Coastal Flooding in the Maldives Induced by Mean Sea-Level Rise and Wind-Waves: From Global to Local Coastal Modelling

The Maldives, with one of the lowest average land elevations above present-day mean sea level, is among the world regions that will be the most impacted by mean sea-level rise and marine extreme events induced by climate change. Yet, the lack of regional and local information on marine drivers is a major drawback that coastal decision-makers face to anticipate the impacts of climate change along the Maldivian coastlines. In this study we focus on wind-waves, the main driver of extremes causing coastal flooding in the region. We dynamically downscale large-scale fields from global wave models, providing a valuable source of climate information along the coastlines with spatial resolution down to 500 m. This dataset serves to characterise the wave climate around the Maldives, with applications in regional development and land reclamation, and is also an essential input for local flood hazard modelling. We illustrate this with a case study of HA Hoarafushi, an atoll island where local topo-bathymetry is available. This island is exposed to the highest incoming waves in the archipelago and recently saw development of an airport island on its reef via land reclamation. Regional waves are propagated toward the shoreline using a phase-resolving model and coastal inundation is simulated under different mean sea-level rise conditions of up to 1 m above present-day mean sea level. The results are represented as risk maps with different hazard levels gathering inundation depth and speed, providing a clear evidence of the impacts of the sea level rise combined with extreme wave events

Evolution of coastal zone vulnerability to marine inundation in a global change context. Application to Languedoc Roussillon (France)

The coastal system is likely to suffer increasing costal risk in a global change context. Its management implies to consider those risks in a holistic approach of the different vulnerability components of the coastal zone, by improving knowledge of hazard and exposure as well as analyzing and quantifying present day and future territory vulnerability. The ANR/VMC2007/MISEEVA project (2008-2011) has applied this approach on Languedoc Roussillon region in France. MISEEVA approach relies on several scenarios for 2030 and 2100, in terms of meteorology (driver of coastal hazard), sea level rise, and also considering further trends in demography and economy, and possible adaption strategies Hazard has been modeled (SWAN, MARS and SURFWB), on the base of the presentday situation, sea level rise hypotheses, and existing or modeled data, of extreme meteorological driving f. It allowed to assess the possible surges ranges and map coastal zone exposure to: - a permanent inundation (considering sea level rise in 2030 and 2100, - a recurrent inundation (considering sea level rise and extreme tidal range) - an exceptional inundation (adding extreme storm surge to sea level rise and tidal range). In 2030, exposure will be comparable to present day exposure. In 2100, extreme condition will affect a larger zone. Present days social and economic components of the coastal zone have been analyzed in terms of vulnerability and potential damaging. Adaptation capacity was approached by public inquiries and interviews of stakeholders and policy makers, based on existing planning documents The knowledge of the present day system is then compared to the possible management strategies that could be chosen in the future, so to imagine what would be the evolution of vulnerability to marine inundation, in regards to these possible strategies

Le couple anticipation/décision aux prises avec l'exceptionnel, l'imprévu et l'incertitude

