The unprecedented resolution of a new 2D modeling approach greatly improves our understanding of how mangroves reduce flood risk.@en

Coastal erosion and flooding are projected to increase during the 21^st century due to sea-level rise (SLR). To prevent adverse impacts of unmanaged coastal development, national organizations can apply a land protection policy, which consists of acquiring coastal land to avoid further development. Yet, these reserved areas remain exposed to flooding and erosion enhanced by SLR. Here, we quantify the exposure of the coastal land heritage portfolio of the French Conservatoire du littoral (Cdl). We find that 30% (~40%) of the Cdl lands owned (projected to be owned) are located below the contemporary highest tide level. Nearly 10% additional surface exposure is projected by 2100 under the high greenhouse gas emissions scenario (SSP5-8.5) and 2150 for the moderate scenario (SSP2-4.5). The increase in exposure is largest along the West Mediterranean coast of France. We also find that Cdl land exposure increases more rapidly for SLR in the range of 0–1 m than for SLR in the range 2–4 m. Thus, near-future uncertainty on SLR has the largest impact on Cdl land exposure evolution and related land acquisition planning. Concerning erosion, we find that nearly 1% of Cdl land could be lost in 2100 if observed historical trends continue. Adding the SLR effect could lead to more than 3% land loss. Our study confirms previous findings that Cdl needs to consider land losses due to SLR in its land acquisition strategy and start acquiring land farther from the coast.

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Monitoring sandy shoreline evolution from years to decades is critical to understand the past and predict the future of our coasts. Optical satellite imagery can now infer such datasets globally, but sometimes with large uncertainties, poor spatial resolution, and thus debatable outcomes. Here we validate and analyse satellite-derived-shoreline positions (1984–2021) along the Atlantic coast of Europe using a moving-averaged approach based on coastline characteristics, indicating conservative uncertainties of long-term trends around 0.4 m/year and a potential bias towards accretion. We show that west-facing open coasts are more prone to long-term erosion, whereas relatively closed coasts favor accretion, although most of computed trends fall within the range of uncertainty. Interannual shoreline variability is influenced by regionally dominant atmospheric climate indices. Quasi-straight open coastlines typically show the strongest and more alongshore-uniform links, while embayed coastlines, especially those not exposed to the dominant wave climate, show weaker and more variable correlation with the indices. Our results provide a spatial continuum between previous local-scale studies, while emphasizing the necessity to further reduce satellite-derived shoreline trend uncertainties. They also call for applications based on a relevant averaging approach and the inclusion of coastal setting parameters to unravel the forcing-response spectrum of sandy shorelines globally.

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Coastal ecosystems provide vital services, but human disturbance causes massive losses. Remaining ecosystems are squeezed between rising seas and human infrastructure development. While shoreline retreat is intensively studied, coastal congestion through infrastructure remains unquantified. Here we analyse 235,469 transects worldwide to show that infrastructure occurs at a median distance of 392 meter from sandy shorelines. Moreover, we find that 33% of sandy shores harbour less than 100 m of infrastructure-free space, and that 23–30% of this space may be lost by 2100 due to rising sea levels. Further analyses show that population density and gross domestic product explain 35–39% of observed squeeze variation, emphasizing the intensifying pressure imposed as countries develop and populations grow. Encouragingly, we find that nature reserves relieve squeezing by 4–7 times. Yet, at present only 16% of world’s sandy shores have a protected status. We therefore advocate the incorporation of nature protection into spatial planning policies.

