli, Vincenzo Artale, Eugenio Carminati, Christian Ferrarin, Vera Fofonova, Robert J. Nicholls, Sara Rubinetti, Angelo Rubino, Gianmaria Sannino, Giorgio Spada, Rémi Thiéblemont, Michael Tsimplis, Georg Umgiesser, Stefano Vignudelli, Guy Wöppelmann, and Susanna Zerbini
Nat. Hazards Earth Syst. Sci., 21, 2643–2678, https://doi.org/10.5194/nhess-21-2643-2021, https://doi.org/10.5194/nhess-21-2643-2021, 2021
Short summary
Short summary
Relative sea level in Venice rose by about 2.5 mm/year in the past 150 years due to the combined effect of subsidence and mean sea-level rise. We estimate the likely range of mean sea-level rise in Venice by 2100 due to climate changes to be between about 10 and 110 cm, with an improbable yet possible high-end scenario of about 170 cm. Projections of subsidence are not available, but historical evidence demonstrates that they can increase the hazard posed by climatically induced sea-level rise.
Piero Lionello, David Barriopedro, Christian Ferrarin, Robert J. Nicholls, Mirko Orlić, Fabio Raicich, Marco Reale, Georg Umgiesser, Michalis Vousdoukas, and Davide Zanchettin
Nat. Hazards Earth Syst. Sci., 21, 2705–2731, https://doi.org/10.5194/nhess-21-2705-2021, https://doi.org/10.5194/nhess-21-2705-2021, 2021
Short summary
Short summary
In this review we describe the factors leading to the extreme water heights producing the floods of Venice. We discuss the different contributions, their relative importance, and the resulting compound events. We highlight the role of relative sea level rise and the observed past and very likely future increase in extreme water heights, showing that they might be up to 160 % higher at the end of the 21st century than presently.
Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 14, 645–659, https://doi.org/10.5194/gmd-14-645-2021, https://doi.org/10.5194/gmd-14-645-2021, 2021
Short summary
Short summary
The problem of the optimization of ocean monitoring networks is tackled through the implementation of data assimilation techniques in a numerical model. The methodology has been applied to the tide gauge network in the Lagoon of Venice (Italy). The data assimilation methods allow identifying the minimum number of stations and their distribution that correctly represent the lagoon's dynamics. The methodology is easily exportable to other environments and can be extended to other variables.
Erik C. van Berchum, Mathijs van Ledden, Jos S. Timmermans, Jan H. Kwakkel, and Sebastiaan N. Jonkman
Nat. Hazards Earth Syst. Sci., 20, 2633–2646, https://doi.org/10.5194/nhess-20-2633-2020, https://doi.org/10.5194/nhess-20-2633-2020, 2020
Short summary
Short summary
Flood risk management is especially complicated in coastal cities. The complexity of multiple flood hazards in a rapidly changing urban environment leads to a situation with many different potential measures and future scenarios. This research demonstrates a new model capable of quickly simulating flood impact and comparing many different strategies. This is applied to the city of Beira, where it was able to provide new insights into the local flood risk and potential strategies.
