Articles | Volume 23, issue 11
https://doi.org/10.5194/nhess-23-3585-2023
https://doi.org/10.5194/nhess-23-3585-2023
Research article
 | 
23 Nov 2023
Research article |  | 23 Nov 2023

A new European coastal flood database for low–medium intensity events

Marine Le Gal, Tomás Fernández-Montblanc, Enrico Duo, Juan Montes Perez, Paulo Cabrita, Paola Souto Ceccon, Véra Gastal, Paolo Ciavola, and Clara Armaroli

Related authors

Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines
Enrico Duo, Juan Montes, Marine Le Gal, Tomás Fernández-Montblanc, Paolo Ciavola, and Clara Armaroli
Nat. Hazards Earth Syst. Sci., 25, 13–39, https://doi.org/10.5194/nhess-25-13-2025,https://doi.org/10.5194/nhess-25-13-2025, 2025
Short summary

Related subject area

Sea, Ocean and Coastal Hazards
Advancing nearshore and onshore tsunami hazard approximation with machine learning surrogates
Naveen Ragu Ramalingam, Kendra Johnson, Marco Pagani, and Mario L. V. Martina
Nat. Hazards Earth Syst. Sci., 25, 1655–1679, https://doi.org/10.5194/nhess-25-1655-2025,https://doi.org/10.5194/nhess-25-1655-2025, 2025
Short summary
Untangling the waves: decomposing extreme sea levels in a non-tidal basin, the Baltic Sea
Marvin Lorenz, Katri Viigand, and Ulf Gräwe
Nat. Hazards Earth Syst. Sci., 25, 1439–1458, https://doi.org/10.5194/nhess-25-1439-2025,https://doi.org/10.5194/nhess-25-1439-2025, 2025
Short summary
Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA)
Lucas Terlinden-Ruhl, Anaïs Couasnon, Dirk Eilander, Gijs G. Hendrickx, Patricia Mares-Nasarre, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci., 25, 1353–1375, https://doi.org/10.5194/nhess-25-1353-2025,https://doi.org/10.5194/nhess-25-1353-2025, 2025
Short summary
Tsunami detection methods for ocean-bottom pressure gauges
Cesare Angeli, Alberto Armigliato, Martina Zanetti, Filippo Zaniboni, Fabrizio Romano, Hafize Başak Bayraktar, and Stefano Lorito
Nat. Hazards Earth Syst. Sci., 25, 1169–1185, https://doi.org/10.5194/nhess-25-1169-2025,https://doi.org/10.5194/nhess-25-1169-2025, 2025
Short summary
Using random forests to forecast daily extreme sea level occurrences at the Baltic Coast
Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci., 25, 1139–1162, https://doi.org/10.5194/nhess-25-1139-2025,https://doi.org/10.5194/nhess-25-1139-2025, 2025
Short summary

Cited articles

Alfieri, L., Salamon, P., Bianchi, A., Neal, J., Bates, P., and Feyen, L.: Advances in Pan-European Flood Hazard Mapping: Advances in Pan-European Flood Hazard Mapping, Hydrol. Process., 28, 4067–4077, https://doi.org/10.1002/hyp.9947, 2014. a
Alves, B., Schiavon, E., Armaroli, C., and Velegrakis, A.: Report on the Users' Requirements, Deliverable 2.3 – ECFAS project (GA-101004211), 2022. a
Athanasiou, P., van Dongeren, A., Giardino, A., Vousdoukas, M., Antolinez, J. A. A., and Ranasinghe, R.: A Clustering Approach for Predicting Dune Morphodynamic Response to Storms Using Typological Coastal Profiles: A Case Study at the Dutch Coast, Front. Mar. Sci., 8, 747754, https://doi.org/10.3389/fmars.2021.747754, 2021. a
Barnard, P. L., van Ormondt, M., Erikson, L. H., Eshleman, J., Hapke, C., Ruggiero, P., Adams, P. N., and Foxgrover, A. C.: Development of the Coastal Storm Modeling System (CoSMoS) for Predicting the Impact of Storms on High-Energy, Active-Margin Coasts, Nat. Hazards, 74, 1095–1125, https://doi.org/10.1007/s11069-014-1236-y, 2014. a
Bates, P. and De Roo, A.: A Simple Raster-Based Model for Flood Inundation Simulation, J. Hydrol., 236, 54–77, https://doi.org/10.1016/S0022-1694(00)00278-X, 2000. a, b, c
Download
Short summary
Assessing coastal hazards is crucial to mitigate flooding disasters. In this regard, coastal flood databases are valuable tools. This paper describes a new coastal flood map catalogue covering the entire European coastline, as well as the methodology to build it and its accuracy. The catalogue focuses on frequent extreme events and relies on synthetic scenarios estimated from local storm conditions. Flood-prone areas and regions sensitive to storm duration and water level peak were identified.
Share
Altmetrics
Final-revised paper
Preprint