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Given recent scientific advances, coastal flooding events can be modelled even in complex environments. However, such models are computationally expensive, preventing their use for forecasting. At the same time, metamodelling techniques have been explored for coastal hydrodynamics, showing promising results. Developing such techniques for predicting coastal flood information (e.g., inland water depths) requires large enough learning datasets providing such inland information. However, detailed inland coastal flood observations are scarce and—when available—only correspond to a limited number of events. This paper aims at demonstrating how we can fill this gap by introducing a publicly available dataset, presenting its setup, and providing examples of use and recommendations. It has been built for the site of Gâvres (France), relying on the joint use of spectral wave (WW3) and non-hydrostatic wave-flow (SWASH) models, accounting for wave overtopping. It compiles 250 scenarios (defined by time-varying forcing conditions; including real and stochastically generated events) and the resulting maximal flooded areas and water depths (on 64,618 inland points). Its construction required the equivalent of 2 years of simulations on 48 cores. The examples of use of the dataset focus on method developments (metamodelling, forecast), local knowledge, and risk management.

Since May 2018, Mayotte island has experienced an important seismic activity linked to the on-going sismo-volcanic crisis. Although variations in the number of earthquakes and in their distribution have been observed since the start of the eruption in early July 2018, a continuous seismicity persists. It could weaken the steep submarine slopes of Mayotte, as highlighted by the high-resolution bathymetry data collected during the MAYOBS cruise in May 2019. This could trigger submarine landslides with associated tsunamis.To address the hazards associated with such events, we analyzed geomorphological data to define 8 scenarios of potential submarine landslides with volumes ranging from 11,25.106 to 800.106 m3. We simulated the resulting landslide dynamics as well as generated waves (Poulain et al. 2022). In order to estimate the uncertainty associated to the modeling approach, a hierarchy of different model approximations was tested, spanning hydrostatic, non-hydrostatic and multilayer approaches. A sensitivity analysis was also performed by varying the initial released mass, the rheological parameters describing the landslide, its interaction with the water column, the Manning friction coefficient as well as the resolution of the bathymetry description. The combination of all these elements provides an estimate of the uncertainty on simulation results. We show that, in the context of Mayotte, non-hydrostatic effects have the most prominent influence on simulated water elevation and waves velocity. Other key factors include the friction coefficient within the landslide and the resolution of the bathymetry. These results show that landslide-tsunami models should still be improved as well as the estimates of the parameters involved to reduce the related uncertainties on the water wave calculation (water elevation, velocity) that can exceed a factor two.Poulain, P., et al. (2022). Numerical simulation of submarine landslides and generated tsunamis: application to the on-going Mayotte seismo-volcanic crisis. Comptes Rendus. Géoscience, 354(S2), 1-30.

Metamodelling techniques (also referred to as surrogate modelling) have shown high performance to overcome the computational burden of numerical hydrodynamic models for fast prediction of key indicators of marine flooding (e.g. total flooded area). To predict flood maps (e.g. spatial distribution of maximum value of water depth during a flood event), a commonly-used approach is to rely on principal component analysis to reduce the high dimensionality of the flood map (related to the number of pixels typically of several 1000 s) by transforming the spatial output into a low number of latent variables (typically

SinceMay 2018,Mayotte Island has been experiencing seismo-volcanic activities that could trigger submarine landslides and, in turn, tsunamis. To address these hazards, we use the HySEA numerical model to simulate granular flow dynamics and the Boussinesq FUNWAVE-TVD numerical model to simulate wave propagation and subsequent inundations. We investigate 8 landslide scenarios (volumes from 11.25£106 m3 to 800£106 m3). The scenario posing the greatest threat involves destabilization on the eastern side ofMayotte’s lagoon at a shallowdepth and can generate sea-surface deformations of up to 2 m.We show that the barrier reef surroundingMayotte plays a prominent role in controlling water-wave propagation and in protecting the island. The tsunami travel time to the coast is very short (a few minutes) and the tsunami is not necessarily preceded by a sea withdrawal. Our simulation results provide a key to establishing hazard maps and evacuation plans and improving early-warning systems, Depuis mai 2018, l’île deMayotte connaît une activité sismo-volcanique importante susceptible de déclencher des glissements de terrain sous-marins générant des tsunamis. Pour faire face à ces aléas, nous utilisons deux modèles numériques complémentaires : le modèle HySEA (simulant la dynamique des écoulements granulaires) et le modèle Boussinesq FUNWAVE-TVD (simulant la propagation des vagues et les inondations) pour étudier 8 scénarios de glissements sous-marins potentiels (volumes de 11,25£106 m3 à 800£106 m3). Les scénarios ayant le plus d’impact se situent à proximité de Petite Terre et à faible profondeur. Ils peuvent générer une élévation de la surface de la mer jusqu’à 2 m en zone habitée à Petite Terre. Nous montrons que la barrière de corail entourant Mayotte joue un rôle prépondérant dans le contrôle de la propagation des vagues et dans la protection de l’île. Le temps de trajet du tsunami jusqu’à la côte est très court (quelques minutes) et le tsunami n’est pas nécessairement précédé d’un retrait maritime. De telles observations sont essentielles pour construire des cartes d’aléas précises et des plans d’évacuation afin d’aider la population

We investigate the dynamics and deposits of granular flows and the amplitude of the generated water waves using the depth-averaged shallow numerical model HySEA, both at the lab- and field scales. We investigate the different sources of errors by quantitatively comparing the simulations with (i) six new laboratory experiments of granular collapses in different conditions (dry, immersed, dry flow entering water) and slope angles, and (ii) numerical simulations made with the code SHALTOP that describes topography effects better than most landslide-tsunami models. In the laboratory configurations, at the limit of the shallow-approximation in such models, we show that topography and non-hydrostatic effects are crucial. However, when empirically accounting for topography effects by artificially increasing the friction coefficient and performing non-hydrostatic simulations, the model is able to reproduce the granular mass deposit and the waves recorded at gauges located at a distance of more than 2-3 times the characteristic dimension of the slide, with an error ranging from 1 % to 25 % depending on the scenario, without any further calibration. Taking into account this error estimation, we simulate landslides that occurred on Montagne Pelée volcano, Martinique, Petites Antilles as well as the generated waves. Results support the hypothesis that large flank collapse events in Montagne Pelée likely occurred in several successive sub-events. This result has a strong impact on the amplitude of the generated waves, and thus on the associated hazards. In the context of the on-going seismic volcanic unrest at Montagne Pelée volcano, we calculate the debris avalanche and associated tsunami for two potential flank-collapse scenarios.

In 2017, Irma and Maria highlighted the vulnerability of small islands to cyclonic events and the necessity of advancing the forecast techniques for cyclone-induced marine flooding. In this context, this paper presents a generic approach to deriving time-varying inundation forecasts from ensemble track and intensity forecasts applied to the case of Reunion Island in the Indian Ocean. The challenge for volcanic islands is to account for the full complexity of wave overtopping processes while also ensuring a robustness and timeliness that are compatible with emergency requirements. The challenge is addressed by following a hybrid approach relying on the combination of process-based models with a statistical model (herein, a random-forest classifier) trained with a precalculated database. The latter enables one to translate any time series of coastal marine conditions into the time-varying probability of inundation for different sectors. The application detailed for the case of Cyclone Dumile at Sainte-Suzanne city shows that the proposed approach enables quick discrimination, in both space and time, thereby identifying safe and exposed areas and demonstrating that probabilistic forecasting of marine flooding by overtopping is feasible. The whole method can be easily adapted to other territories and scales provided that validated process-based models are available. Beyond early warning applications, the developed database and statistical models may also be used for informing risk prevention and adaptation strategies.

