Tropical-cyclone impacts can have devastating effects on the population, infrastructure, and natural habitats. However, predicting these impacts is difficult due to the inherent uncertainties in the storm track and intensity. In addition, due to computational constraints, both the relevant ocean physics and the uncertainties in meteorological forcing are only partly accounted for. This paper presents a new method, called the Tropical Cyclone Forecasting Framework (TC-FF), to probabilistically forecast compound flooding induced by tropical cyclones, considering uncertainties in track, forward speed, and wind speed and/or intensity. The open-source method accounts for all major relevant physical drivers, including tide, surge, and rainfall, and considers TC uncertainties through Gaussian error distributions and autoregressive techniques. The tool creates temporally and spatially varying wind fields to force a computationally efficient compound-flood model, allowing for the computation of probabilistic wind and flood hazard maps for any oceanic basin in the world as it does not require detailed information on the distribution of historical errors. A comparison of TC-FF and JTWC operational ensembles, both based on DeMaria et al. (2009), revealed minor differences of <10 %, suggesting that TC-FF can be employed as an alternative, for example, in data-scarce environments. The method was applied to Cyclone Idai in Mozambique. The underlying physical model showed reliable skill in terms of tidal propagation, reproducing the storm surge generation during landfall and flooding near the city of Beira (success index of 0.59). The method was successfully applied to forecasting the impact of Idai with different lead times. The case study analyzed needed at least 200 ensemble members to get reliable water levels and flood results 3 d before landfall (<1 % flood probability error and <20 cm sampling errors). Results showed the sensitivity of forecasting, especially with increasing lead times, highlighting the importance of accounting for cyclone variability in decision-making and risk management.@en

An unstructured hydrodynamic model is presented that is able to simulate 2D nearshore hydrodynamics on the wave group scale. A non-stationary wave driver with directional spreading, with physics similar to XBeach (Roelvink et al., 2009) is linked to an improved and extended version of the existing unstructured flow solver Delft3D–FM (Kernkamp et al., 2011; Martyr-Koller et al., 2017). The model equations are discretised on meshes consisting of triangular and rectangular elements. The model allows for coverage of the model domain with locally optimised resolution to accurately resolve the dominant processes, yet with a smaller total number of grid cells. The model also allows a larger explicit time step, compared to structured models with similar functionality. The model reliably reproduces measured datasets of water levels, sea/swell and low frequency wave heights in laboratory and field conditions, and is as such widely deployable in a variety of simple and complex coastal settings to study nearshore hydrodynamics.

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This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash,collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.

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Wave breaking on the steep fore-reef slopes of shallow fringing reefs can be effective at dissipating incident sea-swell waves prior to reaching reef shorelines. However, wave setup and free infragravity waves generated during the sea-swell breaking process are often the largest contributors to wave-driven water levels (wave runup) at the shoreline. Laboratory flume experiments and a two-dimensional vertical phase-resolving nonhydrostatic wave-flow model, which includes a canopy model to predict drag forces generated by roughness elements, were used to investigate wave-driven water levels for along-shore uniform fringing reefs. In contrast to many previous studies, both the laboratory experiment and the numerical model account for the effects of large bottom roughness. The numerical model reproduced the observations of the wave transformation and runup over both smooth and rough reef profiles. The numerical model was then extended to quantify the influence of reef geometry and compared to simulations of plane beaches lacking a reef. For a fixed offshore forcing condition, the fore-reef slope controlled wave runup on reef-fronted beaches, whereas the beach slope controlled wave runup on plane beaches. As a result, the coastal protection utility of reefs is dependent on these slopes. For our examples, with a fore-reef slope of 1/5 and a 500 m prototype reef flat length, a beach slope of ∼1/30 marked the transition between the reef providing runup reduction for steeper beach slopes and enhancing wave runup for milder slopes. Roughness coverage, spacing, dimensions, and drag coefficient were investigated, with results indicating the greatest runup reductions were due to tall roughness elements on the reef flat.

