A method to characterize the different extreme waves for islands exposed to various wave regimes: a case study devoted to Reunion Island

This paper outlines a new approach devoted to the analysis of extreme waves in presence of several wave regimes. It entails discriminating the different wave regimes from offshore wave data using classification algorithms, before conducting the extreme wave analysis for each regime separately. The concept is applied to the pilot site of Reunion Island which is affected by three main wave regimes: southern waves, trade-wind waves and cyclonic waves. Several extreme wave scenarios are determined for each regime, based on real historical cases (for cyclonic waves) and extreme value analysis (for non-cyclonic waves). For each scenario, the nearshore wave characteristics are modelled all around Reunion Island and the linear theory equations are used to back calculate the equivalent deep-water wave characteristics for each portion of the coast. The relative exposure of the coastline to the extreme waves of each regime is determined by comparing the equivalent deep-water wave characteristics. <br><br> This method provides a practical framework to perform an analysis of extremes within a complex environment presenting several sources of extreme waves. First, at a particular coastal location, it allows for inter-comparison between various kinds of extreme waves that are generated by different processes and that may occur at different periods of the year. Then, it enables us to analyse the alongshore variability in wave exposition, which is a good indicator of potential runup extreme values. For the case of Reunion Island, cyclonic waves are dominant offshore around the island, with equivalent deep-water wave heights up to 18 m for the northern part. Nevertheless, due to nearshore wave refraction, southern waves may become as energetic as cyclonic waves on the western part of the island and induce similar impacts in terms of runup and submersion. This method can be easily transposed to other case studies and can be adapted, depending on the data availability

Uncertainties in shoreline projections to 2100 at Truc Vert Beach (France): Role of sea‐level rise and equilibrium model assumptions

Sandy shorelines morphodynamics responds to a myriad of processes interacting at different spatial and temporal scales, making shoreline predictions challenging. Shoreline modeling inherits uncertainties from the primary driver boundary conditions (e.g., sea-level rise and wave forcing) as well as uncertainties related to model assumptions and/or misspecifications of the physics. This study presents an analysis of the uncertainties associated with future shoreline evolution at the cross-shore transport dominated sandy beach of Truc Vert (France) over the 21st century. We explicitly resolve wave-driven shoreline change using two different equilibrium modeling approaches to provide new insight into the contributions of sea-level rise, and free model parameters uncertainties on future shoreline change in the frame of climate change. Based on a Global Sensitivity Analysis, shoreline response during the first half of the century is found to be mainly sensitive to the equilibrium model parameters, with the influence of sea-level rise emerging in the second half of the century (∼2050 or later), under several simulated scenarios. The results reveal that the seasonal and interannual variability of the predicted shoreline position is sensitive to the choice of the wave-driven equilibrium-based model. Finally, we discuss the importance of the chronology of wave events in future shoreline change, calling for more continuous wave projection time series to further address uncertainties in future wave conditions. Our contribution demonstrates that unmitigated climate change can result in shoreline retreat of several tens of meters by 2100, even for sectors that have been stable or slightly accreting over the last century

Probabilistic sea level projections at the coast by 2100

As sea level is rising along many low-lying and densely populated coastal areas, affected communities are investing resources to assess and manage future socio-economic and ecological risks created by current and future sea level rise. Despite significant progress in the scientific understanding of the physical mechanisms contributing to sea level change, projections beyond 2050 remain highly uncertain. Here, we present recent developments in the probabilistic projections of coastal mean sea level rise by 2100, which provides a summary assessment of the relevant uncertainties. Probabilistic projections can be used directly in some of the decision frameworks adopted by coastal engineers for infrastructure design and land use planning. However, relying on a single probability distribution or a set of distributions based upon a common set of assumptions can understate true uncertainty and potentially misinform users. Here, we put the probabilistic projections published over the last 5 years into context

Climate change-driven coastal erosion modelling in temperate sandy beaches: Methods and uncertainty treatment