The 2011 Great East Japan earthquake and tsunami remind us once again that these types of cascade event can occur and cause considerable damage. The scientific community realizes the need for rapid theoretical and practical progress on cascade events to provide field teams with the necessary tools and information for action during these types of events. The earthquake damage scenario for Martinique and Guadeloupe islands (French West Indies) has already been performed within the framework of French governmental projects, but these areas, in the vicinity of the French West Indies subduction zone, are also subject to tsunami events. In this study, we propose to perform a combined scenario in which an earthquake is followed by a tsunami, as it could arrive one day, considering the seismic characteristics and potential of such a subduction zone. The vulnerability of the buildings is defined considering local specific information based on several years of field inventories and inspections and is later classified into one of the 36 model building types of HAZUS. The calculation of the damages due to tsunamis follows the HAZUS methodologies. The main novelty of our study is the calculation of damage due to the two phenomena occurring one after the other, not in parallel, as is calculated in the existing literature. Therefore, for the calculation of the damages due to the second event (i.e. the tsunami), the vulnerability characteristics of the initial structure are reduced, considering the damage state of the construction after the first event (i.e. the earthquake). Hence, in our case, this calculation approach allows us to update the number of exposed elements and their changed vulnerabilities considering the damages due to the earthquake, since certain structures are already damaged by the earthquake before the arrival of the tsunami wave. The results coming from our study and our manner of treating the cascading hazards are putting into perspective with the Hazus method for combining damages coming from earthquake and the damages coming from consequently tsunami. The results expressed as the sum of the damages in both most damaged states, Extensive and Complete, are more or less in the same range of values for both studies (our study and HAZUS 2017). However, a trend of having more percentage of complete damages (and hence, less the Extensive damages) with our method than the ones obtained with the Hazus combination can be important information for crisis managing. This is a first result for the French West Indies territory, but anyway, more studies should be carried out in order to check this trend and eventually to confirm and validate this issue for others territories with others bathymetries, vulnerabilities and seismological features.

International audience; Given recent scientific advances, coastal flooding events can be properly modelled. Nevertheless, such models are computationally expensive (requiring many hours), which prevents their use for forecasting and warning. In addition, there is a gap between the model outputs and information actually needed by decision makers. The present work aims to develop and test a method capable of forecasting coastal flood information adapted to users’ needs. The method must be robust and fast and must integrate the complexity of coastal flood processes. The explored solution relies on metamodels, i.e., mathematical functions that precisely and efficiently (within minutes) estimate the results that would provide the numerical model. While the principle of relying on metamodel solutions is not new, the originality of the present work is to tackle and validate the entire process from the identification of user needs to the establishment and validation of the rapid forecast and early warning system (FEWS) while relying on numerical modelling, metamodelling, the development of indicators, and information technologies. The development and validation are performed at the study site of Gâvres (France). This site is subject to wave overtopping, so the numerical phase-resolving SWASH model is used to build the learning dataset required for the metamodel setup. Gaussian process- and random forest classifier-based metamodels are used and post-processed to estimate 14 indicators of interest for FEWS users. These metamodelling and post-processing schemes are implemented in an FEWS prototype, which is employed by local users and exhibits good warning skills during the validation period. Based on this experience, we provide recommendations for the improvement and/or application of this methodology and individual steps to other sites.

To estimate return levels of wave heights (Hs) induced by tropical cyclones at the coast, a commonly-used approach is to (1) randomly generate a large number of synthetic cyclone events (typically >1,000); (2) numerically simulate the corresponding Hs over the whole domain of interest; (3) extract the Hs values at the desired location at the coast and (4) perform the local extreme value analysis (EVA) to derive the corresponding return level. Step 2 is however very constraining because it often involves a numerical hydrodynamic simulator that can be prohibitive to run: this might limit the number of results to perform the local EVA (typically to several hundreds). In this communication, we propose a spatial stochastic simulation procedure to increase the database size of numerical results with synthetic maps of Hs that are stochastically generated. To do so, we propose to rely on a data-driven dimensionality-reduction method, either unsupervised (Principal Component Analysis) or supervised (Partial Least Squares Regression), that is trained with a limited number of pre-existing numerically simulated Hs maps. The procedure is applied to the Guadeloupe island and results are compared to the commonly-used approach applied to a large database of Hs values computed for nearly 2,000 synthetic cyclones (representative of 3,200 years – Krien et al., NHESS, 2015). When using only a hundred of cyclones, we show that the estimates of the 100-year return levels can be achieved with a mean absolute percentage error (derived from a bootstrap-based procedure) ranging between 5 and 15% around the coasts while keeping the width of the 95% confidence interval of the same order of magnitude than the one using the full database. Without synthetic Hs maps augmentation, the error and confidence interval width are both increased by nearly 100%. A careful attention is paid to the tuning of the approach by testing the sensitivity to the spatial domain size, the information loss due to data compression, and the number of cyclones. This study has been carried within the Carib-Coast INTERREG project (https://www.interreg-caraibes.fr/carib-coast).

Since May 2018, Mayotte island has experienced an important seismic activity linked to the on-going sismo-volcanic crisis. The epicenters of the seismic swarms are located between 5 and 15 km east of Petite Terre for the main swarm, and 25 km east of Petite Terre for the secondary swarm. Although variations in the number of earthquakes and their distribution have been observed since the start of the eruption in early July 2018 [Lemoine A.(2020), Cesca et al.(2020)], a continuous seismicity persists and could generate several earthquakes of magnitudes close to M4 widely felt by the population. This recurrent seismicity could weaken the steep submarine slopes of Mayotte, as highlighted by the high resolution bathymetry data collected during the MAYOBS cruise in May 2019 (Feuillet et al.,submitted) and trigger submarine landslides with associated tsunamis.To address the hazards associated with such events, we analyzed morphological data to define 8 scenarios of potential submarine slides with volumes ranging from 11,25.106 to 800.106 m3 and we simulate the landslide dynamics and generated waves. We use two complementary numerical models: (i) the code HYSEA to simulate the dynamic of the submarine granular flows and the water wave generation, and (ii) the Boussinesq FUNWAVE- TVD model simulate the waves propagation and the inundation on Mayotte. The effect of the time at which the models are coupled is investigated.The most impacting submarine slide scenarios are located close to Petite Terre at a shallow depth. They can locally generate a sea surface elevation more than a meter in local areas especially at Petite Terre. The various simulations show that parts of the island are particularly sensitive to the risk of tsunamis. Indeed, some scenarios that does not cause significant coastal flooding still seems to cause significant hazards in these exposed areas. The barrier reef around Mayotte has a prominent role in controlling the wave propagation towards the island and therefore reducing the impact on land. It should be noted that the arrival of tsunamis on the coastline is not necessarily preceded by a retreat from the sea and the waves can reach the coasts of Mayotte very quicky (few minutes). Cesca, S., Letort, J., Razafindrakoto, H.N.T. et al. Drainage of a deep magma reservoir near Mayotte inferred from seismicity and deformation. Nat. Geosci. 13, 87–93 (2020). https://doi.org/10.1038/s41561-019-0505-5Feuillet, N, Jorry, S. J., Crawford, W, Deplus, C. Thinon, I, Jacques, E. Saurel, J.M., Lemoine, A., Paquet, F., Daniel, R., Gaillot, A., Satriano, C., Peltier, A., Aiken, C., Foix, O., Kowalski, P., Laurent, A., Beauducel, F., Grandin, R., Ballu, V., Bernard, P., Donval, J.P., Geli, L., Gomez, J. Guyader, V., Pelleau, P., Rinnert, E., Bertil, D., Lemarchand, A., Van der Woerd, J.et al. (in rev). Birth of a large volcano offshore Mayotte through lithosphere-scale rifting, Nature.Anne Lemoine, Pierre Briole, Didier Bertil, Agathe Roullé, Michael Foumelis, Isabelle Thinon, Daniel Raucoules, Marcello de Michele, Pierre Valty, Roser Hoste Colomer, The 2018–2019 seismo-volcanic crisis east of Mayotte, Comoros islands: seismicity and ground deformation markers of an exceptional submarine eruption, Geophysical Journal International, Volume 223, Issue 1, October 2020, Pages 22–44, https://doi.org/10.1093/gji/ggaa273