Cited articles
Ahn, J., Na, Y., and Park, S W.: Development of Two-Dimensional Inundation
Modelling Process using MIKE21 Model, KSCE J. Civ. Eng., 23, 3968–3977, https://doi.org/10.1007/s12205-019-1586-9, 2019. a, b
Amadio, M., Mysiak, J., Carrera, L., and Koks, E.: Improving flood damage
assessment models in Italy, Nat. Hazards, 82, 2075–2088,
https://doi.org/10.1007/s11069-016-2286-0, 2016. a
Aqua Grande: AquaGranda – A Digital Community Memory, https://www.aquagrandainvenice.it/en/about (last access: 12 May 2021), 2020. a
ArcGis: Map Venice in 2D and 3D, https://learn.arcgis.com/en/projects/map-venice-in-2d-and-3d/ (last access: 8 April 2021), 2020. a
Arrighi, C., Brugioni, M., Castelli, F., Franceschini, S., and Mazzanti, B.:
Urban micro-scale flood risk estimation with parsimonious hydraulic modelling
and census data, Nat. Hazards Earth Syst. Sci., 13, 1375–1391,
https://doi.org/10.5194/nhess-13-1375-2013, 2013. a
Arrighi, C., Brugioni, M., Castelli, F., Franceschini, S., and Mazzanti, B.:
Flood risk assessment in art cities: the exemplary case of Florence (Italy),
J. Flood Risk Manage., 11, S616–S631, https://doi.org/10.1111/jfr3.12226, 2018a. a, b, c, d
Arrighi, C., Rossi, L., Trasforini, E., Rudari, R., Ferraris, L., Brugioni, M., Franceschini, S., and Castelli, F.: Quantification of flood risk mitigation benefits: A building-scale damage assessment through the RASOR platform, J. Environ. Manage., 207, 92–104, https://doi.org/10.1016/j.jenvman.2017.11.017, 2018b. a
Battistin, D. and Canestrelli, P.: 1872–2004: la serie storica delle maree a
Venezia, Instituzione Centro Previsioni e Segnalazioni Maree, VEA0695159, https://binp.regione.veneto.it/SebinaOpac/resource/18722004-la-serie-storica-delle-maree-a-venezia/VIA1614330# (last access: 15 July 2022), 2006. a
Berchum, E. C., Mobley, W., Jonkman, S. N., Timmermans, J. S., Kwakkel, J. H., and Brody, S. D.: Evaluation of flood risk reduction strategies through
combinations of interventions, J. Flood Risk Manage., 12, e12506, https://doi.org/10.1111/jfr3.12506, 2019. a
Bryant, K. and Akbar, M.: An Exploration of Wind Stress Calculation Techniques in Hurricane Storm Surge Modeling, J. Mar. Sci. Eng., 4, 65–90, https://doi.org/10.3390/jmse4030058, 2016. a
Caporin, M. and Fontini, F.: The Value of Protecting Venice from the Acqua Alta Phenomenon under Different Local Sea Level Rises, 20 p.,
https://doi.org/10.2139/ssrn.2397933, 2014. a, b
Cardona, O.-D., van Aalst, M. K., Birkmann, J., Fordham, M., McGregor, G.,
Perez, R., Pulwarty, R. S., Schipper, E. L. F., Tan Sinh, B., Décamps, H., Keim, M., Davis, I., Ebi, K. L., Lavell, A., Mechler, R., Murray, V., Pelling, M., Pohl, J., Smith, A.-O., and Thomalla, F.: Determinants of Risk: Exposure and Vulnerability, in: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 65–108, https://doi.org/10.1017/CBO9781139177245.005, 2012. a
Cavaleri, L., Bajo, M., Barbariol, F., Bastianini, M., Benetazzo, A., Bertotti, L., Chiggiato, J., Davolio, S., Ferrarin, C., Magnusson, L., Papa, A., Pezzutto, P., Pomaro, A., and Umgiesser, G.: The October 29, 2018 storm in Northern Italy – An exceptional event and its modeling, Prog. Oceanogr., 178, 102178, https://doi.org/10.1016/j.pocean.2019.102178, 2019. a
Cavallaro, L., Iuppa, C., and Foti, E.: Effect of Partial Use of Venice Flood
Barriers, J. Mar. Sci. Eng., 5, 58, https://doi.org/10.3390/jmse5040058, 2017. a, b, c
Cellerino, R., Giancola, L., and Anghinelli, S.: Venezia atlantide: L'impatto
economico delle acque alte, in: vol. 80 of Economia, Sezione 5, Ricerche di
economia applicata, Angeli, Milano, 1998. a
City of Venice: Città di Venezia | Comune di Venezia – Portale dei
servizi, https://portale.comune.venezia.it/ (last access: 28 March 2021), 2000. a
City of Venice: Sistema Informativo Territoriale, https://geoportale.comune.venezia.it/Html5Viewer/index.html?viewer=GeoPortale.Geoportale&LOCALE=IT-it, last access: 5 July 2021. a
