Articles | Volume 22, issue 10
https://doi.org/10.5194/nhess-22-3167-2022
© 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-22-3167-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2022
Research article |
| 06 Oct 2022
| 06 Oct 2022
Partitioning the contributions of dependent offshore forcing conditions in the probabilistic assessment of future coastal flooding
BRGM, 3 av. C. Guillemin, 45060 Orléans CEDEX 2, France
Deborah Idier
BRGM, 3 av. C. Guillemin, 45060 Orléans CEDEX 2, France
Remi Thieblemont
BRGM, 3 av. C. Guillemin, 45060 Orléans CEDEX 2, France
Goneri Le Cozannet
BRGM, 3 av. C. Guillemin, 45060 Orléans CEDEX 2, France
François Bachoc
Institut de Mathématiques de Toulouse, 118 Rte de Narbonne, 31400 Toulouse, France
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This study examines how tropical cyclones cause coastal flooding by combining waves and sea level changes over time. Using long-term storm data for Guadeloupe, we simulated realistic storm evolution rather than relying on single peak values. The results show that accounting for timing reduces errors in estimating extreme flood levels and reveals that wave-driven effects dominate the most severe events, improving reliability for coastal risk planning.
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Characterizing extreme wave environments caused by tropical cyclones in the Caribbean Sea near Guadeloupe is difficult because cyclones rarely pass near the location of interest. STM-E (space-time maxima and exposure) model utilizes wave data during cyclones on a spatial neighbourhood. Long-duration wave data generated from a database of synthetic tropical cyclones are used to evaluate the performance of STM-E. Results indicate STM-E provides estimates with small bias and realistic uncertainty.
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This study examines how tropical cyclones cause coastal flooding by combining waves and sea level changes over time. Using long-term storm data for Guadeloupe, we simulated realistic storm evolution rather than relying on single peak values. The results show that accounting for timing reduces errors in estimating extreme flood levels and reveals that wave-driven effects dominate the most severe events, improving reliability for coastal risk planning.
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Ryota Wada, Jeremy Rohmer, Yann Krien, and Philip Jonathan
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Short summary
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Characterizing extreme wave environments caused by tropical cyclones in the Caribbean Sea near Guadeloupe is difficult because cyclones rarely pass near the location of interest. STM-E (space-time maxima and exposure) model utilizes wave data during cyclones on a spatial neighbourhood. Long-duration wave data generated from a database of synthetic tropical cyclones are used to evaluate the performance of STM-E. Results indicate STM-E provides estimates with small bias and realistic uncertainty.
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Ann. Geophys., 39, 1013–1035, https://doi.org/10.5194/angeo-39-1013-2021, https://doi.org/10.5194/angeo-39-1013-2021, 2021
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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
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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.
Rémi Thiéblemont, Gonéri Le Cozannet, Jérémy Rohmer, Alexandra Toimil, Moisés Álvarez-Cuesta, and Iñigo J. Losada
Nat. Hazards Earth Syst. Sci., 21, 2257–2276, https://doi.org/10.5194/nhess-21-2257-2021, https://doi.org/10.5194/nhess-21-2257-2021, 2021
Short summary
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Sea level rise and its acceleration are projected to aggravate coastal erosion over the 21st century. Resulting shoreline projections are deeply uncertain, however, which constitutes a major challenge for coastal planning and management. Our work presents a new extra-probabilistic framework to develop future shoreline projections and shows that deep uncertainties could be drastically reduced by better constraining sea level projections and improving coastal impact models.
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Short summary
We quantify the influence of wave–wind characteristics, offshore water level and sea level rise (projected up to 2200) on the occurrence of flooding events at Gâvres, French Atlantic coast. Our results outline the overwhelming influence of sea level rise over time compared to the others. By showing the robustness of our conclusions to the errors in the estimation procedure, our approach proves to be valuable for exploring and characterizing uncertainties in assessments of future flooding.
We quantify the influence of wave–wind characteristics, offshore water level and sea level rise...
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