Sea-level rise due to anthropogenic climate change is projected not only to exacerbate extreme events such as cyclones and storms but also to cause more frequent chronic flooding occurring at high tides under calm weather conditions. Chronic flooding occasionally takes place today in the low-lying areas of the Petit Cul-de-sac marin (Guadeloupe, West Indies, French Antilles). This area includes critical industrial and harbor and major economic infrastructures for the islands. As sea level rises, concerns are growing regarding the possibility of repeated chronic flooding events, which would alter the operations at these critical coastal infrastructures without appropriate adaptation. Here, we use information on past and future sea levels, vertical ground motion, and tides to assess times of emergence of chronic flooding in the Petit Cul-de-sac marin. For RCP8.5 (Representative Concentration Pathway 8.5; i.e., continued growth of greenhouse gas emissions), the number of flood days is projected to increase rapidly after the emergence of the process so that coastal sites will be flooded 180 d a year within 2 decades of the onset of chronic flooding. For coastal locations with the lowest altitude, we show that the reconstructed number of floods is consistent with observations known from a previous survey. Vertical ground motions are a key source of uncertainty in our projections. Yet, our satellite interferometric synthetic-aperture radar results show that the local variability in this subsidence is smaller than the uncertainties in the technique, which we estimate to be between 1 (standard deviation of measurements) and 5 mm/yr (upper theoretical bound). Despite these uncertainties, our results imply that adaptation pathways considering a rapid increase in recurrent chronic flooding are required for the critical port and industrial and commercial center of Guadeloupe. Similar processes are expected to take place in many low-elevation coastal zones worldwide, including on other tropical islands. The method used in this study can be applied to other locations, provided tide gauge records and local knowledge of vertical ground motions are available. We argue that identifying times of emergence of chronic flooding events is urgently needed in most low-lying coastal areas, because adaptation requires decades to be implemented, whereas chronic flooding hazards can worsen drastically within years of the first event being observed.

Chronic flooding, occurring at high tides under calm weather conditions, is occasionally taking place today in the low-lying areas of the Petit-Cul-de-sac marin (Guadeloupe, West Indies, French Antilles). This area includes critical industrial, harbor and major economic infrastructures for the island. As sea level rises, concerns are growing regarding the possibility for repeated chronic flooding events, which would alter the operations at these critical coastal infrastructures without appropriate adaptation. Here, we use information on past and future sea levels, vertical ground motion and tides to assess times of emergence of chronic flooding in the Petit-Cul-de-sac marin. For RCP8.5 (i.e., continued growth of greenhouse gas emissions), the number of flood days is projected to increase rapidly after the emergence of the process, so that coastal sites will be flooded every two days within 2 decades after the onset of chronic flooding. For coastal locations with the smallest altitude, we show that the reconstructed number of floods are consistent with observations known from a previous survey. One key uncertainty of our result is the actual rate of subsidence of the island. However, our satellite interferometric synthetic-aperture radar results show that the local variability of this subsidence is smaller than the uncertainties of the technique, which we estimate between 1 (standard deviation of measurements) and 5 mm/yr (upper theoretical bound). Our results imply that adaptation pathways considering a rapid increase of recurrent chronic flooding are required in the critical port, industrial and commercial center of Guadeloupe, as well as presumably in many low-elevation coastal zones of other tropical islands.

Integrating full-process high resolution hydrodynamic simulations within early warning system (EWS) for marine flooding is hindered by the large computation time cost of such numerical models. This problem can be alleviated through the statistical analysis of pre-calculated simulation results to build a fast (low computation time cost) statistical predictive model (named metamodel). Despite the success of this approach, a direct application of such techniques for EWS is not straightforward in all settings, more particularly in environments where the stochastic character of waves has a significant effect on the induced flood, i.e., where overtopping is on a duration smaller than 500 times the offshore wave period. In such environments, the numerical simulator is not deterministic and provides statistical quantities of the flooding indicators. By focusing on the estimates of quantiles, the objective of the present study is to explore the applicability of random forest (RF) models for marine flooding prediction by providing two levels of information: (1) the quantile of interest via a quantile random forest regression model (qRF); (2) the flooding probability via a classification random forest (cRF). We use the macrotidal site of Gâvres (French Atlantic coast) as an application case for which ~ 2000 numerical simulations were performed (i.e. stochastic simulations given 100 different extreme-but-realistic offshore meteo-oceanic input conditions were repeated 20 times) to compute local and global flooding indicators (respectively the maximum water depth at the coast and the total volume of water entering the territory). Through an extensive repeated cross-validation procedure, we tune the qRF parameters leading to high coefficient of determination of ~ 90% for the quantiles at 25–50–75%, and we show that the qRF models outperform the commonly used Tobit regression model. The comparison with the numerical results on historical events shows very satisfactory prediction for events both leading to major flooding and to absence of impact. For low quantile level and minor-to-moderate flooding events, the second level provided by the cRF-derived flooding probability shows its added value by enabling the EWS user to nuance the qRF prediction and to tag some situations where the prediction remains unsure.