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Sandy beaches and dune systems have high recreational and ecological value, and they offer protection against flooding during storms. At the same time, these systems are very vulnerable to storm impacts. Process-based numerical models are presently used to assess the morphological changes of dune and beach systems during storms. However, such models come with high computational costs, hindering their use in real-life applications which demand many simulations and/or involve a large spatial-temporal domain. Here we design a novel meta-model to predict dune erosion volume (DEV) at the Dutch coast, based on artificial neural networks (ANNs), trained with cases from process-based modeling. First, we reduce an initial database of 1/41400 observed sandy profiles along the Dutch coastline to 100 representative typological coastal profiles (TCPs). Next, we synthesize a set of plausible extreme storm events, which reproduces the probability distributions and statistical dependencies of offshore wave and water level records. We choose 100 of these events to simulate the dune response of the 100 TCPs using the process-based model XBeach, resulting in 10 000 cases. Using these cases as training data, we design a two-phase meta-model, comprised of a classifying ANN (which predicts the occurrence (or not) of erosion) and a regression ANN (which gives a DEV prediction). Validation against a benchmark dataset created with XBeach and a sparse set of available dune erosion observations shows high prediction skill with a skill score of 0.82. The meta-model can predict post-storm DEV 103-104 times faster (depending on the duration of the storm) than running XBeach. Hence, this model may be integrated in early warning systems or allow coastal engineers and managers to upscale storm forcing to dune response investigations to large coastal areas with relative ease.

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Dune erosion driven by extreme marine storms can damage local infrastructure or ecosystems and affect the long-term flood safety of the hinterland. These storms typically affect long stretches (∼100 km) of sandy coastlines with variable topo-bathymetries. The large spatial scale makes it computationally challenging for process-based morphological models to be used for predicting dune erosion in early warning systems or probabilistic assessments. To alleviate this, we take a first step to enable efficient estimation of dune erosion using the Dutch coast as a case study, due to the availability of a large topo-bathymetric dataset. Using clustering techniques, we reduce 1,430 elevation profiles in this dataset to a set of typological coastal profiles (TCPs), that can be employed to represent dune erosion dynamics along the whole coast. To do so, we use the topo-bathymetric profiles and historic offshore wave and water level conditions, along with simulations of dune erosion for a number of representative storms to characterize each profile. First, we identify the most important drivers of dune erosion variability at the Dutch coast, which are identified as the pre-storm beach geometry, nearshore slope, tidal level and profile orientation. Then using clustering methods, we produce various sets of TCPs, and we test how well they represent dune morphodynamics by cross-validation on the basis of a benchmark set of dune erosion simulations. We find good prediction skill (0.83) with 100 TCPs, representing a 93% input and associated computational costs reduction. These TCPs can be used in a probabilistic model forced with a range of offshore storm conditions, enabling national scale coastal risk assessments. Additionally, the presented techniques could be used in a global context, utilizing elevation data from diverse sandy coastlines to obtain a first order prediction of dune erosion around the world.

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Coral reefs are effective natural coastal flood barriers that protect adjacent communities. Coral degradation compromises the coastal protection value of reefs while also reducing their other ecosystem services, making them a target for restoration. Here we provide a physics-based evaluation of how coral restoration can reduce coastal flooding for various types of reefs. Wave-driven flooding reduction is greatest for broader, shallower restorations on the upper fore reef and between the middle of the reef flat and the shoreline than for deeper locations on the fore reef or at the reef crest. These results indicate that to increase the coastal hazard risk reduction potential of reef restoration, more physically robust species of coral need to be outplanted to shallower, more energetic locations than more fragile, faster-growing species primarily being grown in coral nurseries. The optimization and quantification of coral reef restoration efforts to reduce coastal flooding may open hazard risk reduction funding for conservation purposes.@en

A 2-layer non-hydrostatic model with improved dispersive behaviour is presented. Due to the assumption of a constant non-hydrostatic pressure distribution in the lower layer, the dispersive behaviour is improved without much additional computational time. A comparison with linear wave theory showed that this 2-layer model gives a better result for the dispersion relation and shoaling of waves in intermediate water. This means that the 2-layer model is applicable in shallow and intermediate water depths (up to relative depths kh equals 4), whereas the 1-layer model is only applicable in shallow water depths (kh smaller than 1). Three laboratory experiments, including a fringing reef and a barred beach, were used to validate the presented mode for different hydrodynamic conditions. Based on these results, it can be concluded that the 2-layer model can be applied to accurately simulate the bulk wave height and spectral properties. The low frequency wave height, the setup and in particular the second order statistics contain more scatter, but the model accurately captured the general trend. Furthermore, the model showed good results for complex bathymetries in shallow to intermediate water.