International audienceAnticipation and decision-making in crisis situations are subject of numerous studies that highlight the polysemy of these concepts as well as the difficulties regularly encountered during their implementation (context of uncertainty, format and circulation of information, different perceptions of the situation between actors and geographical scales, etc.). Through two case studies located during the Irma-José-Maria crisis, one observed in the National French Crisis Center and the other experienced by a government operator, at a more regional level, this article illustrates these obstacles and highlights the fragmentation of the anticipation/decision couple in the practice of the different ORSEC levels. It appears that the lack of a shared vision within and between the crisis units on the nature, time horizon and methodological framework of the anticipation function were as many obstacles to its effective implementation during the cyclone sequence. This situation is due in particular to the co-existence of different ministerial cultures of anticipation. As time appears to be a structuring and critical element of an adaptive and shared anticipatory approach, the authors argue for an understanding of the anticipation/decision-making relationship in terms of a continuum, assuming the plurality of cultures and integrating all temporalities.L'anticipation et la prise de décision en situation de crise font l'objet de nombreuses études qui mettent en avant la polysémie de ces notions ainsi que les difficultés régulièrement rencontrés lors de leur mise en oeuvre (contexte d'incertitude, format et circulation de l'information, perceptions différentes de la situation entre les acteurs et les échelles géographiques, etc.). A travers deux études de cas situées pendant la crise Irma-José-Maria, l'une observée en CIC, au niveau interministériel, et l'autre vécue par un opérateur de l'Etat, au niveau territorial, cet article illustre ces obstacles et souligne la fragmentation du couple anticipation/décision dans la pratique des différents niveaux ORSEC. Il apparaît en effet que l'absence d'une vision partagée au sein et entre les cellules de crise sur la nature, l'horizon temporel et le cadre méthodologique de la fonction anticipation ont été autant d'entraves à sa mise en oeuvre effective pendant la séquence cyclonique. Cette situation trouve notamment son origine dans la coexistence de cultures ministérielles différentes de l'anticipation. Le temps apparaissant comme un élément structurant et critique d'une démarche anticipative adaptative et partagée, les auteurs plaident pour une compréhension du couple anticipation / prise de décision en termes de continuum, assumant la pluralité des cultures et intégrant l'ensemble des temporalités. Abstract Anticipation and decision-making in crisis situations are subject of numerous studies that highlight the polysemy of these concepts as well as the difficulties regularly encountered during their implementation (context of uncertainty, format and circulation of information, different perceptions of the situation between actors and geographical scales, etc.). Through two case studies located during the Irma-José-Maria crisis, one observed in the National French Crisis Center and the other experienced by a government operator, at a more regional level, this article illustrates these obstacles and highlights the fragmentation of the anticipation/decision couple in the practice of the different ORSEC levels. It appears that the lack of a shared vision within and between the crisis units on the nature, time horizon and methodological framework of the anticipation function were as many obstacles to its effective implementation during the cyclone sequence. This situation is due in particular to the coexistence of different ministerial cultures of anticipation. As time appears to be a structuring and critical element of an adaptive and shared anticipatory approach, the authors argue for an understanding of the anticipation/decision-making relationship in terms of a continuum, assuming the plurality of cultures and integrating all temporalities

Spatial variability of extreme wave height along the Atlantic and Channel French coast

International audienceThe knowledge of wave climate, and more particularly of the extremes and historical large wave events, is crucial for offshore infrastructure design as well as coastal applications such as defences design or submersion and erosion risks assessment. When it comes to analysing the spatial variability of extremes, a key issue is to ensure a uniform approach to get spatially comparable results. The present paper describes a new wave extreme values database for the French Atlantic and Channel coasts (BoBWA-X) relying on: (1) the wave hindcast BoBWA-10kH (1958-2002; Charles et al., 2012); (2) a POT/GPD method adapted to reduce the operator subjectivity in the threshold choice so as to ensure reproducible and comparable results along the coasts. The obtained extreme wave heights of 43 points distributed along the coast, exhibit a significant spatial variability delimiting 4 relatively homogenous areas, with 100-year return wave heights ranging between 3 m (East Cotentin) and 16 m (Western Brittany). These spatial distributions are analyzed in terms of spatial variability of the statistical parameters, using a depth-independent analysis and 7 quite homogeneous coastal segments are identified. The delimited segments are directly related to the wave climate and the exposure to classical storm waves. Therefore, they show similar repartition frontiers with the delimited areas by the Hs100 spatial variations but with a higher degree of precision. The analysis of past events over the 1958-2002 period of the BoBWA-10kH dataset shows 7 events characterized by wave heights with return periods larger than 50 years. The extent and intensity of these events vary greatly from one zone to another. For instance, the 1979 event affected 950 km of coast. Brittany is a particularly exposed region, with two events (1958, 1990) whose Hs return period (Rp(Hs)) ranges between 70 and 100 years. The highest return period is detected in the Dover Strait area (Rp(Hs) = 107 years) during the Daria storm (January 25th 1990). The spatial variability of these large wave events is discussed regarding the atmospheric conditions and their similarities with classical weather types. Both databases (BoBWA-10kH and BoBWA-X) are available at http://bobwa.brgm.fr