Pedreros, R.; Idier, D.; Le Roy, S.; David, A.; Schaeffer, D.; Durand, J., and Desmazes, F., 2020. Infragravity waves in a complex macro-tidal environment: High frequency hydrodynamic measurements and modelling. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1235–1239. Coconut Creek (Florida), ISSN 0749-0208.Nearshore high frequency (> 1 Hz) hydrodynamic measurements over month to year scale face many issues, especially in inter-tidal areas. We present measurements done in the intertidal area of a macro-tidal site (Gâvres, France), and on a time span of 2 years. The measurements are done with a WiSens NKE pressure sensor (burst mode of 17 minutes). Infragravity (IG) waves are present in the signal with IG wave heights reaching 0.5 m. The hydro-meteorological conditions (tide, surge, offshore short wave, wind) are characterized for each burst, showing for instance a linear increase of IG wave height with the offshore wave height (Hs) as long as Hs remains smaller than 4 m. To further investigate the temporal and spatial variability of IG waves, the analysis is completed using an unsteady phase resolving model (SWASH). We show how the IG wave height depend on the offshore wave conditions, the still water level, local wind conditions, and the local configuration, and provide hypothesis on the IG wave mechanisms generation on Gâvres.

The characterisation of past coastal flood events is crucial for risk prevention. However, it is limited by the partial character of historical information on flood events and the lack or limited quality of past hydro-meteorological data. In addition coastal flood processes are complex, driven by many hydro-meteorological processes, making mechanisms and probability analysis challenging. These issues are tackled by joining historical, statistical and modelling approaches. We focus on a macrotidal site (Gâvres, France) subject to overtopping and investigate the 1900-2010 period. A continuous hydro-meteorological database is built and a damage event database is set up based on archives, newspapers, maps and aerial photographies. Using together historic information, hindcasts and hydrodynamic models, we identified 9 flood events, among which 5 significant flood events (4 with high confidence: 1924, 1978, 2001, 2008; 1 with a lower confidence: 1904). These flood events are driven by the combination of sea-level rise, tide, atmospheric surge, offshore wave conditions and local wind. The critical conditions leading to flood are further analysed, including the effect of coastal defences, showing that the present coastal defences would not have allowed to face the hydro-meteorological conditions of 09/02/1924 for instance, whose bi-variate return periods of exceedance Tr (still water level relative to the mean sea level and significant wave height) is larger than 1000 y. In addition, Tr is expected to significantly decrease with the sea-level rise, reaching values smaller than 1 y, for 8 of the 9 historical events, for a sea-level rise of 0.63 m, which is equal to the median amount of sea-level rise projected by the 5th Assessment Report of the IPCC in this region for RCP8.5 in 2100.

The Maldives, located in the Indian Ocean, are the paradigm of low-lying coral-reef islands where adaptation to climate change is essential. Besides the mean sea level rise in this region, that is expected to be around 1 m by the end of the century according to the last IPCC report, these islands are exposed to one of the largest swells in terms of significant wave height and peak period. In this study we characterize, using the output of global wind-wave models forced by wind fields from the CMIP5 ensemble delivered by CSIRO, the present conditions and future projections of the waves around the Maldivian archipelago, as well as the return periods for the predominant swell directions. We then propagate extreme waves inside the domain using WaveWatch III model run onto a high-resolution grid (down to 500 m at the coast). Finally, we evaluate the coastal impacts of extreme swell waves in two strategic case study islands with different exposures and where land reclamation and different adaptation solutions have been/are being done. To do so, we propagate waves using SWASH model with rising mean sea level towards the shoreline and assess the flooding extend under different conditions. This kind of studies are essential to help the policy makers in defining the most accurate and appropriate adaptation strategies.

The characterisation of past coastal flood events is crucial for risk prevention. However, it is limited by the partial nature of historical information on flood events and the lack or limited quality of past hydro-meteorological data. In addition, coastal flood processes are complex, driven by many hydro-meteorological processes, making mechanisms and probability analysis challenging. Here, we tackle these issues by joining historical, statistical and modelling approaches. We focus on a macrotidal site (Gâvres, France) subject to overtopping and investigate the 1900–2010 period. We build a continuous hydro-meteorological database and a damage event database using archives, newspapers, maps and aerial photographs. Using together these historical information, hindcasts and hydrodynamic models, we identify nine flood events, among which five are significant flood events (four with high confidence: 1924, 1978, 2001, 2008; one with a lower confidence: 1904). These flood events are driven by the combination of sea-level rise, tide, atmospheric surge, offshore wave conditions and local wind. We further analyse the critical conditions leading to flood, including the effect of coastal defences, showing, for instance, that the present coastal defences would not have allowed to face the hydro-meteorological conditions of 09/02/1924, whose bi-variate return periods of exceedance $$T_\mathrm{R}$$ (still water level relative to the mean sea level and significant wave height) are larger than 1000 year. In the coming decades, $$T_\mathrm{R}$$ is expected to significantly decrease with sea-level rise, reaching values smaller than 1 year, for eight of the nine historical events, for a sea-level rise of 0.63 m, which is equal to the median sea-level rise projected by the 5th Assessment Report of the IPCC in this region for RCP8.5 in 2100.

Idier, D.; Aurouet, A.; Bachoc, F.; Baills, A.; Betancourt, J.; Durand, J.; Mouche, R.; Rohmer, J.; Gamboa, F.; Klein T.; Lambert, J.; Le Cozannet, G.; Le Roy, S.; Louisor, J.; Pedreros, R., and Veron, A.L., 2020. Toward a user-based, robust and fast running method for coastal flooding forecast, early warning, and risk prevention. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1111–1116. Coconut Creek (Florida), ISSN 0749-0208.Scientific progresses now allow properly modelling coastal flooding events. Such models are nevertheless very expensive in terms of computation time (>hours) which prevents any use for forecast and warning or even for estimating the coastal flood hazard return period together with uncertainties. In addition, there is a gap between model outputs and information actually needed by the decision makers. Within the RISCOPE project, we aim at developing a user-based method contributing to forecast, early-warning and prevention of coastal flooding risks. The method should be robust, fast and integrate the complexity of coastal flood processes. To build such coastal flooding models, the solution explored relies on meta-models, i.e. mathematical functions which estimate, with good precision and at a negligible computational cost (

International audience; In this work we consider an e cient discretization of the Shallow Water Equations in spherical geometry for oceanographic applications. Instead of the classical 2d-covariant or 3d-Cartesian approaches, we focus on the mixed 3d/2d form of [Bernard et al., JCP 2009] which evolves the 2d momentum tangential to the sphere by projecting the 3d-Cartesian right-hand side on the sphere surface. Di↵erently from the last reference we consider the exact representation of the sphere instead of the finite element one, mixed with a covariant basis projection of the momentum. This leads to several simplifications of the Discontinuous Galerkin scheme: the local mass matrix goes back to the standard block-diagonal form; the Riemann Problem does not require any tensor or vector rotations to align the bases on the two sides of an edge. Second we consider well balancing corrections related to relevant equilibrium states for tsunami and storm surge simulations. These corrections allow to compensate for the inherent non-exactness of the quadrature induced by the non-polynomial nature of both the geometrical mapping and of the covariant basis. In other words, these corrections are the order of the cubature error. We show that their addition makes the scheme exactly well balanced, and is is equivalent to recasting the integral of the hydrostatic pressure term in strong form. The proposed method is validated on academic benchmarks involving both smooth and discontinuous solutions, and applied to realistic tsunami and an historical storm surge simulation.