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Coastal management in the Netherlands has the aim to defend coastal zones by preventing flooding and mitigating erosion. To that end, large-scale nourishments are placed in the nearshore, which are supposed to dynamically preserve the coastal zone over a timescale of years. To assess their effectiveness, these nourishments are monitored over large areas and long durations. As repetitive, in-situ measurements become too expensive, remote sensing offers an attractive alternative, mapping depth and near-surface current fields via depth inversion algorithms (DIA). However, the information that can be derived from remotely-sensed data is subject to improvement. In this study a 3D-FFT based DIA named XMFit (X-Band Matlab Fitting) is introduced, which is robust, accurate and fast enough for operational use. Focusing on depth estimates, the algorithm was validated for two case studies in the Netherlands: (1) the “Sand Engine”, a beach mega nourishment at a uniform open coast, and (2) the tidal inlet of the Dutch Wadden Sea island Ameland, characterizing a more complex coast. Considering both sites, the algorithm performance was characterized by a spatially averaged depth bias of −0.9 m at the Sand Engine and a time-varying bias of approximately -2 – 0 m at the Ameland Inlet. When compared to in-situ depth surveys the accuracy was lower, but the time resolution higher. Depth estimates from the Ameland tidal inlet were produced every 50 min by an operational system using a navigational X-Band radar to monitor the placement of a 5 million m³ ebb-tidal delta nourishment – a pilot measure for coastal management. Volumetric changes in the nourishment area over the year 2018, occurring at 7 km distance from the radar, were estimated with an error of 7%. Depth errors statistically correlated with the direction and magnitude of simultaneous near-surface current estimates. Additional experiments on Sand Engine data demonstrated that depth errors may be significantly reduced using an alternative spectral approach and/or by using a Kalman filter.

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Considering the likely increase in coastal flooding in small island developing states (SIDSs) due to climate change, coastal managers at the local and global levels have been developing initiatives aimed at implementing disaster risk reduction (DRR) and adaptation measures. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which in the case of insular states are often subject to input uncertainty. We analysed the impact of a number of uncertain inputs on coastal flood damage estimates: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models, and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with a direct impact model (Delft-FIAT) for a case study of a number of villages on the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDFs) and digital elevation models (DEMs) dominate the overall damage estimation uncertainty. When introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive uncertainty in CFR assessments in SIDSs. The findings of this research can help to prioritize the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.

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The assessment of coastal flood risk on a reef-lined coastline presents several challenges. From the probabilistic side, we need to consider all possible events that could occur in the system, taking into account the different contributions of waves, storm surges, and tides that contribute to the total water level. To estimate reliable flood extents, we need to accurately model the complex wave processes that occur across the reef. To explore the multivariate nature of coastal flooding, we rely on a climate emulator that accounts for climate variability and simulates time series of all the variables involved. Due to the computational constraints to numerically simulate thousands of events, we explore the feasibility of using a recently developed tool, the HyCreWW (Hybrid Coral Reef Wave and Water level) meta-model to estimate wave run-up and flooding extents. Limitation of a 1D assessment are analyzed and results compared with 2D modeling.@en

Small island developing states are among the most vulnerable areas to the impact of natural hazards and climate change. Flooding due to storm surges and extreme waves, coastal erosion, and salinization of freshwater lenses are already a serious threat and could lead to irreversible consequences in the coming decades. Reef flat mining is one of the most common practices to source the required material for the implementation of coastal protection measures, but concerns remain that partial removal of the protective reef could increase wave loading on the islands. However, the available data and knowledge on the effects of these mining pits are currently very limited. This study provides new insights on the effects that pits may have on nearshore hydrodynamics and wave runup. Results are based on a large numerical data set of fringing reefs, derived using the validated XBeach nonhydrostatic+ process-based model. Model results indicate that excavation pits cause a decrease in infragravity wave energy around the fundamental mode of the reef, which is partly caused by reduced wave transmission. Additionally, changes in sea and swell wave energy are attributed to reduced transmission, “a decrease” in wave dissipation, and (triad) wave–wave interaction. Furthermore, in 13% of all modeled cases, an increase in wave runup is observed, mainly due to more sea and swell wave energy reaching the shoreline. This probability is lowest for narrow pits relative to the reef flat width or pits located further from shore.