Colamussi, A.: Venice high water barriers problems analysis and design
approach, in: Proceedings of the Short Course on Design and Reliability of
Coastal Structures, Venice, 645–667,
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1007.3969&rep=rep1&type=pdf (last access: 4 April 2021), 1992. a
Commune Venezia: Dati urbanistica, https://portale.comune.venezia.it/content/dati-urbanistica (last access: 04 April, 2021), 2014. a
Comune di Venezia: Rischio Idraulico,
https://www.comune.venezia.it/it/content/rischio-idraulico (last access date: 15 June, 2021), 2016. a
D'Alpaos, L. and Defina, A.: Mathematical modeling of tidal hydrodynamics in
shallow lagoons: A review of open issues and applications to the Venice lagoon, Comput. Geosci., 33, 476–496, https://doi.org/10.1016/j.cageo.2006.07.009, 2007. a
Diaz Loaiza, M. A., Bricker, J. D., Meynadier, R., Duong, T. M., Ranasinghe,
R., and Jonkman, S. N.: Development of damage curves for buildings near La
Rochelle during storm Xynthia based on insurance claims and hydrodynamic
simulations, Nat. Hazards Earth Syst. Sci., 22, 345–360,
https://doi.org/10.5194/nhess-22-345-2022, 2022. a
Drdácký, M. F.: Flood Damage to Historic Buildings and Structures,
J. Perform. Construct. Facil., 24, 439–445, https://doi.org/10.1061/(ASCE)CF.1943-5509.0000065, 2010. a, b
EMODnet: EMODnet Digital Bathymetry (DTM) – European Union Open Data Portal,
https://data.europa.eu/euodp/en/data/dataset/EMODnet_bathymetry (last access: 12 February 2021), 2018. a
European Commission: EUR-Lex – 32007L0060 – EN – EUR-Lex,
https://eur-lex.europa.eu/eli/dir/2007/60/oj (last access: 18 October 2021), 2007. a
Fatorić, S. and Seekamp, E.: A measurement framework to increase
transparency in historic preservation decision-making under changing climate
conditions, J. Cult. Herit., 30, 168–179, https://doi.org/10.1016/j.culher.2017.08.006, 2018. a
Ferrarin, C. and Umgiesser, G.: Hydrodynamic modeling of a coastal lagoon: The Cabras lagoon in Sardinia, Italy, Ecol. Model., 188, 340–357,
https://doi.org/10.1016/j.ecolmodel.2005.01.061, 2005. a
Ferrarin, C., Cucco, A., Umgiesser, G., Bellafiore, D., and Amos, C. L.:
Modelling fluxes of water and sediment between Venice Lagoon and the sea,
Cont. Shelf Res., 30, 904–914, https://doi.org/10.1016/j.csr.2009.08.014, 2010. a
Ferrarin, C., Tomasin, A., Bajo, M., Petrizzo, A., and Umgiesser, G.: Tidal
changes in a heavily modified coastal wetland, Cont. Shelf Res., 101, 22–33, https://doi.org/10.1016/j.csr.2015.04.002, 2015. a, b
Ferrarin, C., Bajo, M., Benetazzo, A., Cavaleri, L., Chiggiato, J., Davison,
S., Davolio, S., Lionello, P., Orlić, M., and Umgiesser, G.: Local and
large-scale controls of the exceptional Venice floods of November 2019,
Prog. Oceanogr., 102628, https://doi.org/10.1016/j.pocean.2021.102628, 2021. a, b
Fontini, F., Umgiesser, G., and Vergano, L.: The Role of Ambiguity in the
Evaluation of the Net Benefits of the MOSE System in the Venice Lagoon,
“Marco Fanno” Working Papers, 69, 1964–1972, https://doi.org/10.1016/j.ecolecon.2010.05.008, 2008. a, b
Gallien, T. W., Sanders, B. F., and Flick, R. E.: Urban coastal flood
prediction: Integrating wave overtopping, flood defenses and drainage, Coast. Eng., 91, 18–28, https://doi.org/10.1016/j.coastaleng.2014.04.007, 2014. a
Gerl, T., Kreibich, H., Franco, G., Marechal, D., and Schröter, K.: A
Review of Flood Loss Models as Basis for Harmonization and Benchmarking, PLOS
ONE, 11, e0159791, https://doi.org/10.1371/journal.pone.0159791, 2016. a, b
Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S. J., Marzeion, B., Fettweis, X., Ionescu, C., and Levermann, A.: Coastal
flood damage and adaptation costs under 21st century sea-level rise, P. Natl. Acad. Sci. USA, 111, 3292–3297, https://doi.org/10.1073/pnas.1222469111, 2014. a
Hudson, P., Botzen, W. W., Feyen, L., and Aerts, J. C.: Incentivising flood
risk adaptation through risk based insurance premiums: Trade-offs between