Gabarrou, S.; Le Cozannet, G.; Parteli, E.J.R.; Pedreros, R.; Guerber, E.; Millescamps, B.; Mallet, C., and Oliveros, C., 2018. Modelling the Retreat of a Coastal Dune under Changing Winds. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 166–170. Coconut Creek (Florida), ISSN 0749-0208.Coastal dunes can move in response to winds and cause serious hazard to human assets. Changes in wind patterns, potentially occurring as a consequence of climate change or variability, could affect rates of aeolian transport and migration velocity of coastal dunes. However, most of previous modeling studies were conducted assuming that aeolian bedforms are subject to constant wind velocities. This article presents a modeling of the mobility of the Dune du Pilat in Aquitaine, a coastal transverse dune exposed to winds of varying intensity. It applies well-established models and empirical formula for aeolian dune migration, including a model previously validated against measurements of real profiles of desert and coastal dunes. The average migration velocity of Pilat dune predicted by the models is about 3m/year, which is in good agreement with in-situ measurements. To test the response of transverse dune mobility to changing winds, virtual wind time series are generated using a stochastic model. Modelling experiments suggest that more frequent storms have less impacts than more intense winds. Due to the size of the Pilat Dune (altitude of about 100m), these result in moderate changes in the average dune velocity. This study shows that the approach of combining a stochastic model for winds with a morphodynamic dune model can provide valuable insight into how aeolian bedforms respond to changes in flow conditions potentially caused by climate change.

International audience; As low-lying coastal areas can be impacted by flooding caused by dynamic components that are dependent on each other (wind, waves, water levels—tide, atmospheric surge, currents), the analysis of the return period of a single component is not representative of the return period of the total water level at the coast. It is important to assess a joint return period of all the components. Based on a semiparametric multivariate extreme value analysis, we determined the joint probabilities that significant wave heights (Hs), wind intensity at 10 m above the ground (U), and still water level (SWL) exceeded jointly imposed thresholds all along the Corsica Island coasts (Mediterranean Sea). We also considered the covariate peak direction (Dp), the peak period (Tp), and the wind direction (Du). Here, we focus on providing extreme scenarios to populate coastal hydrodynamic models, SWAN and SWASH-2DH, in order to compute the 100-year total water level (100y-TWL) all along the coasts. We show how the proposed multivariate extreme value analysis can help to more accurately define low-lying zones potentially exposed to coastal flooding, especially in Corsica where a unique value of 2 m was taken into account in previous studies. The computed 100y-TWL values are between 1 m along the eastern coasts and a maximum of 1.8 m on the western coast. The calculated values are also below the 2.4 m threshold recommended when considering the sea level rise (SLR). This highlights the added value of performing a full integration of extreme offshore conditions, together with their dependence on hydrodynamic simulations for screening out the coastal areas potentially exposed to flooding.

Muller, H.; van Rooijen, A.; Idier, D.; Pedreros, R., and Rohmer, J., 2017. Assessing storm impact on a French coastal dune system using morphodynamic modeling. Natural coastal dune systems provide protection against flooding from the ocean for many coastal communities around the world. An in-depth knowledge of their erosion mechanisms under oceanic stress can help to identify potential weak spots along the coastline and eventually prevent damage to the hinterland. The objective of this study was to assess the effects of hydro-morphodynamic phenomena on the coastal dune morphology during storm events and to evaluate their level of protection. This paper focuses on the physical processes that cause erosion and breaching of sandy dune systems, which are typically a function of the coastal morphology in combination with the hydraulic loading. An XBeach model was set up for the coast of Les Boucholeurs (France), which suffered from severe erosion, dune breaching (at six locations), and inundation of ...

In this paper, we present a new source assessment of the La Palma collapse scenario previously described and studied in Abadie et al. (2012). Three scenarios (i.e., slide volumes of 20, 40 and 80 km3) are considered, from the initiation of the slide to the water waves generation, using THETIS, a 3D Navier–Stokes model. The slide is considered as a Newtonian fluid whose viscosity is adjusted to approximate a granular behavior. After 5 minutes of propagation with THETIS, the generated water wave is transferred into FUNWAVE-TVD for 15 minutes of Boussinesq model simulation. Then, four different depth-averaged codes are used to propagate the wave to the Guadeloupe area, Europe and French coasts. Finally, the wave impact in terms of run-up is evaluated through direct computations in specific areas or using theoretical formulas. Although the wave source appears reduced due to the rheology used compared to former works, the wave impact is still significant for the maximum slide volume considered on surrounding islands and coasts, as well as on remote most exposed coasts such as Guadeloupe. In Europe and in France, the wave impact is moderate (for specific areas in Spain and Portugal) to weak (Atlantic French coast). The comparison between the different wave models in overlapping computational regions shows an overall agreement in terms of first wave amplitude and time of arrival, but differences appear in the trailing waves.

In the framework of the French research project TANDEM dedicated to tsunami modelling, a series of benchmarks has been set up, addressing the various stages of a tsunami event: generation, propagation, run-up and inundation. We present here the results of five codes, involving both depth-averaged Boussinesq and fully 3D Navier-Stokes equations, aimed at being applicable to tsunami modelling. The codes are evaluated on a flow involving propagation, run-up, overtopping and reflection of the waves on two-dimensional reefs, and compared with the experimental data produced from a set of laboratory experiments carried out at the O.H. Hinsdale Wave Research Laboratory, Oregon State University (OSU, see Roeber et al., 2010 and Roeber and Chung, 2012).

The knowledge and prediction of cyclones as well as wave models experienced significant improvements in this last decade, opening the perspective of a better understanding of the wave sensitivity to the cyclone characteristics (e.g. track angle of approach θ, forward speed V f, radius of maximum wind R m, landfall position x o, etc.). Physically, waves are strongly linked to the time-varying evolution of the relative cyclone position. Thus, even assuming the main cyclone characteristics to be stationary, exploring the role played by each of them should necessarily be conducted in a dynamic manner. This problem is investigated using the advanced statistical tools of variance-based global sensitivity analysis (VBSA) in different ways to provide an overall view of wave height sensitivity to cyclone characteristics: (1) step-by-step: by computing the time series of sensitivity measures; (2) aggregated: by summarising the time-varying information into a single sensitivity indicator; (3). mode-based: by studying the sensitivity with respect to the occurrence of specific temporal patterns (e.g. up-down translation of the overall series). Yet, applying this multi-look dynamic sensitivity analysis faces two major difficulties: (1) VBSA requires a large number of simulations (typically > 10,000), which appears to be incompatible with the large computation time cost of numerical codes (>several hours for a single run); (2) integrating the time dimension imposes to process a large amount of information via vectors of large size (e.g. series of significant wave height H S discretised over several hundreds of time steps). In this study, we propose a joint procedure combining kriging meta-modelling (to overcome the 1st issue) and principal component analysis techniques (to overcome the 2nd issue by summarising the time information into a limited number of components). The applicability of this strategy is tested and demonstrated on a real case (Sainte-Suzanne city, located at Reunion Island) using a set of 100 cyclone-induced H S series, each of them being computed for different scenarios of cyclone characteristics, i.e. using only 100 long-running simulations. The key role of R m over the whole evolution of H S is shown by means of the aggregated option, with a more specific influence in the vicinity of Sainte-Suzanne (when the cyclone eye is located less than 200 km away from the site) as highlighted by the step-by-step option. The step-by-step option also highlights the influence of the landfall position on the H S peak reached in strong interaction with θ and R m. Finally, the role of V f in the occurrence of a turning point marking a shift near landfall between regimes of low-to-high H S values is also identified. The above results provide guidelines for future research efforts on cyclone characteristics prediction.