Revealing the dependence structure of scenario-like inputs in numerical environmental simulations using Gaussian Process regression

Document de travailModel uncertainties (related to the structure/form of the model or to the choice of "appropriate" physical laws) are generally integrated in environmental long running numerical simulators via scenario-like variables. By focusing on Gaussian Processes (GP), we show how different categorical covariance functions (exchangeable, ordinal, group, etc.) can bring valuable insights into the inter-dependencies of these scenarios. Supported by two real case applications (cycloneinduced waves and reservoir modelling), we have proposed a cross-validation approach to select the most appropriate covariance function by finding a trade-off between predictability, explainability, and stability of the covariance coefficients. This approach can be effectively used to support (or contradict) some physical assumptions regarding the scenario-like input. Through comparison to tree-based techniques, we show that GP models can be considered a satisfactory compromise when only a few model runs (~100) are available by presenting a high predictability and a concise and graphical way to map the dependence

Revealing the interlevel dependence structure of categorical inputs in numerical environmental simulations with kernel model selection

International audienceModel uncertainties are generally integrated in environmental long-running numerical simulators via a categorical variable. By focusing on Gaussian process (GP) models, we show how different categorical kernel models (exchangeable, ordinal, group, etc.) can bring valuable insights into the correlation of the simulator output values computed for different levels of the categorical variable, i.e., the interlevel dependence structure. Supported by two real case applications (cyclone-induced waves and reservoir modeling), we have proposed a cross-validation approach to select the most appropriate kernel by finding a trade-off between predictability, explainability, and stability of the covariance coefficients. This approach can be used effectively to support some physical assumptions regarding the categorical variable. Through comparison to tree-based techniques, we show that GP models can be considered a satisfactory compromise when only a few model runs (∼100) are available by presenting a high predictability and a concise and graphical way to map the interlevel dependence structure

Improved metamodels for predicting high-dimensional outputs by accounting for the dependence structure of the latent variables: application to marine flooding

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 < 10). One commonly-used approach is to build one metamodel per latent variable by assuming independence between the latent variables. Using two real cases of marine flooding, we show that the predictive performance of the metamodelling approach (relying on kriging metamodels) can significantly be improved when the dependence structure of the latent variables is accounted for. Our tests show that the most efficient approach relies on the clustering in the space of the latent variables (here with k-means algorithm). Complementing the approach with a kriging metamodel specifically dedicated to handle vector-valued variables allows an additional increase of predictability, but only if two conditions are jointly met: (1) the number of training samples is sufficiently high to learn the dependence structure over the respective clusters; (2) a careful selection of the number of clusters has been performed

CoastSnap Nouvelle-Aquitaine : déploiement d'une plateforme participative pour mesurer la dynamique des plages en Nouvelle-Aquitaine

International audienceLes plages exposées à l'action des vagues et des courants tidaux ou estuariens évoluent sur une large gamme d'échelles spatio-temporelles pouvant menacer les activités et infrastructures humaines. La mise en place de programmes de mesures régulières en zone littorale est cruciale pour suivre et comprendre cette variabilité, et informer correctement les gestionnaires du littoral. L'inclusion des usagers du littoral dans les programmes d'observation représente pour les scientifiques une nouvelle source de données dont l'acquisition se fait à une fréquence élevée (quotidienne) et à moindre cout. C'est dans cette perspective que l'Observatoire de la Côte de Nouvelle-Aquitaine (OCNA) a récemment décliné à l'échelle régionale le réseau international CoastSnap qui s'appuie sur la collecte de photos citoyennes du littoral acquises dans des conditions contrôlées. Les chaines de traitements CoastSnap originelles sont conçues pour être appliquées à des environnements microtidaux où la ligne d'eau extraite des photos citoyennes peut être utilisée comme descripteur du trait de côte. En contexte méso à macrotidal (e.g. littoral de Nouvelle-Aquitaine) d'autres algorithmes doivent être mis en oeuvre pour exploiter scientifiquement ces photos. Cette communication présente les caractéristiques des premières stations CoastSnap installées en Nouvelle-Aquitaine, les traitements des photos à mettre en oeuvre ainsi qu'un exemple d'exploitation possible