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Wave-induced flooding is a major coastal hazard on tropical islands fronted by coral reefs. The variability of shape, size, and physical characteristics of the reefs across the globe make it difficult to obtain a parameterization of wave run-up, which is needed for risk assessments. Therefore, we developed the HyCReWW metamodel to predict wave run-up under a wide range of reef morphometric and offshore forcing characteristics. Due to the complexity and high dimensionality of the problem, we assumed an idealized one-dimensional reef profile, characterized by seven primary parameters. XBeach Non-Hydrostatic was chosen to create the synthetic dataset, and Radial Basis Functions implemented in MATLAB® were chosen for interpolation. Results demonstrate the applicability of the metamodel to obtain fast and accurate results of wave run-up for a large range of intrinsic reef morphologic and extrinsic hydrodynamic forcing parameters, offering a useful tool for risk management and early warning systems. @en

The accurate prediction of extreme wave run-up is important for effective coastal engineering design and coastal hazard management. While run-up processes on open sandy coasts have been reasonably well-studied, very few studies have focused on understanding and predicting wave run-up at coral reef-fronted coastlines. This paper applies the short-wave resolving, Nonhydrostatic (XB-NH) and short-wave averaged, Surfbeat (XB-SB) modes of the XBeach numerical model to validate run-up using data from two 1D (alongshore uniform) fringing-reef profiles without roughness elements, with two objectives: i) to provide insight into the physical processes governing run-up in such environments; and ii) to evaluate the performance of both modes in accurately predicting run-up over a wide range of conditions. XBeach was calibrated by optimizing the maximum wave steepness parameter (maxbrsteep) in XB-NH and the dissipation coefficient (alpha) in XB-SB) using the first dataset; and then applied to the second dataset for validation. XB-NH and XB-SB predictions of extreme wave run-up (Rmax and R2%) and its components, infragravity- and sea-swell band swash (SIG and SSS) and shoreline setup (<η>), were compared to observations. XB-NH more accurately simulated wave transformation but under-predicted shoreline setup due to its exclusion of parameterized wave-roller dynamics. XB-SB under-predicted sea-swell band swash but overestimated shoreline setup due to an over-prediction of wave heights on the reef flat. Run-up (swash) spectra were dominated by infragravity motions, allowing the short-wave (but not wave group) averaged model (XB-SB) to perform comparably well to its more complete, short-wave resolving (XB-NH) counterpart. Despite their respective limitations, both modes were able to accurately predict Rmax and R2%.@en

Infragravity (hereafter IG) waves are surface ocean waves with frequencies below those of wind-generated “short waves” (typically below 0.04 Hz). Here we focus on the most common type of IG waves, those induced by the presence of groups in incident short waves. Three related mechanisms explain their generation: (1) the development, shoaling and release of waves bound to the short-wave group envelopes (2) the modulation by these envelopes of the location where short waves break, and (3) the merging of bores (breaking wave front, resembling to a hydraulic jump) inside the surfzone. When reaching shallow water (O(1–10 m)), IG waves can transfer part of their energy back to higher frequencies, a process which is highly dependent on beach slope. On gently sloping beaches, IG waves can dissipate a substantial amount of energy through depth-limited breaking. When the bottom is very rough, such as in coral reef environments, a substantial amount of energy can be dissipated through bottom friction. IG wave energy that is not dissipated is reflected seaward, predominantly for the lowest IG frequencies and on steep bottom slopes. This reflection of the lowest IG frequencies can result in the development of standing (also known as stationary) waves. Reflected IG waves can be refractively trapped so that quasi-periodic along-shore patterns, also referred to as edge waves, can develop. IG waves have a large range of implications in the hydro-sedimentary dynamics of coastal zones. For example, they can modulate current velocities in rip channels and strongly influence cross-shore and longshore mixing. On sandy beaches, IG waves can strongly impact the water table and associated groundwater flows. On gently sloping beaches and especially under storm conditions, IG waves can dominate cross-shore sediment transport, generally promoting offshore transport inside the surfzone. Under storm conditions, IG waves can also induce overwash and eventually promote dune erosion and barrier breaching. In tidal inlets, IG waves can propagate into the back-barrier lagoon during the flood phase and induce large modulations of currents and sediment transport. Their effect appears to be smaller during the ebb phase, due to blocking by countercurrents, particularly in shallow systems. On coral and rocky reefs, IG waves can dominate over short-waves and control the hydro-sedimentary dynamics over the reef flat and in the lagoon. In harbors and semi-enclosed basins, free IG waves can be amplified by resonance and induce large seiches (resonant oscillations). Lastly, free IG waves that are generated in the nearshore can cross oceans and they can also explain the development of the Earth's “hum” (background free oscillations of the solid earth).

