Episodic coastal hazards associated to sea storms are responsible for sudden and intense changes in coastal morphology. Climate change and local anthropogenic activities such as river regulation and urban growth are raising risk levels in coastal hotspots, like low-lying areas of river deltas. This urges to revise present management strategies to guarantee their future sustainability, demanding a detailed diagnostic of the hazard evolution. In this paper, flooding and erosion under current and future conditions have been assessed at local scale at the urban area of Riumar, a touristic enclave placed at the Ebro Delta (Spain). Process-based models have been used to address the interaction between beach morphology and storm waves, as well as the influence of coastal environment complexity. Storm waves have been propagated with SWAN wave model and have provided the forcings for XBeach, a 2DH hydro-morphodynamic model. Results show that future trends in sea level rise and wave forcing produce non-linear variations of the flooded area and the volume of mobilized sediment resulting from marine storms. In particular, the balance between flooding and sediment transport will shift depending on the relative sea level. Wave induced flooding and long-shore sand transport seem to be diminished in the future, whereas static sea level flooding and cross-shore sediment transport are exacerbated. Therefore, the characterization of tipping points in the coastal response can help to develop robust and adaptive plans to manage climate change impact in sandy wave dominated coasts with a low-lying hinterland and a complex shoreline morphology.

Wave extreme events can be understood as the combination of Storm-intensity, Directionality and Intra-time distribution. However, the dependence structure among these factors is still unclear. A methodology has been developed to model wave-storms whose components are linked together. The model is composed by three parts: an intensity module, a wave directionality module, and an intra-time distribution module. In the Storm-intensity sub-model, generalized Pareto distributions and hierarchical Archimedean copulas have been used to characterize the storm energy, unitary energy, peak wave-period and duration. In the Directionality and Intra-time sub-models, the wave direction (at the peak of the storm) and the storm growth–decay rates are linked to the variables from the intensity model, respectively. The model is applied to the Catalan coast (NW Mediterranean). The outcomes denote spatial patterns that coincide with the state of knowledge. The proposed methodology is able to provide boundary conditions for wave and near-shore studies, saving computational time and establishing the dependence of the proposed variables. Such synthetic storms reproduce the inter-variable co-dependence of the original data.Peer ReviewedPostprint (published version

The characterization of future wave-storms and their relationship to large-scale climate can provide useful information for environmental or urban planning at coastal areas. A hybrid methodology (process-based and statistical) was used to characterize the extreme wave-climate at the northwestern Black Sea. The Simulating WAve Nearshore spectral wave-model was employed to produce wave-climate projections, forced with wind-fields projections for two climate change scenarios: Representative Concentration Pathways (RCPs) 4.5 and 8.5. A non-stationary multivariate statistical model was built, considering significant wave-height and peak-wave-period at the peak of the wave-storm, as well as storm total energy and storm-duration. The climate indices of the North Atlantic Oscillation, East Atlantic Pattern, and Scandinavian Pattern have been used as covariates to link to storminess, wave-storm threshold, and wave-storm components in the statistical model. The results show that, first, under both RCP scenarios, the mean values of significant wave-height and peak-wave-period at the peak of the wave-storm remain fairly constant over the 21st century. Second, the mean value of storm total energy is more markedly increasing in the RCP4.5 scenario than in the RCP8.5 scenario. Third, the mean value of storm-duration is increasing in the RCP4.5 scenario, as opposed to the constant trend in the RCP8.5 scenario. The variance of each wave-storm component increases when the corresponding mean value increases under both RCP scenarios. During the 21st century, the East Atlantic Pattern and changes in its pattern have a special influence on wave-storm conditions. Apart from the individual characteristics of each wave-storm component, wave-storms with both extreme energy and duration can be expected in the 21st century. The dependence between all the wave-storm components is moderate, but grows with time and, in general, the severe emission scenario of RCP8.5 presents less dependence between storm total energy and storm-duration and among wave-storm components.

Storm surges are one of the main drivers for extreme flooding at the coastal areas. Such events can be characterized with the maximum level in an extreme storm surge event (surge peak), as well as the duration of the event. Surge projections come from a barotropic model for the 1950–2100 period, under a severe climate change scenario (RCP 8.5) at the northeastern Spanish coast. The relationship of extreme storm surges to three large-scale climate patterns was assessed: North Atlantic Oscillation ( $NAO$ ), East Atlantic Pattern ( $EAWR$ ), and Scandinavian Pattern ( $SC$ ). The statistical model was built using two different strategies. In Strategy #1, the joint probability density was characterized by a moving-average series of stationary Archimedean copula, whereas in Strategy #2, the joint probability density was characterized by a non-stationary probit copula. The parameters of the marginal distribution and the copula were defined with generalized additive models. The analysis showed that the mean values of surge peak and event duration were constant and were independent of the proposed climate patterns. However, the values of $NAO$ and $SC$ influenced the threshold and the storminess of extreme events. According to Strategy #1, the variance of the surge peak and event duration increased with a fast shift of negative $SC$ and a positive $NAO$ , respectively. Alternatively, Strategy #2 showed that the variance of the surge peak increased with a positive $EAWR$ . Both strategies coincided in that the joint dependence of the maximum surge level and the duration of extreme surges ranged from low to medium degree. Its mean value was stationary, and its variability was linked to the geographical location. Finally, Strategy #2 helped determine that this dependence increased with negative $NAO$ .

Barrier reefs dissipate most incoming wind-generated waves and, as a consequence, regulate the morphodynamics of its inbounded shorelines. The coastal protective capacity of reefs may nevertheless be compromised by climate change effects, such as reef degradation and sea-level rise. To assess the magnitude of these climate change effects, an analysis of the waves propagating across the barrier reef is carried out in Flic-en-Flac beach, Mauritius, based on scenarios of future sea levels and predicted coral reef condition. In the study, both the mean wave climate and extreme event conditions are considered. The results show that lower coral structure complexity jointly with higher water levels allow for higher waves to pass over the reef and, therefore, to reach the shoreline. In addition, modeling for cyclonic conditions showed that nearshore waves would also increase in height, which could lead to major coastal morphodynamic changes. Measures aimed at preserving the coral reef may allow the system to accommodate for the gradual climatic changes forecasted while keeping its coastal protective function.

The sea level station operating since 1996 at Mazagón (Huelva, Spain) has been progressively upgraded to fit tsunami warning requirements, due to its location in one of the main regions at risk. Its radar water level sensor was complemented in 2017, with the addition of a pressure sensor. The performance of both sea level sensors and their response to sea level oscillations, at different frequencies, is assessed. Particular emphasis is put on the effect of extreme events, such as Storm Emma, when alternative methods to obtain 1-min data are tested, in contrast to the one based on arithmetic means. The overall differences are small, for the whole period of study (centered-root-mean-square-error below 1cm, for 5-min and hourly data; similar tidal parameters and sea level oscillations with periods between 30s and 5 min). However, during Storm Emma, the pressure sensor presents sensibly lower readings than the radar, with the centered-root-mean-square-error rising to 80mm on the 2^nd of March of 2018. A new method to compute 1-min data, based on medians, reduced this value to 10 mm for the same day.