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Quantitative predictions of marine and aeolian sediment transport in the nearshore–beach–dune system are important for designing Nature-Based Solutions (NBS) in coastal environments. To quantify the impact of the marine-aeolian interactions on shaping NBS, we present a framework coupling three existing process-based models: Delft3D Flexible Mesh, SWAN and AeoLiS. This framework facilitates the continuous exchange of bed levels, water levels and wave properties between numerical models focussing on the aeolian and marine domain. The coupled model is used to simulate the morphodynamic evolution of the Sand Engine mega-nourishment. Results display good agreement with the observed aeolian and marine volumetric developments, showing similar marine-driven erosion from the main peninsula and aeolian-driven infilling of the dune lake. To estimate the magnitude of the interactions between aeolian and marine processes, a comparison between the simulated morphological development by the coupled and stand-alone models was made. This comparison shows that aeolian sediment transport to the foredune, i.e. 214,000 m³ over 5 years, extracts sediment from the marine domain. As a result, the alongshore redistribution of sediment from the main peninsula by marine-driven processes decreased by 70,000 m³, representing 1.7% of the total marine-driven dispersion. From the aeolian perspective, marine-driven deposition and erosion reshape the cross-shore profile, controlling the supply-limited aeolian sediment transport and the magnitude of sediment deposition in the foredunes. In the region with persistent accretion along the Sand Engine's southern flank, a higher than average foredune deposition was predicted due to morphological development of the region where sediment is picked up by aeolian transport. Including these marine processes in the coupled model resulted in an increase of 1.3% in foredune growth in year 1 and up to 6.7% in year 5 along this accretive section. At the northern flank, where the developing lagoon and tidal channel provided increased shelter to the supratidal beach, predicted foredune deposition reduced up to −11.5% over the evaluation period. Our findings show that both aeolian and marine transports impact reshaping the nourished sand, where developments in one domain affect the other. The study findings echo that the interplay between aeolian- and marine-driven morphodynamics could play a relevant role when predicting sandy NBS.

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Sand waves are found on shallow, sandy seabeds throughout the world and their dynamics may pose an imminent threat to offshore construction. Therefore, there is a pressing need to understand bed level dynamics in sand wave areas. These bed level dynamics lead to variations in sand wave shape and migration rate over time. However, these variations cannot be explained with the present-day process-based sand wave models, which all include a purely periodic tidal forcing. To explain these fluctuations a more intricate description of the hydrodynamics is necessary. The aim of this study is to explore the importance of time-varying, non-tidal currents for sand wave dynamics in the North Sea. We adopted the three-dimensional Delft3D-Flexible Mesh model, and were able to reconstruct time-varying, non-tidal currents on top of the periodic tidal forcing, while significantly reducing computation times. The simulated currents and water levels showed a good agreement with in-situ measurements. Compared to the situation with only tidal forcing, the simulated sedimentation and erosion rates were amplified up to 15 times due to time-varying, non-tidal currents. Additionally, periods of net erosion were found at locations in the sand wave transect where tidally forced models only showed net-sedimentation. It is therefore important to consider time-varying, non-tidal currents when predicting future sand wave dynamics in the field.

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Accelerated sea level rise prompts the upscaling of nourishment strategies, either through larger individual nourishment volumes or increased frequency of implementation. In such strategies, the nourished sand may lack time to effectively redistribute in the designated timeframe, leading to significant deformation of the profile over multiple nourishment cycles. This study quantifies subsequent effects, focusing on profile steepening, nourishment lifetimes, and the feasibility of operational objectives. We simulated two common nourishment strategies at a Dutch case study location using the cross-shore morphological model Crocodile over a 50-year timespan under sea level rise rates of 2–32 mm/year. The choice of strategy led to a variation of up to 75% in the total amount of sand used. Our results show increasing profile deformation with nourishment volume applied and duration of the nourishment strategy, with sand accumulating in the nourished section and little dissipation to the lower shoreface. The consequent profile steepening leads to reduced nourishment lifetimes by up to 30%. Additionally, under high sea level rise rates, more erosive coasts experience a reduction in nourishment lifetimes to annual intervals, while less erosive areas require up to four times more sand than currently needed. These findings illustrate key dilemmas in the formulation of future nourishment strategies and highlight the importance of optimizing these strategies to account for sea level rise.

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Projections of high rates of sea level rise have stimulated proposals for adaptation strategies with increasingly high nourishment volumes along sandy beaches. An underlying assumption is that coastal profiles respond rapidly to nourishments by redistributing sediments towards a (new) equilibrium shape. However, this perception may not be valid when high volumes of nourishment are applied, as the profile shape may then undergo significant deformation. Current state-of-the-art modelling techniques often concentrate on a single spatio-temporal scale, either lacking the necessary temporal horizon or failing to provide the required level of cross-shore detail. This article introduces Crocodile, a diffusion based cross-shore model designed to bridge the gap between short- and long-term nourishment modelling. The model simulates the effects of nourishment strategies on coastal volume, coastline position and beach width over a decadal timeframe. It incorporates different elements which compute cross-shore diffusion, sediment exchange with the dune and longshore sediment losses. To test the model performance, a series of idealized nourishment scenarios are examined, along with three case studies along the Dutch coast with different nourishment strategies over the past few decades. The modelled coastal volume, shoreline position and beach width strongly resemble the observations with only a 12% overestimation in profile volume and 13% underestimation in beach width. Averaged over selected periods of nourishment, trends and trend reversals between different strategies are well replicated with slight overestimation for coastal volume trends by 1.5m³/m/yr(10%), while beach width trends are underestimated by 0.2m/yr (15%). Given that the added nourishment volumes are typically in the order of 100m³/m, these model errors are considered sufficiently low to conclude that Crocodile effectively simulates variations in coastal volume, coastline position and beach width over a decadal timeframe in response to different nourishment strategies. Therefore, Crocodile can facilitate the evaluation of future nourishment strategies.