affordability and risk reduction, Ecol. Econ., 125, 1–13,
https://doi.org/10.1016/j.ecolecon.2016.01.015, 2016. a
Huijbregts, Z., van Schijndel, J. W. M., Schellen, H. L., and Blades, N.:
Hygrothermal modelling of flooding events within historic buildings, J. Build. Phys., 38, 170–187, https://doi.org/10.1177/1744259114532613, 2014. a, b
IPCC, 2021: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth
Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A.,
Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E.,
Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA, In press, https://www.ipcc.ch/report/ar6/wg1/ (last access: 13 March 2022), 2021. a
Istituto Superiore per la Protezione
e la Ricerca Ambientale: Le stazioni meteo-mareografiche, https://www.venezia.isprambiente.it/rete-meteo-mareografica, last access: 18 May 2021. a
ISTAT: Basi territoriali e variabili censuarie,
https://www.istat.it/it/archivio/104317 (last access: 5 June 2021), 2020. a
Jordà, G., Gomis, D., and Marcos, M.: Comment on “Storm surge frequency
reduction in Venice under climate change” by Troccoli et al, Climatic Change, 113, 1081–1087, https://doi.org/10.1007/s10584-011-0349-5, 2012. a
Kelman, I. and Spence, R.: An overview of flood actions on buildings, Eng. Geol., 73, 297–309, https://doi.org/10.1016/j.enggeo.2004.01.010, 2004. a
Kreibich, H., Seifert, I., Thieken, A. H., Lindquist, E., Wagner, K., and Merz, B.: Recent changes in flood preparedness of private households and businesses in Germany, Reg. Environ. Change, 11, 59–71,
https://doi.org/10.1007/s10113-010-0119-3, 2011. a
Kreibich, H., Bubeck, P., van Vliet, M., and de Moel, H.: A review of
damage-reducing measures to manage fluvial flood risks in a changing climate,
Mitig. Adapt. Strat. Global Change, 20, 967–989, https://doi.org/10.1007/s11027-014-9629-5, 2015. a
Lionello, P., Barriopedro, D., Ferrarin, C., Nicholls, R. J., Orlić, M.,
Raicich, F., Reale, M., Umgiesser, G., Vousdoukas, M., and Zanchettin, D.:
Extreme floods of Venice: characteristics, dynamics, past and future
evolution (review article), Nat. Hazards Earth Syst. Sci., 21, 2705–2731, https://doi.org/10.5194/nhess-21-2705-2021, 2021. a
Liu, X. J., Zhong, D. H., Tong, D. W., Zhou, Z. Y., Ao, X. F., and Li, W. Q.:
Dynamic visualisation of storm surge flood routing based on three-dimensional
numerical simulation, J. Flood Risk Manage., 11, S729–S749, https://doi.org/10.1111/jfr3.12252, 2018. a
López-Marrero, T.: An integrative approach to study and promote natural
hazards adaptive capacity: a case study of two flood-prone communities in
Puerto Rico, Geogr. J., 176, 150–163, https://doi.org/10.1111/j.1475-4959.2010.00353.x, 2010. a
Madricardo, F., Foglini, F., Kruss, A., Ferrarin, C., Pizzeghello, N. M.,
Murri, C., Rossi, M., Bajo, M., Bellafiore, D., Campiani, E., Fogarin, S.,
Grande, V., Janowski, L., Keppel, E., Leidi, E., Lorenzetti, G., Maicu, F.,
Maselli, V., Mercorella, A., Montereale Gavazzi, G., Minuzzo, T., Pellegrini, C., Petrizzo, A., Prampolini, M., Remia, A., Rizzetto, F., Rovere, M., Sarretta, A., Sigovini, M., Sinapi, L., Umgiesser, G., and Trincardi, F.: High resolution multibeam and hydrodynamic datasets of tidal channels and inlets of the Venice Lagoon, Scient. Data, 4, 170121,
https://doi.org/10.1038/sdata.2017.121, 2017. a, b
Martyr-Koller, R. C., Kernkamp, H., van Dam, A., van der Wegen, M., Lucas, L. V., Knowles, N., Jaffe, B., and Fregoso, T. A.: Application of an unstructured 3D finite volume numerical model to flows and salinity dynamics in the San Francisco Bay-Delta, Estuarine, Coast. Shelf Sci., 192, 86–107, https://doi.org/10.1016/j.ecss.2017.04.024, 2017. a
Međugorac, I., Pasarić, M., and Güttler, I.: Will the wind
associated with the Adriatic storm surges change in future climate?,
Theor. Appl. Climatol., 143, 1–18, https://doi.org/10.1007/s00704-020-03379-x, 2020. a
Merz, B. and Thieken, A. H.: Flood risk curves and uncertainty bounds, Nat.