International audience; This study assessed the ability of the SWASH model to reproduce wave set-up and run-up on complex realistic 3D morphology during highly dissipative stormy conditions, based on the most energetic field data set reported in the bibliography (ECORS-Truc Vert’08 beach experiment). Several approaches (1D and 2D) and forcing methods (spectral and parametric) were applied. For the three days of high-energy conditions caused by the Johanna storm, wave set-up was accurately reproduced, with simulation performance in 1D and 2D at R² = 0.66, 0.81 respectively for all data considered; RMSE = 0.13 m, 0.08 m; bias = 0.06, -0.02. Run-up in the 1D configuration is significantly overestimated while in 2D, the reproduction of run-up using spectral forcing was very accurate with R² = 0.73; RMSE = 0.19; bias = 0.04, underlining the role of spectral frequency and directional spread to precisely reproduce the surf zone processes during a storm on a complex barred beach. The maximum estimated values for set-up, run-up and spatial variability of run-up are comparable with results from previous studies, even though significantly higher offshore wave conditions. These results support the hypothesis of a run-up saturation signature in dissipative contexts, mainly influenced by extreme offshore wave conditions.

Le projet ALDES a consiste a etudier, par des simulations numeriques detaillees, le risque tsunami sur 3 sites pilotes de la cote mediterraneenne francaise, pour des scenarios sismiques et gravitaires. Malgre l'intensite moderee des tsunamis susceptibles d'affecter ces cotes, Antibes apparait particulierement exposee, en particulier pour un scenario comme le glissement de terrain de l'aeroport de Nice de 1979.Cet evenement, a l'origine de nombreux dommages sur Antibes, a ete simule en s'appuyant sur des caracterisations du glissement menees par l'IFREMER. L'utilisation de calculs emboites (codes GEOWAVE et SURF-WB) a permis d'affiner la simulation jusqu'a une resolution de 3,75 m en integrant explicitement les elements urbains (modele numerique d'elevation integrant le bâti).Les resultats s'averent coherents avec les observations historiques, en termes de temps d'arrivee et de polarite de la vague sur la Baie des Anges et en termes d'inondation sur Antibes. La simulation montre que le quartier de la Salis est atteint au bout de 6 minutes par un tsunami depassant les 3 m a la cote. Cette premiere vague, la plus importante, entraine une submersion consequente avec des courants localement eleves et des run-up pouvant atteindre 4 m.Plusieurs tests de sensibilite ont ete menes sur ce cas, permettant de mettre en evidence l'importance du choix des equations (Boussinesq - Saint-Venant) et de la description du glissement pour simuler un tsunami d'origine gravitaire. Enfin, ces resultats permettent de souligner l'interet d'une prise en compte explicite du bâti pour la representativite des simulations de submersion en milieu urbain.

International audience; This paper investigates the construction of a metamodel for coastal flooding early warning at the peninsula of Gâvres, France. The code under study is an hydrodynamic model which receives time-varying maritime conditions as inputs. We concentrate on Gaussian pocess metamodels to emulate the behavior of the code. To model the inputs we make a projection of them onto a space of lower dimension. This setting gives rise to a model selection methodology which we use to calibrate four characteristics of our functional-input metamodel: (i) the family of basis functions to project the inputs; (ii) the projection dimension; (iii) the distance to measure similarity between functional input points; and (iv) the set of functional predictors to keep active. The proposed methodology seeks to optimize these parameters for metamodel predictability, at an affordable computational cost. A comparison to a dimensionality reduction approach based on the projection error of the input functions only showed that the latter may lead to unnecessarily large projection dimensions. We also assessed the adaptability of our methodology to changes in the number of training and validation points. The methodology proved its robustness by finding the optimal solution for most of the instances, while being computationally efficient.

Identifying the offshore forcing and breaching conditions that lead to marine inundation is of high importance for risk management. This task cannot be conducted by using a numerical hydrodynamic model due to its high computation time cost (of several minutes or even hours). In the present study, we show how the random forest (RF) classification technique can approximate the numerical model to explore these critical conditions. We focus on the Boucholeurs site, which is located on the French Atlantic coast and exposed to overflow processes. An iterative strategy is developed for selecting the numerical simulations (a total of 200) to train the RF model. The sensitivity to the input parameters is studied using permutation-based importance measures and extended versions of the partial dependence plots. The results highlight the key interplay among the high-tide level, the surge peak and the phase difference, and the complex role of the breaching location.

International audience

Lecacheux, S.; Bonnardot, F.; Rousseau, M.; Paris F.; Pedreros, R.; Nicolae Lerma, A.; Quetelard, H., and Barbary, D., 2018. Probabilistic forecast of coastal waves for flood warning applications at Reunion Island (Indian Ocean). In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 776–780. Coconut Creek (Florida), ISSN 0749-0208.La Reunion being a small isolated island, the coastal impacts of tropical cyclones transiting nearby are tightly related to the relative position of the track, wind intensity and size. Thus, the forecast of cyclone-induced waves should be conducted in a probabilistic manner.Using ensemble track and intensity forecasts of Bonnardot and Quetelard (2016), the approach presented here relies on two steps: (1) Considering that the use of parametric models leads to an underestimation of wave heights distant from the cyclone eye, the forecasted vortex is bogused into the large-scale wind field provided by ECMWF's IFS model for each track and time step. A short simulation is conducted with Meso-NH model at 8 km resolution so that it can create realistic wind and pressure fields well balanced with the large-scale conditions (2) A combination of a two-way nested Wavewatch 3 modelling framework enables to compute the waves associated to each track from 10 km to 300 m resolution at the coast.Results extracted at 50 m depth are presented as exceedance values and probabilities of exceedance of wave heights for different coastal segments and thresholds. The comparison with measurements and simulations performed with Best-Track data show that probabilistic wave forecasts performed with the ensemble sets of Bonnardot and Quetelard (2016) upgrade the precision and the level of information provided compared to the deterministic method. Nevertheless, the study also points out that the size and shape parameters of the cyclones should be considered in the ensemble generation method to produce more accurate wave forecast.