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In this study, we present a novel modeling framework that provides a stylized representation of coastal adaptation and migration dynamics under sea level rise (SLR). We develop an agent-based model that simulates household and government agents adapting to shoreline change and increasing coastal flood risk. This model is coupled to a gravity-based model of migration to simulate coastward migration. Household characteristics are derived from local census data from 2015, and household decisions are calibrated based on empirical survey data on household adaptation in France. We integrate projections of shoreline retreat and flood inundation levels under two Representative Concentration Pathways (RCPs) and account for socioeconomic development under two Shared Socioeconomic Pathways (SSPs). The model is then applied to simulate coastal adaptation and migration between 2015 and 2080. Our results indicate that without coastal adaptation, SLR could drive the cumulative net outmigration of 13,100 up to as many as 21,700 coastal inhabitants between 2015 and 2080 under SSP2–RCP4.5 and SSP5–RCP8.5, respectively. This amounts to between 3.0 %–3.7 % of the coastal population residing in the 1/100-year flood zone in 2080 under a scenario of SLR. We find that SLR-induced migration is largely dependent on the adaptation strategies pursued by households and governments. Household implementation of floodproofing measures combined with beach renourishment reduces the projected SLR-induced migration by 31 %–36 % when compared to a migration under a scenario of no adaptation. A sensitivity analysis indicates that the effect of beach renourishment on SLR-induced migration largely depends on the level of coastal flood protection offered by sandy beaches. By explicitly modeling household behavior combined with governmental protection strategies under increasing coastal risks, the framework presented in this study allows for a comparison of climate change impacts on coastal communities under different adaptation strategies.

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Climate change and human activity threaten sea turtle nesting beaches through increased flooding and erosion. Understanding the environmental characteristics that enable nesting can aid to preserve and expand these habitats. While numerous local studies exist, a comprehensive global analysis of environmental influences on the distribution of sea turtle nesting habitats remains largely unexplored. Here, we relate the distribution of global sea turtle nesting to 22 coastal indicators, spanning hydrodynamic, atmospheric, geophysical, habitat, and human processes. Using state-of-the-art global datasets and a novel 50-km-resolution hexagonal coastline grid (Coastgons), we employ machine learning to identify spatially homogeneous patterns in the indicators and correlate these to the occurrence of nesting grounds. Our findings suggest sea surface temperature, tidal range, extreme surges, and proximity to coral and seagrass habitats significantly influence global nesting distribution. Low tidal ranges and low extreme surges appear to be particularly favorable for individual species, likely due to reduced nest flooding. Other indicators, previously reported as influential (e.g., precipitation and wind speed), were not as important in our global-scale analysis. Finally, we identify new, potentially suitable nesting regions for each species. On average, 23 % of global coastal regions between - 39 ^∘ and 48 ^∘ latitude could be suitable for nesting, while only 7 % is currently used by turtles, showing that the realized niche is significantly smaller than the fundamental niche, and that there is potential for sea turtles to expand their nesting habitat. Our results help identify suitable nesting conditions, quantify potential hazards to global nesting habitats, and lay a foundation for nature-based solutions to preserve and potentially expand these habitats.