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Several studies have reported the development of undular bores over fringing coral reefs (e.g, Gallagher, 1976; Nwogu and Demirbilek, 2010) but the importance of this phenomenon for reef hydrodynamics has never been studied. Yet, the transformation of a long wave (e.g., swell or infragravity wave) into an undular bore leads to significant modifications of the wave field. The formation of undulations is for example associated to a significant increase of the leading bore height. Moreover, if the undulations have enough time to develop (i.e. if the reef flat is wide enough), the initial long wave will ultimately split into a series of solitons (e.g., Grue et al., 2008). All this is likely to affect wave run-up. As reeffronted coastlines are particularly vulnerable to flooding, a good understanding of long wave transformation over the reef flat, including their possible transformation into undular bores, is crucial. In this study, we investigate undular bore development over reef-type profiles based on a series of laboratory experiments. More specifically, we aim to characterize the conditions under which undular bores develop, and analyse how their development affect the hydrodynamics at the toe of the reef-lined beach and the resulting wave run-up.@en

Many low-elevation, coral reef-lined, tropical coasts are vulnerable to the effects of climate change, sea level rise, and wave-induced flooding. The considerable morphological diversity of these coasts and the variability of the hydrodynamic forcing that they are exposed to make predicting wave-induced flooding a challenge. A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, “XBNH”) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on reef-lined coasts. The Bayesian estimator has high predictive skill for the XBNH model outputs that are flooding indicators, and was validated for a number of available field cases. It was found that, in order to accurately predict flooding hazards, water depth over the reef flat, incident wave conditions, and reef flat width are the most essential factors, whereas other factors such as beach slope and bed friction due to the presence or absence of corals are less important. BEWARE is a potentially powerful tool for use in early warning systems or risk assessment studies, and can be used to make projections about how wave-induced flooding on coral reef-lined coasts may change due to climate change.

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This study applied the process-based model XBeach to predict bathymetrically controlled rip current flow occurrence, velocities and duration in the wind-sea-dominated environment of Egmond aan Zee, The Netherlands. The model is validated against data obtained during a 5-day field experiment with GPS-equipped floating drifters. Numerical model results show good agreement with data and simulate flow patterns that resemble the offshore flow through the rip channel and subsequent alongshore drift of the drifters. The average relative error of the drifter position is 0.15 and 0.19 for the cross-shore and the alongshore position, respectively. Results from the numerical experiments suggest that the rip current intensity is tidally modulated. For the period of analysis, the rips are initiated approximately 5 hours before low tide, reaching a maximum speed during low tide, and becoming inactive 3 hours after low tide. Initiation and duration of the rip current is correlated to a ratio of ∼0.55 between offshore wave height and water depth over the bar. Further experiments with the numerical model show that at Egmond, drifters that are transported offshore by the rip current are unlikely to circulate back to the shore (with only a 14% return rate). Instead, they are ejected from the surf zone and advected alongshore, dependent on the direction of the tidal current. Without wave group forcing in the model (i.e. with a stationary wave resolving approach), the model's predictability decreases, which mostly affects the prediction of the spatial flow patterns. The rip current durations can still be predicted very well, whereas the rip current magnitude is underestimated. With wind stress forcing, the model's predictive skill increases for the alongshore flow when the wind speed is relatively high, but this is not the case for low wind conditions.@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.

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A laboratory experiment was conducted to investigate the dynamics of cross-shore sediment transport across a fringing coral reef. The aim was to quantify how a highly bimodal spectrum of high-frequency (sea-swell) and low-frequency (infragravity and seiching) waves that is typically present on coral reef flats, influences the various sediment transport mechanisms. The experiments were conducted in a 55. m wave flume, using a 1:15 scale fringing reef model that had a 1:5 forereef slope, a 14. m long reef flat, and a 1:12 sloping beach. The initial 7. m of reef flat had a fixed bed, whereas the back 7. m of the reef and the beach had a moveable sandy bed. Four seven-hour irregular wave cases were conducted both with and without bottom roughness elements (schematically representing bottom friction by coral roughness), as well as for both low and high still water levels. We observed that the wave energy on the reef flat was partitioned between two primary frequency bands (high and low), and the proportion of energy within each band varied substantially across the reef flat, with the low-frequency waves becoming increasingly important near the shore. The offshore transport of suspended sediment by the Eulerian mean flow was the dominant transport mechanism near the reef crest, but a wide region of onshore transport prevailed on the reef flat where low-frequency waves were very important to the overall transport. Ripples developed over the movable bed and their properties were consistent with the local high-frequency wave orbital excursion lengths despite substantial low-frequency wave motions also present on the reef flat. This study demonstrated that while a proportion of the sediment was transported by bedload and mean flow, the greatest contributions to cross-shore transport were due to the skewness and asymmetry of the high and low-frequency waves.

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