Overwash hydrodynamics datasets are mixed in quality and scope, being hard to obtain due to fieldwork experimental difficulties. Aiming to overcome such limitations, this work presents accurate fieldwork data on overwash hydrodynamics, further exploring it to model overwash on a low-lying barrier island. Fieldwork was performed on Barreta Island (Portugal), in December 2013, during neap to spring-tides, when significant wave height reached 2.64 m. During approximately 4 hours, more than 120 shallow overwash events were measured with a video-camera (at 10 Hz), a pressure transducer (at 4 Hz) and a current-meter (at 4 Hz). This high-frequency fieldwork dataset includes runup, overwash number, depth and velocity. Fieldwork data along with information from literature were used to setup XBeach model in non-hydrostatic mode. The baseline model had variable skills over the duration of the overwash each 30 minutes. The baseline model was forced to simulate overwash with different nearshore morphology, grain-size and lagoon water level. An average decrease of about 30% overwash was obtained due to changes in the nearshore episode, performing better during the rising tide than during the falling tide. Model average number of events RMSE (root-mean-square-error) was 7 events morphology, mostly a small vertical growth of the submerged bar. The coarser and finer grain-sizes tests produced an 11% change in overwash, with less overwash on the coarser barrier. Changing lagoon water levels had a reduced effect on overwash hydraulics.@en

Low frequency, high impact storm events can have large impacts on sandy coasts. The physical processes governing these impacts are complex because of the feedback between the hydrodynamics of surges and waves, sediment transport and morphological change. Predicting these coastal changes using a numerical model requires a large amount of computational time, which in the case of an operational prediction for the purpose of Early Warning is not available. For this reason morphodynamic predictions are not commonly included in Early Warning Systems (EWSs). However, omitting these physical processes in an EWS may lead to potential under or over estimation of the impact of a storm event. To solve this problem, a method has been developed to construct a probabilistic Bayesian Network (BN). This BN connects three elements: offshore hydraulic boundary conditions, characteristics of the coastal zone, and onshore hazards, such as erosion and overwash depths and velocities. The hydraulic boundary conditions are derived at a water depth of approximately 20 m from a statistical analysis of observed data using copulas, and site characteristics are obtained from measurements. This BN is trained using output data from many pre-computed process-based model simulations, which connect the three elements. Once trained, the response of the BN is instantaneous and can be used as a surrogate for a process-based model in an EWS in which the BN can be updated with an observation of the hydraulic boundary conditions to give a prediction for onshore hazards. The method was applied to Praia de Faro, Portugal, a low-lying urbanised barrier island, which is subject to frequent flooding. Using a copula-based statistical analysis, which preserves the natural variability of the observations, a synthetic dataset containing 100 events was created, based on 20 years of observations, but extended to return periods of significant wave height of up to 50 years. These events were transformed from offshore to onshore using a 2D XBeach (Roelvink et al., 2009) model. Three BN configurations were constructed, of which the best performing one was able to predict onshore hazards as computed by the model with an accuracy ranging from 81% to 88% and predict events with no significant onshore hazards with an accuracy ranging from 90% to 95%. Two examples are presented on the use of a BN in operational predictions or as an analysis tool. The added value of this method is that it can be applied to many coastal sites: (1) limited observations of offshore hydrodynamic parameters can be extended using the copula method which retains the original observations’ natural variability, (2) the transformation from offshore observations to onshore hazards can be computed with any preferred coastal model and (3) a BN can be adjusted to fit any relevant connections between offshore hydraulic boundary conditions and onshore hazards. Furthermore, a BN can be continuously updated with new information and expanded to include different morphological conditions or risk reduction measures. As such, it is a promising extension of existing EWSs and as a planning tool for coastal managers.@en

This study evaluates the patterns and effects of relative sea-level rise on the tidal circulation of the basin of the Ria Formosa coastal lagoon using a process-based model that is solved on an unstructured mesh. To predict the changes in the lagoon tidal circulation in the year 2100, the model is forced by tides and a static sea level. The bathymetry and the basin geometry are updated in response to sea-level rise for three morphological response scenarios: no bed updating, barrier island rollover, and basin infilling. Model results indicate that sea-level rise (SLR) will change the baseline current velocity patterns inside the lagoon over the ~100-year study period, due to a strong reduction in the area of the intertidal basin. The basin infilling scenario is associated with the most important adjustments of the tidal circulation (i.e., increases in the flood velocities and delays in the ebb tide), together with an increase in the cumulative discharges of the tidal inlets. Under sea-level rise and in the basin infilling scenario, the salt marshes and tidal flats experience increases in the tidal range and current asymmetry. Basin infilling changes the sediment flushing capacity of the lagoon, leading to the attenuation of the flood dominance in the main inlet and the strengthening of the flood dominance in the two secondary inlets. The predictions resulting from these scenarios provide very useful information on the long-term evolution of similar coastal lagoons that experience varying degrees of SLR. This study highlights the need for research focusing on the quantification of the physical and socio-economic impacts of SLR on lagoon systems, thus enabling the development of effective adaptation strategies.@en

Sandy beaches occupy more than one-third of the global coastline1 and have high socioeconomic value related to recreation, tourism and ecosystem services2. Beaches are the interface between land and ocean, providing coastal protection from marine storms and cyclones3. However the presence of sandy beaches cannot be taken for granted, as they are under constant change, driven by meteorological4,5, geological6 and anthropogenic factors1,7. A substantial proportion of the world’s sandy coastline is already eroding1,7, a situation that could be exacerbated by climate change8,9. Here, we show that ambient trends in shoreline dynamics, combined with coastal recession driven by sea level rise, could result in the near extinction of almost half of the world’s sandy beaches by the end of the century. Moderate GHG emission mitigation could prevent 40% of shoreline retreat. Projected shoreline dynamics are dominated by sea level rise for the majority of sandy beaches, but in certain regions the erosive trend is counteracted by accretive ambient shoreline changes; for example, in the Amazon, East and Southeast Asia and the north tropical Pacific. A substantial proportion of the threatened sandy shorelines are in densely populated areas, underlining the need for the design and implementation of effective adaptive measures.@en