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Coastal science has entered a new era of data-driven research, facilitated by satellite data and cloud computing. Despite its potential, the coastal community has yet to fully capitalize on these advancements due to a lack of tailored data, tools, and models. This paper demonstrates how cloud technology can advance coastal analytics at scale. We introduce GCTS, a novel foundational dataset comprising over 11 million coastal transects at 100-m resolution. Our experiments highlight the importance of cloud-optimized data formats, geospatial sorting, and metadata-driven data retrieval. By leveraging cloud technology, we achieve up to 700 times faster performance for tasks like coastal waterline mapping. A case study reveals that 33% of the world’s first kilometer of coast is below 5 m, with the entire analysis completed in a few hours. Our findings make a compelling case for the coastal community to start producing data, tools, and models suitable for scalable coastal analytics.@en

Correction to: Nature Communications, published online 13 March 2023 The original version of this Article contained an error in Fig. 2, in which c was incorrectly described as “middle scenario” where it should have been described as “low scenario”. The correct version of Fig. 2 is: (Figure presented.) which replaces the previous incorrect version: (Figure presented.) This has been corrected in both the PDF and HTML versions of the Article.

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Muddy coasts provide ecological habitats, supply food and form a natural coastal defence. Relative sea level rise, changing wave energy and human interventions will increase the pressure on muddy coastal zones. For sustainable coastal management it is key to obtain information on the geomorphology of and historical changes along muddy areas. So far, little is known about the distribution and behaviour of muddy coasts at a global scale. In this study we present a global scale assessment of the occurrence of muddy coasts and rates of coastline change therein. We combine publicly available satellite imagery and coastal geospatial datasets, to train an automated classification method to identify muddy coasts. We find that 14% of the world’s ice-free coastline is muddy, of which 60% is located in the tropics. Furthermore, the majority of the world’s muddy coasts are eroding at rates exceeding 1 m/yr over the last three decades.

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Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.

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A common inference in research studies of observed and projected changes in global ocean wave height and storm surge, is that such changes are potentially important for long-term coastal management. Despite numerous studies of the impacts of anthropogenic climate change on trends in global wind and waves, a clear link to impacts on sandy coastlines, at global scale, is yet to be demonstrated. This study presents a first-pass assessment of the potential link between historical trends in global wave and storm surge values and recession/progradation rates of sandy coastlines since the 1980s. Global datasets of waves, surge and shoreline change rate are used for this purpose. Over the past 30 + years, we show that there have been clear changes in waves and storm surge at global scale. The data, however, does not show an unequivocal linkage between trends in wave and storm surge climate and sandy shoreline recession/progradation. We conclude that these long-term changes in oceanographic parameters may still be too small to have a measurable impact on shoreline recession/progradation and that primary drivers such as ambient imbalances in the coastal sediment budget may be masking any such linkages.

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Traditionally, independent tools have been used to simulate wave- or wind-driven processes to simulate coastal morphology change. Coupled models that cross the land-sea division and integrate these collective processes can increase our knowledge on complex morphodynamic interactions and improve predictions of the foreshore, beach, and dune evolution. In this paper we present the initial development of a coupled modelling framework capable of numerically predicting the integrated development of coastal landforms, including both marine and aeolian processes, by using a generic model coupling approach that leverages the Basic Model Interface. The aim of this tool is to support the interdisciplinary design of Nature-based Solutions on varying spatiotemporal scales. As shown for the Marker Wadden case, the implemented model functionalities allow for the numerical description of the coast in an integrated manner and thus create opportunities for modeling coastal landform of the nearshore, beach, and dune that would not be possible with a discrete model approach. Specifically, by coupling two discrete numerical models, AeoLiS and XBeach, the aeolian and marine interaction resulted in a more realistic behavior of processes in the intertidal area. After coupling, bed levels compared better to the observations compared to the superpositioned results of both separate model components, which showed the added value and potential of coupled modelling. These findings have implications on the ability to predict spatio-temporal integrated coastal development – including these interacting aerodynamic, hydrodynamic, and ecological processes, which are essential in the interdisciplinary design of NbS.@en

Projections of high rates of sea level rise have stimulated proposals for adaptation strategies with increasingly high nourishment volumes. Nourishment strategies involving higher sand volumes can be accomplished by increasing the volume of individual nourishments or by decreasing the time interval between successive nourishments. The optimal placement of the sediment volumes in the cross-shore and alongshore to attain our coastal management goals is still under debate. From a long term, large scale perspective only the added sediment volume may be considered, regardless of the placement. A widely accepted perception is that coastal profiles respond to nourishment by rapid equilibration to an equilibrium shape including the added sand volume. However, the timescale of the redistribution of the sediment may be slower than the desired spreading rate of the added sediment, causing sediment to accumulate at some parts of the profile, while leaving other elevations sediment starved. This research aims to examine decadal-scale coastal profile response to nourishment strategies upscaled with sea level rise (SLR) whereby potential nourishment strategy impacts for beach width (fluctuations), dune growth potential and momentary coastline are mapped. @en