Pedreros, R.; Idier, D.; Muller, H.; Lecacheux, S.; Paris, F.; Yates-Michelin, M.; Dumas, F.; Pineau-Guillou, L., and Senechal, N., 2018. Relative contribution of wave setup to the storm surge: observations and modeling based analysis in open and protected environments (Truc Vert beach and Tubuai island). In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1046–1050. Coconut Creek (Florida), ISSN 0749-0208.Recent events like the Xynthia (2010, France) storm illustrate the potentially devastating effect that storm surges can have on the coasts. Nearshore storm surges at the result mainly from two processes: atmospheric surges and wave setup. This paper investigate the relative wave setup contribution in the storm surge signal for energetic events and focusing on two cases: an open beach (Truc Vert beach, France) and a high island protected by a reef lagoon (Tubuai, French Polynesia). The two selected events are the Johanna storm (March'08), for the Truc Vert site, and the Oli cyclone (February'10), for Tubuai. The data analysis shows that the maximum total storm surge reaches 1.2 m on the Truc Vert site and 1.1 m in the Tubuai lagoon. On the Truc Vert beach, the ECORS'08 in-situ measurements allow estimating a wave setup contribution of 80% of the total storm surge, at the time of maximum storm surge. The relative contribution of the wave setup is investigated a bit further, using the modeling approach. The modeling relies on the joint use of a shallow-water (MARS 2DH) and wave (SWAN) models. It shows an heterogeneous distribution of the wave setup in the Tubuai lagoon and a longshore variability close to the waterline for Truc Vert (~ 30%). In both cases, the wave setup contribution to the whole storm surge is predominant, with relative values ranging from 71 to 120% of the total maximal storm surge. Values larger than 100% occur on the Tubuai site when the atmospheric storm surge is negative.

Uncertainty related to the source parameters of earthquake can largely impact the tsunami-induced wave characteristics, especially in the case of near-field tsunami source. The combination of numerical simulations and historical eyewitness accounts can be used to better constrain those uncertainties. In the present study, we propose a Bayesian procedure to infer (i.e. learn) the probability distribution of the source parameters of the earthquake. The strategy is based on the combination of: (1) kriging-based metamodelling techniques to overcome the high computation time cost of the numerical simulator; and (2) Approximate Bayesian Computation (ABC) procedure to perform the Bayesian inference. The procedure is applied to the Ligurian (North West of Italy) 1887 tsunami case, for which tsunami-induced sea surface elevations at the coast have been reported at four locations, namely Marseille, Imperia, Diano-Marina and Genoa. The kriging metamodels are trained using only 300 long-running numerical simulations that were performed using the FUNWAVE-TVD code. Contrary to recent inversion exercises that can benefit from current modern observation networks (like tide gauges, sea bottom pressure gauges, GPS-mounted buoys), the case of historical tsunami like Liguria is complicated by the imprecision and scarcity of the observations: this is accounted for by conducting the combined ABC-kriging procedure a large number of times (i.e. 1000); each time a new set of observations being randomly generated to account for this observational error. The combined analysis of the inference results and of the observation uncertainty reveals that: (1) the coseismic slip is the most important source parameter with a very peaky density distribution around low values ranging from 0.3 to 0.6 m; (2) The fault width has a peaky density distribution around low values ranging from 10 to 12 km; (3) The rake and azimuth distribution only slightly deviate from the uniform prior, hence indicating a low influence of those parameters; (4) The bi-modal distribution of the dip is also evidenced.

A modelling chain was implemented in order to propose a realistic appraisal of the risk in coastal areas affected as well by overflowing as overtopping processes. Simulations are performed through a nested downscaling strategy from regional to local scale at high spatial resolution with explicit buildings, urban structures such as sea front walls and hydraulic structures liable to affect the propagation of water in urban areas. Validation of the model performance is based on hard and soft available data analysis and conversion of qualitative to quantitative information to reconstruct the area affected by flooding and the succession of events during two recent storms. Two joint probability statistical approaches (joint exceedance probability and environmental contour) are used to define 100 years off-shore conditions scenarios and to investigate the flood response to each scenario in term of: (1) maximum spatial extent of flooded areas, (2) volumes of water propagation inland and (3) water level in flooded areas. Scenarios of sea level rise are also considerate in order to evaluate the potential hazard evolution. Our simulations show that for a maximising 100-year hazard scenario, for the municipality as a whole, 38 % of the zones are prone to overflow flooding and 62 % to flooding by propagation of overtopping water volume along the seafront. Results also reveal that for the two kind of statistic scenarios a difference of about 5 % in the forcing conditions (water level, wave height and period) can produce significant differences responses in terms of flooding like +13.5 % of water volumes propagating inland or +11.3 % of affected surfaces. In some areas, flood response appears to be very sensible to the scenario chosen with differences of 0.3 to 0.5 m in water level. The approach developed enable to bracket the 100-year hazard and to characterise spatially the robustness or the uncertainty over the results. Considering a 100-year scenario with mean sea level rise (0.6 m), hazard characteristics are dramatically changed with an evolution of the overtopping/overflowing process ratio and an increase of 384 % in volumes of water propagating inland and 247 % in flooded surfaces.

International audience; The purpose of this study is to assess the ability of the SWASH model to reproduce wave setup and runup in highly dissipative stormy conditions. To proceed we use data collected during the ECORS Truc Vert’08 Experiment, especially during the Johanna storm in the winter of 2007-008 (wave setup under Hs= 8.2 m and Tp= 18.3 s and runup under 6.4 m and peak period up to 16.4 s). We test different model settings (1D and 2D mode) and model forcing (spectral and parametric) to reproduce sensor measured wave setup at several locations in the nearshore area and video measured runup on two beach profiles. For the whole tested configurations, the wave setup is reproduced accurately. Results considering all the sensor locations in the near shore area in 1D and 2D are significantly correlated to the observations with respectively ρ²=0.66 and 0.81; RMSE=0.13 m and 0.08 m without any significant bias. Observations and simulations of runup are investigated in terms of spectra and statistic component. 1D simulations produces an overall overestimation and no significant improvement is obtained by modifying the breaking parameters. The results for 2D simulations are fairly satisfactory reproducing significant swash height (S ), but are significantly improved with spectral forcing than parametric with respectively ρ²=0.73 and 0.71, RMSE=0.19 m and 0.43 m. Generally, the model reproduces accurately the infragravity component but tends to overestimate the incident component, leading to an overestimation of the energy density for moderate wave conditions and more accurate results for higher-energy wave conditions. Results in 2D with spectral forcing show a saturation of the infragravity component with a threshold around Hs=4 to 5 m, which is comparable to the observations collected at Truc Vert Beach. As regards the conventional statistical parameter for runup estimation (R2%) three methods are applied to derive the 2% exceedence value for runup from observed and simulated shoreline vertical elevation time series. When R2% is based on the sum of wave setup and half of the significant swash height, results provided by the model are close or even better than estimations provided by empirical formulas from the bibliography. Defining R2% as the exceeded 2% values of the time, derived considering the cumulative distribution function of the entire water-level time series also provide fairly good results. Results using only runup maxima time series are less satisfactory. In the two last cases, R2% is slightly underestimated for moderate wave conditions (Hs