Hazards, 51, 437–458, https://doi.org/10.1007/s11069-009-9452-6, 2009. a, b, c, d
Molinari, D. and Scorzini, A. R.: On the Influence of Input Data Quality to
Flood Damage Estimation: The Performance of the INSYDE Model, Water, 9, 688,
https://doi.org/10.3390/w9090688, 2017. a
Molinari, D., Scorzini, A. R., Arrighi, C., Carisi, F., Castelli, F.,
Domeneghetti, A., Gallazzi, A., Galliani, M., Grelot, F., Kellermann, P.,
Kreibich, H., Mohor, G. S., Mosimann, M., Natho, S., Richert, C., Schroeter,
K., Thieken, A. H., Zischg, A. P., and Ballio, F.: Are flood damage models
converging to “reality”? Lessons learnt from a blind test, Nat. Hazards
Earth Syst. Sci., 20, 2997–3017, https://doi.org/10.5194/nhess-20-2997-2020, 2020. a, b, c
Molinaroli, E., Guerzoni, S., and Suman, D.: Adaptations to Sea Level Rise: A
Tale of Two Cities – Venice and Miami, MarXiv, https://doi.org/10.31230/osf.io/73a25, 2018. a, b
Mooyaart, L. F. and Jonkman, S. N.: Overview and Design Considerations of Storm Surge Barriers, J. Waterway Port, Coast. Ocean Eng., 143, 06017001, https://doi.org/10.1061/(ASCE)WW.1943-5460.0000383, 2017. a
Morucci, S., Coraci, E., Crosato, F., and Ferla, M.: Extreme events in Venice
and in the North Adriatic Sea: 28–29 October 2018, Rendiconti Lincei, Scienze Fisiche e Naturali, 31, 113–122, https://doi.org/10.1007/s12210-020-00882-1,
2020. a, b
Nunes, P. A. L. D., Breil, M., and Gambarelli, G.: Economic Valuation of on
Site Material Damages of High Water on Economic Activities based in the City
of Venice: Results from a Dose-Response-Expert-Based Valuation Approach,
Social Science Research Network, https://doi.org/10.2139/ssrn.702965, 2005. a, b
Patt, H. and Jüpner, R., eds.: Hochwasser-Handbuch: Auswirkungen und
Schutz, in: 2. aufl. 2013, neu bearb. Edn., Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-28191-4, 2013. a
Penning-Rowsell, E., Johnson, C., Tunstall, S., Tapsell, S., Morris, J.,
Chatterton, J., and Green, C.: The Benefits of Flood and Coastal Risk
Management: A Handbook of Assessment Techniques, Middlesex University Press, ISBN 1904750516, 2005. a
Regione del Veneto: Prezzario regionale on-line 2019, https://www.regione.veneto.it/web/lavori-pubblici/prezzario-online-2019 (last access: 20 June 2021), 2019. a
Roland, A., Cucco, A., Ferrarin, C., Hsu, T.-W., Liau, J.-M., Ou, S.-H.,
Umgiesser, G., and Zanke, U.: On the development and verification of a 2-D coupled wave-current model on unstructured meshes, J. Mar. Syst., 78, S244–S254, https://doi.org/10.1016/j.jmarsys.2009.01.026, 2009. a
Sai, H. A., Tabata, T., Hiramatsu, K., Harada, M., and Luong, N. C.: An optimal scenario for the emergency solution to protect Hanoi Capital from the Red River floodwater using Van Coc Lake, J. Flood Risk Manage., 13, 12661-1-20, https://doi.org/10.1111/jfr3.12661, 2020. a
Sarretta, A., Pillon, S., Molinaroli, E., Guerzoni, S., and Fontolan, G.:
Sediment budget in the Lagoon of Venice, Italy, Cont. Shelf Res., 30, 934–949, https://doi.org/10.1016/J.CSR.2009.07.002, 2010. a