Marine plastic pollution poses a potential threat to the ecosystem, but the sources and their magnitudes remain largely unclear. Existing bottom-up emission inventories vary among studies for two to three orders of magnitudes (OMs). Here, we adopt a top-down approach that uses observed dataset of sea surface plastic concentrations and an ensemble of ocean transport models to reduce the uncertainty of global plastic discharge. The optimal estimation of plastic emissions in this study varies about 1.5 OMs: 0.70 (0.13–3.8 as a 95% confidence interval) million metric tons yr⁻¹ at the present day. We find that the variability of surface plastic abundance caused by different emission inventories is higher than that caused by model parameters. We suggest that more accurate emission inventories, more data for the abundance in the seawater and other compartments, and more accurate model parameters are required to further reduce the uncertainty of our estimate.

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Dutch coastal policy aims for a safe, economically strong and attractive coast. This is achieved by maintaining the part of the coast that support these functions; the coastal foundation. The coastal foundation is maintained by means of sand nourishments. Up to now, it has been assumed that net transports across the coastal foundation's offshore boundary at the 20 m depth contour are negligibly small. In the framework of the Coastal Genesis 2.0 program we investigated sand transports across this boundary and across other depth contours at the lower shoreface. This paper presents a computationally efficient approach to compute the annual sand transport rates at the Dutch lower shoreface. It is based on the 3D Dutch Continental Shelf Model with Flexible Mesh (3D DCSM-FM), a wave transformation tool and a 1DV sand transport module. We validate the hydrodynamic input against field measurements and present flow, wave and sand transport computations for the years 2013–2017. Our computations show that the net annual sand transport rates along the Dutch coast are determined by peak tidal velocities (and asymmetry thereof), density driven residual flows, wind driven residual flows and waves. The annual mean alongshore transports vary along the continuous 20 m depth contour. The computed total cross-shore transports are onshore directed over the continuous 20 m, 18 m and 16 m depth contours and increase with decreasing water depth. The effect of density difference and wind on the 3D structure of the flow and on the sand transports cannot be neglected along the Dutch lower shoreface. Our computations show that excluding the effect of density results in a significant decrease of the onshore directed transports. Also switching off wind largely counteracts this effect. The net cross-shore transport is determined by a delicate balance between gross onshore and offshore transports, where wave conditions are important. We show an example for Scheveningen where the net cross-shore transport is onshore directed when including all wave conditions but would be offshore directed when excluding waves higher than 3.5 m. In contrast, at Callantsoog the highest waves contribute more to the offshore directed transports. These results suggest that storm conditions play an important role in the magnitude and direction of the net annual transport rates at the lower shoreface.

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The Saudi Arabian tourism sector is growing, and its economy has flourished over the last decades. This has resulted in numerous coastal developments close to large economic centers, while many more are proposed or planned. The coastal developments have influenced the behavior of the shoreline in the past. Here we undertake a national assessment on the state of the coast of Saudi Arabia based on recent data sets on historic and future shoreline positions. While at national scale the shoreline is found to be stable over the last three decades, the Red Sea coast shows a regional-mean retreat rate while the Gulf coast shows a regional-mean prograding behavior. Detailed analysis of the temporal evolution of shoreline position at selected locations show that human interventions may have accelerated shoreline retreat along adjacent shorelines, some of which are Marine Protected Areas. Furthermore, reef-fronted coastal sections have a mean accretive shoreline change rate, while the open coast shows a mean retreat rate. Future shoreline projections under RCP 4.5 and RCP 8.5 show that large parts of the shoreline may experience an accelerated retreat or a change in its regime from either stable or sprograding to retreating. Under the high emission RCP 8.5 scenario, the length of coastline projected to retreat more than doubles along the Red Sea coast, and approximately triples along the Gulf coast in 2100. At national scale, the Saudi Arabian coastline is projected to experience regional-mean retreats of ~30 m and of ~130 m by 2050 and 2100 under both RCPs considered in this study. These results indicate that effective adaptation strategies will be required to protect areas of ecological and economic value, and that climate resilience should be a key consideration in planned or proposed coastal interventions.

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