There is a growing interest for marine flooding related to recent catastrophic events and their unintended consequences in terms of casualties and damages, and to the increasing population and issues along the coasts in a context of changing climate. Consequently, the knowledge on marine flooding has progressed significantly for the last years and this review, focused on storm-induced marine submersions, responds to the need for a synthesis. Three main components are presented in the review: (1) a state-of-the-art on marine submersions from the viewpoint of several scientific disciplines; (2) a selection of examples demonstrating the added value of interdisciplinary approaches to improve our knowledge of marine submersions; (3) a selection of examples showing how the management of future crises or the planning efforts to adapt to marine submersions can be supported by new results or techniques from the research community. From a disciplinary perspective, recent progress were achieved with respect to physical processes, numerical modeling, the knowledge of past marine floods and vulnerability assessment. At a global scale, the most vulnerable coastal areas to marine flooding with high population density are deltas and estuaries. Recent and well-documented floods allow analyzing the vulnerability parameters of different coastal zones. While storm surges can nowadays be reproduced accurately, the modeling of coastal flooding is more challenging, particularly when barrier breaches and wave overtopping have to be accounted for. The chronology of past marine floods can be reconstructed combining historical archives and sediment records. Sediment records of past marine floods localized in back barrier depressions are more adequate to reconstruct past flooding chronology. For the two last centuries, quantitative and descriptive historical data can be used to characterize past marine floods. Beyond providing a chronology of events, sediment records combined with geochronology, statistic analysis and climatology, can be used to reconstruct millennial-scale climate variability and enable a better understanding of the possible regional and local long-term trends in storm activity. Sediment records can also reveal forgotten flooding of exceptional intensity, much more intense than those of the last few decades. Sedimentological and historical archives, combined with highresolution topographic data or numerical hindcast of storms can provide quantitative information and explanations for marine flooding processes. From these approaches, extreme past sea levels height can be determined and are very useful to complete time series provided by the instrumental measurements on shorter time scales. In particular, historical data can improve the determination of the return periods associated with extreme water levels, which are often inaccurate when computed based on instrumental data, due to the presence of gaps and too short time-series. Longterm numerical hindcast of tides and surges can also be used to provide the required time series for statistical analysis. Worst-case scenarios, used to define coastal management plans and strategies, can be obtained from realistic atmospheric settings with different tidal ranges and by shifting the trajectory of storms. Management of future crises and planning efforts to adapt to marine submersions are optimized by predictions of water levels from hydrodynamic models. Such predictions combined with in situ measurements and analysis of human stakes can be used to define a vulnerability index. Then, the efficiency of adaptation measures can be evaluated with respect to the number of lives that could be potentially saved. Numerical experiments also showed that the realignment of coastal defenses could result in water level reduction up to 1 m in the case where large marshes are flooded. Such managed realignment of coastal defenses may constitute a promising adaptation to storm-induced flooding and future sea level rise. From a legal perspective, only a few texts pay specific attention to the risk of marine flooding whether nationally or globally. Recent catastrophic events and their unintended consequences in terms of death and damages have triggered political decisions, like in USA after hurricane Katrina, and in France after catastrophic floods that occurred in 2010. 151-184pp Volume 165 DHA/NEC Earth-Science Reviews

A model has been developed in order to estimate insurance-related losses caused by coastal flooding in France. The deterministic part of the model aims at identifying the potentially flood-impacted sectors and the subsequent insured losses a few days after the occurrence of a storm surge event on any part of the French coast. This deterministic component is a combination of three models: a hazard model, a vulnerability model, and a damage model. The first model uses the PREVIMER system to estimate the water level resulting from the simultaneous occurrence of a high tide and a surge caused by a meteorological event along the coast. A storage-cell flood model propagates these water levels over the land and thus determines the probable inundated areas. The vulnerability model, for its part, is derived from the insurance schedules and claims database, combining information such as risk type, class of business, and insured values. The outcome of the vulnerability and hazard models are then combined with the damage model to estimate the event damage and potential insured losses. This system shows satisfactory results in the estimation of the magnitude of the known losses related to the flood caused by the Xynthia storm. However, it also appears very sensitive to the water height estimated during the flood period, conditioned by the junction between seawater levels and coastal topography, the accuracy for which is still limited by the amount of information in the system.

International audience; Coastal flooding assessment has considerably improved in recent years, especially thanks to the enhancements in probabilistic approaches and in numerical modeling. This study, conducted on the city of Hyères-les-Palmiers (French Riviera), aimed to evaluate how sea level rise could modify coastal flooding hazards in the urban areas located near small estuaries in a microtidal context. A joint probability approach on 3 variables allowed establishing typical storm parameters associated with specific return periods (30 years, 50 years and 100 years), taking into account both offshore conditions (sea level and significant wave height) and the river level. Storm scenarios have then been established based on these parameters and on the chronology of the most impacting recent storm (rising, peak and decrease of the storm). The sea level rise has been simply integrated, considering a rise of 20 cm for year 2030 and a rise of 60 cm for year 2100. The coastal flooding associated with these different scenarios has been simulated with a non-hydrostatic non-linear shallow-water model: SWASH (Zijlema et al., 2011). The calculations have been realized on high resolution DEM (1 to 5 m mesh size) based on LiDAR data, in order to consider the presence of buildings and coastal protections in the flooding simulation. The simulation approach has been validated by reproducing a recent flooding event in this area. Obtained results show the importance of wave overtopping in current coastal flooding hazard in this area. Nevertheless, if Hyères-les-Palmiers is currently little exposed to coastal flooding, these simulations highlight an increasing role of overflowing due to sea level rise by climate change. Consequently, the results show that some areas should be significantly flooded in 2100, even for quite frequent events. These conclusions should be used by the municipality to guide the future land use planning in the exposed areas. Overview of the overtopping and flooding simulation in Ayguade village: 30 years return period storm in 2030, situation after 8 hours of simulated storm This work has been supported by the Hyères-les-Palmiers municipality and the BRGM.

Resume : Cette etude, realisee sur la ville d’Hyeres-les-Palmiers (Var), vise a evaluer l’impact de l’elevation du niveau de la mer sous l’effet du changement climatique sur les submersions marines susceptibles d’affecter les zones urbanisees en contexte microtidal, notamment a proximite de petits estuaires. Les periodes de retour des evenements (30, 50 et 100 ans) ont ete determinees par analyse multi-variee et calcul de probabilites conjointes des parametres de forcages (vagues, niveau marin, niveau de la riviere). L’elevation du niveau de la mer (echeances 2030 et 2100) a ete fixee conformement aux recommandations utilisees pour l’etablissement des Plans de Prevention des Risques Littoraux (respectivement +20 cm et +60 cm). Le modele implemente (SWAN pour la propagation spectrale des vagues, SWASH pour la submersion a terre par franchissement et/ou debordement) rend compte des processus hydrodynamiques a haute-resolution (de 1 a 5 m), en integrant notamment le bâti et l’occupation du sol. Apres validation sur la submersion causee par la tempete de decembre 2008 (seul evenement recent de submersion suffisamment renseigne sur ce littoral), differents scenarios ont ete simules (periodes de retour 30 ans a echeance 2030 et 2100, et periodes de retour 50 et 100 ans a echeance 2100). Les resultats mettent en evidence la vulnerabilite des zones urbanisees littorales le long de la plaine du Ceinturon, et confirment certains elements de connaissance sur les processus locaux, comme le role des lones sur la propagation des eaux sur la zone arriere-littorale, les roles relatifs des processus de franchissement et de debordement dans la submersion totale et le role des ouvrages. Ces resultats pourront desormais etre utilises par la municipalite pour orienter l’amenagement futur dans les zones exposees. Mots-cles : Submersion marine, Tempete, Vague, Surcote, Franchissement par paquets de mer, Modelisation 2D, Zone urbaine.