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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 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 (

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).

As the climate is changing, more applied information on resulting impacts are required to inform adaptation planning. Over the last decade, the amount of information relevant to climate change impact assessment has grown drastically. This can particularly be illustrated in coastal areas, threatened by sea-level rise due to climate change, where a key recent development has been the delivery of precise and accurate topography obtained by Light Detection and Ranging (Li-DAR) at regional and national scales, i.e., respectively, large and small scales. However, using such large, complex, and heterogeneous coastal data sets in a contextual manner is far from straightforward. It is the reason why these developments have not led to easier assessment of coastal climate change impacts so far. In this chapter, we address this interoperability challenge by developing and describing a prototype of Web service combining Li-DAR, tidal, and sea-level rise data to quickly communicate spatial information on the exposure to future coastal flooding along the French coastal zones. We discuss several issues related to data architecture, on-the-fly (geo)-processing capabilities, management of asynchronous workflows, and data diffusion strategies in the context of international standards such as Infrastructure for Spatial Information in Europe (INSPIRE). We believe that our flexible architecture mainly reusing off-the-shelf components is able to improve both complex scenarios’ analysis for experts and dissemination of these future coastal changes to the general public.

National audience; La méthodologie présentée dans le présent article vise à simuler de manière la plus réaliste possible les franchissements par paquets de mer et la submersion qui en résulte en milieu urbain. Elle s'appuie sur des simulations régionales à locales de niveaux d'eau et de vagues pour établir des conditions de forçage pour un modèle à résolution de phase ("vague-à-vague") utilisant des schémas numériques adaptés. Ce modèle est alors utilisé sur un Modèle Numérique d'Elévation (MNE), intégrant les bâtiments, de manière à simuler simultanément le franchissement et la propagation de l'inondation. Cette méthodologie a été appliquée avec le modèle SURF-WB à la submersion survenue à Gâvres (Morbihan) lors de la tempête Johanna (10 mars 2008). Les résultats obtenus s'avèrent tout à fait cohérents avec les observations disponibles (zones de franchissement, étendue de l'inondation, hauteurs d'eau et chronologie). Cette méthode permet d'améliorer la qualité des résultats en milieu urbain par rapport aux approches plus classiques, notamment vis-à-vis de la vitesse des courants à terre. Le développement rapide et récent de ce type de modèle devrait permettre la généralisation de ce type d'approche dans les années à venir. Ce travail a été réalisé dans le cadre du projet JOHANNA (partenariat BRGM-UBO, cofinancé par la Fondation MAIF).

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