Schlumberger, J., Ferrarin, C., Jonkman, S., Diaz Loaiza, S.N., Antonini, A., Fatoric, S.: Outputfiles and processing codes to produce the results of this paper, OneDrive [code] and [data set], https://1drv.ms/u/s!AujDMT3F11JwgpEoTj2zfvrJqDcOdA?e=dY2c6O (last access: 28 May 2022), 2021. a
Smith, S. D. and Banke, E. G.: Variation of the sea surface drag coefficient
with wind speed, Q. J. Roy. Meteorol. Soc., 101, 665–673, https://doi.org/10.1002/qj.49710142920, 1975. a
Tambroni, N. and Seminara, G.: Are inlets responsible for the morphological
degradation of Venice Lagoon?, J. Geophys. Res.-Earth, 111, 13, https://doi.org/10.1029/2005JF000334, 2006. a
Teng, J., Jakeman, A. J., Vaze, J., Croke, B., Dutta, D., and Kim, S.: Flood
inundation modelling: A review of methods, recent advances and uncertainty
analysis, Environ. Model. Softw., 90, 201–216,
https://doi.org/10.1016/j.envsoft.2017.01.006, 2017. a
Thieken, A., Piroth, K., Schwarz, J., Schwarze, R., and Müller, M.: Methods for the evaluation of direct and indirect flood losses, in: 4th International Symposium on Flood Defence:4th International Symposium on Flood Defence: Managing Flood Risk, Reliability and Vulnerability,
https://www.researchgate.net/publication/259273112_Methods_for_the_evaluation_of_direct_and_indirect_flood_losses, (last access: 13 December 2021), 2022. a
Tiggeloven, T., de Moel, H., Winsemius, H. C., Eilander, D., Erkens, G.,
Gebremedhin, E., Diaz Loaiza, A., Kuzma, S., Luo, T., Iceland, C., Bouwman,
A., van Huijstee, J., Ligtvoet, W., and Ward, P. J.: Global-scale
benefit–cost analysis of coastal flood adaptation to different flood risk
drivers using structural measures, Nat. Hazards Earth Syst. Sci., 20, 1025–1044, https://doi.org/10.5194/nhess-20-1025-2020, 2020. a
Tognin, D., Finotello, A., D'Alpaos, A., Viero, D. P., Pivato, M., Mel, R. A., Defina, A., Bertuzzo, E., Marani, M., and Carniello, L.: Loss of geomorphic diversity in shallow tidal embayments promoted by storm-surge barriers, Sci. Adv., 8, eabm8446, https://doi.org/10.1126/sciadv.abm8446, 2022. a
Umgiesser, G.: The impact of operating the mobile barriers in Venice (MOSE)
under climate change, J. Nat. Conserv., 54, 125783, https://doi.org/10.1016/j.jnc.2019.125783, 2020. a, b
Umgiesser, G. and Matticchio, B.: Simulating the mobile barrier (MOSE)
operation in the Venice Lagoon, Italy: global sea level rise and its implication for navigation, Ocean Dynam., 56, 320–332, https://doi.org/10.1007/s10236-006-0071-4, 2006. a, b, c, d
Umgiesser, G., Canu, D. M., Cucco, A., and Solidoro, C.: A finite element model for the Venice Lagoon. Development, set up, calibration and validation,
J. Mar. Syst., 51, 123–145, https://doi.org/10.1016/j.jmarsys.2004.05.009, 2004. a
Umgiesser, G., Bajo, M., Ferrarin, C., Cucco, A., Lionello, P., Zanchettin, D., Papa, A., Tosoni, A., Ferla, M., Coraci, E., Morucci, S., Crosato, F.,
Bonometto, A., Valentini, A., Orlić, M., Haigh, I. D., Nielsen, J. W.,