Developing future projections of shoreline change requires a good understanding of the driving coastal processes. These processes result primarily from the combination of mean sea level, waves, storm surges and tides, which are affected by global and regional climate change, and whose uncertainty increases with time. This paper reviews the current state of the art of methods used to model climate change-induced coastal erosion focusing on how climate change-related drivers and the associated uncertainty are considered. We identify research gaps, describe and analyse the key components of a comprehensive framework to derive future estimates of shoreline change and make suggestions for good practice. Within the scope of the review, we find that although significant progress has been made over the last decade, most of the studies limit uncertainty sampling to considering ranges of variation of forcing variables and ensembles of emissions scenarios, and applications with high level of probabilistic development remain few. Further research is necessary to fully (a) incorporate projected time series of coastal drivers into the erosion models, including bias correction; (b) sufficiently sample the uncertainty associated with each step of the top-down approach, including the consideration of different emission scenarios, inter- and intra-model variability, and multiple runs of erosion models or model ensembles; and (c) reduce uncertainty in shoreline change estimates by developing better datasets and model parameterisations, and progressing in detection and attribution

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk

This study provides a literature-based comparative assessment of uncertainties and biases in global to world-regional scale assessments of current and future coastal flood risks, considering mean and extreme sea-level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea-level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio-economic development (factors 2.3–5.8), digital elevation data (factors 1.2–3.8), ice sheet models (factor 1.6–3.8) and greenhouse gas emissions (factors 1.6–2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth-damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea-levels, storm surges, tides and waves. Advancing the state-of-the-art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth-damage functions would be best reduced through open community-based efforts, in which many scholars work together in collecting and validating these data

Sea-level rise: from global perspectives to local services

Coastal areas are highly diverse, ecologically rich, regions of key socio-economic activity, and are particularly sensitive to sea-level change. Over most of the 20th century, global mean sea level has risen mainly due to warming and subsequent expansion of the upper ocean layers as well as the melting of glaciers and ice caps. Over the last three decades, increased mass loss of the Greenland and Antarctic ice sheets has also started to contribute significantly to contemporary sea-level rise. The future mass loss of the two ice sheets, which combined represent a sea-level rise potential of ∼65 m, constitutes the main source of uncertainty in long-term (centennial to millennial) sea-level rise projections. Improved knowledge of the magnitude and rate of future sea-level change is therefore of utmost importance. Moreover, sea level does not change uniformly across the globe and can differ greatly at both regional and local scales. The most appropriate and feasible sea level mitigation and adaptation measures in coastal regions strongly depend on local land use and associated risk aversion. Here, we advocate that addressing the problem of future sea-level rise and its impacts requires (i) bringing together a transdisciplinary scientific community, from climate and cryospheric scientists to coastal impact specialists, and (ii) interacting closely and iteratively with users and local stakeholders to co-design and co-build coastal climate services, including addressing the high-end risks

Evaluación del riesgo de inundación a múltiples componentes en la costa del Maresme