Bertin, X., Fortunato, A. B., Pérez Gómez, B., Alvarez Fanjul, E., Paradis, D., Jourdan, D., Pasquet, A., Mourre, B., Tintoré, J., and
Nicholls, R. J.: The prediction of floods in Venice: methods, models and
uncertainty (review article), Nat. Hazards Earth Syst. Sci., 21, 2679–2704, https://doi.org/10.5194/nhess-21-2679-2021, 2021. a, b, c, d
Vergano, L. and Nunes, P. A. L. D.: Analysis and evaluation of ecosystem
resilience: an economic perspective with an application to the Venice lagoon,
Biodivers. Conserv., 16, 3385–3408, https://doi.org/10.1007/s10531-006-9085-y, 2007. a
Vousdoukas, M. I., Mentaschi, L., Hinkel, J., Ward, P. J., Mongelli, I.,
Ciscar, J.-C., and Feyen, L.: Economic motivation for raising coastal flood
defenses in Europe, Nat. Commun., 11, 2119, https://doi.org/10.1038/s41467-020-15665-3, 2020. a
Vrancken, J., van den Berg, J., and Dos Santos Soares, M.: Human factors in system reliability: lessons learnt from the Maeslant storm surge barrier in
The Netherlands, Int. J. Crit. Infrastruct., 4, 418–429, 2008. a
Wang, J.-J.: Flood risk maps to cultural heritage: Measures and process, J. Cult. Herit., 16, 210–220, https://doi.org/10.1016/j.culher.2014.03.002, 2015. a
Xing, Y., Liang, Q., Wang, G., Ming, X., and Xia, X.: City-scale hydrodynamic
modelling of urban flash floods: the issues of scale and resolution, Nat.
Hazards, 96, 473–496, https://doi.org/10.1007/s11069-018-3553-z, 2019. a, b, c
Yin, J., Jonkman, S., Lin, N., Yu, D., Aerts, J., Wilby, R., Pan, M., Wood, E., Bricker, J., Ke, Q., Zeng, Z., Zhao, Q., Ge, J., and Wang, J.: Flood Risks in Sinking Delta Cities: Time for a Reevaluation?, Earth's Future, 8,
e2020EF00161, https://doi.org/10.1029/2020EF001614, 2020. a
Zampato, L., Bajo, M., Canestrelli, P., and Umgiesser, G.: Storm surge
modelling in Venice: two years of operational results, J. Operat. Oceanogr., 9, s46–s57, https://doi.org/10.1080/1755876X.2015.1118804, 2016. a, b
Zanchettin, D., Bruni, S., Raicich, F., Lionello, P., Adloff, F., Androsov, A., Antonioli, F., Artale, V., Carminati, E., Ferrarin, C., Fofonova, V.,
Nicholls, R. J., Rubinetti, S., Rubino, A., Sannino, G., Spada, G., Thiéblemont, R., Tsimplis, M., Umgiesser, G., Vignudelli, S., Wöppelmann, G., and Zerbini, S.: Sea-level rise in Venice: historic and
future trends (review article), Nat. Hazards Earth Syst. Sci.,
21, 2643–2678, https://doi.org/10.5194/nhess-21-2643-2021, 2021. a, b
Short summary
Flooding has serious impacts on the old town of Venice. This paper presents a framework combining a flood model with a flood-impact model to support improving protection against future floods in Venice despite the recently built MOSE barrier. Applying the framework to seven plausible flood scenarios, it was found that individual protection has a significant damage-mediating effect if the MOSE barrier does not operate as anticipated. Contingency planning thus remains important in Venice.
Flooding has serious impacts on the old town of Venice. This paper presents a framework...
Altmetrics
Final-revised paper
Preprint