The coast is one of the areas most affected by natural hazards, with floods being the most frequent and significant of these in terms of their induced impacts, so any management scheme requires their evaluation. In coastal areas, flooding is a hazard associated with different processes acting at different scales: coastal storms, flash floods and sea level rise (SLR). To address the problem as a whole, this study presents a methodology to undertake a preliminary integrated risk assessment of the magnitude of each flood component, taking into account their scope (extension of the affected area) and their temporal scale. The risk is quantified using specific indicators to assess the hazard magnitude (for each component) and the consequences. This allows for a robust comparison of the spatial risk distribution along the coast in order to identify both the most at-risk areas and the most influential risk components. This methodology is applied to a stretch of coastline (Maresme, Catalonia) representative of the Spanish Mediterranean coast. The results obtained characterise this coastline as an area with a relatively low overall risk, although some hotspots are identified as having high-risk values. Resumen: La costa es una de las zonas más sometidas a riesgos naturales, siendo la inundación uno de los más frecuentes e importantes en términos de daños inducidos, por lo que cualquier esquema de gestión requiere evaluación. La inundación en zonas costeras es una amenaza natural asociada a diferentes procesos que actúan a distintas escalas: tormentas costeras, riadas y subida del nivel del mar (SNM). Para abarcar la totalidad del problema, este trabajo propone una metodología para la evaluación preliminar del riesgo integrado de inundación costera a una escala regional que permite evaluar la magnitud de cada componente teniendo en cuenta su alcance (extensión de la zona afectada) y su escala temporal. El riesgo se cuantifica en función de unos indicadores específicos que valoran la magnitud de la amenaza para cada componente y las consecuencias. Esto permite comparar robustamente la distribución espacial del riesgo a lo largo de la costa, para identificar tanto zonas de mayor riesgo como las componentes que más contribuyen al mismo. Aplicamos esta metodología a un tramo de costa característica del Mediterráneo español (Maresme, Cataluña). Los resultados permiten caracterizar esta costa como un área con un riesgo global relativamente bajo, pero algunos puntos singulares con riesgo alto

Uncertainty and bias in global to regional scale assessments of current and future coastal flood risk

This study provides a literature-based comparative assessment of uncertainties and biases in global to world-regional scale assessments of current and future coastal flood risks, considering mean and extreme sea-level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea-level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio-economic development (factors 2.3–5.8), digital elevation data (factors 1.2–3.8), ice sheet models (factor 1.6–3.8) and greenhouse gas emissions (factors 1.6–2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth-damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea-levels, storm surges, tides and waves. Advancing the state-of-the-art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth-damage functions would be best reduced through open community-based efforts, in which many scholars work together in collecting and validating these data

Erosion consequences on beach functions along the Maresme coast (NW Mediterranean, Spain)

A methodology to analyse the influence of erosion on beach functions at a regional scale is presented. The method considers erosion hazards at different timescales and assesses consequences by evaluating impacts on recreation and protection functions. To provide useful information to decision makers for managing these functions, hazard and consequences are integrated at the municipal level within a risk matrix. This methodology is applied at the Maresme, a 45-km sandy coast situated northward of Barcelona, which supports a strong urban and infrastructure development as well as an intensive beach recreational use. Obtained results indicate differentiated erosion implications along the region, depending on the management target considered. Thus, southern municipalities are more prone to erosion affecting the protection function of the beach and leisure use by the local population, whereas erosion will have a greater effect on foreign tourism in the northern municipalities. These results highlight the necessity to employ an articulated erosion risk assessment focusing on specific targets depending on the site in question. This methodology can help coastal managers to adopt tailored measures to manage erosion impacts towards specific goals, in a more efficient and sustainable manner

Sea-level rise: From global perspectives to local services

Coastal areas are highly diverse, ecologically rich, regions of key socio-economic activity, and are particularly sensitive to sea-level change. Over most of the 20th century, global mean sea level has risen mainly due to warming and subsequent expansion of the upper ocean layers as well as the melting of glaciers and ice caps. Over the last three decades, increased mass loss of the Greenland and Antarctic ice sheets has also started to contribute significantly to contemporary sea-level rise. The future mass loss of the two ice sheets, which combined represent a sea-level rise potential of ∼65 m, constitutes the main source of uncertainty in long-term (centennial to millennial) sea-level rise projections. Improved knowledge of the magnitude and rate of future sea-level change is therefore of utmost importance. Moreover, sea level does not change uniformly across the globe and can differ greatly at both regional and local scales. The most appropriate and feasible sea level mitigation and adaptation measures in coastal regions strongly depend on local land use and associated risk aversion. Here, we advocate that addressing the problem of future sea-level rise and its impacts requires (i) bringing together a transdisciplinary scientific community, from climate and cryospheric scientists to coastal impact specialists, and (ii) interacting closely and iteratively with users and local stakeholders to co-design and co-build coastal climate services, including addressing the high-end risks