Wave Spectral Parameters Research Articles

Validation of an efficient two-layer non-hydrostatic wave model on a sloping foreshore

In the physical modelling of coastal engineering problems, use is often made of foreshores and transition slopes to obtain the desired wave conditions - both spectral parameters and wave height distribution - at a given location. Numerical wave models can be used to predict whether the target wave conditions are met for a given physical model layout and wave forcing. The XBeach non-hydrostatic two-layer model is a computationally efficient numerical model that has been validated for spectral wave parameters, but lacks validation of the simulated wave height distributions. In this work, wave flume data with high spatial density over a sloping foreshore is used to validate the ability of this numerical model to reproduce both spectral wave parameters and wave height distributions. As part of this effort, optimal settings have been derived for the wave breaking formulation used in the numerical model, resulting in recommended values for the maxbrsteep and reformsteep parameters of 0.40 and 0.20 respectively. From the results of the validation it is concluded that the numerical model is unsuccessful in reproducing the validation tests with 5.0% wave steepness, potentially due to the higher kph numbers on the generating model boundary. Hence, using the numerical model with values of kph ≥ 2 on the model boundary is not recommended. The XBeach non-hydrostatic two-layer model performs much better for the 1.0% and 2.5% wave steepness tests, where the spectral wave parameters are represented well. The corresponding wave height distributions are represented reasonably well up to the point that the relative water depth gets very shallow. For shallower water, the model is expected to underestimate the higher waves in the wave height distribution. Additionally, the numerical model is shown to reproduce the wave height distribution better than a commonly used analytical formulation for wave height distributions on slopes.

Measuring nearshore waves at break point in 4D with Stereo-GoPro photogrammetry: A field comparison with multi-beam LiDAR and pressure sensors

Measuring nearshore waves remains technically challenging despite wave properties are being used in a variety of applications. With the promise of high-resolution and remotely-sensed measurements of water surfaces in four dimensions (spatially and temporally), stereo-photogrammetry applied to video imagery has grown as a viable solution over the last ten years. However, past deployments have essentially used costly cameras and optics, requiring fixed deployment platforms and hindering the applicability of the method in the field.Focusing on close-range measurements of nearshore waves at break point, this paper presents a detailed evaluation of a field-oriented and cost-effective stereo-video system composed of two GoProTM(Hero 7) cameras capable of collecting 12-megapixel imagery at 24 frames per second. The so-called ‘Stereo-GoPro’ system was deployed in the surf zone during energetic conditions at a macrotidal field site using a custom-assembled mobile tower. Deployed concurrently with stereo-video, a 16-beam LiDAR (Light Detection and Ranging) and two pressure sensors provided independent data to assess stereo-GoPro performance. All three methods were compared with respect to the evolution of the free-surface elevation over 25 min of recording at high tide and the wave parameters derived from spectral analysis. We show that stereo-GoPro allows producing digital elevation models (DEMs) of the water surface over large areas (250 m2) at high spatial resolution (0.2 m grid size), which was unsurpassed by the LiDAR. From instrument inter-comparisons at the location of the pressure transducers, free-surface elevation root-mean square errors of 0.11 m and 0.18 m were obtained respectively for LiDAR and stereo-GoPro. This translated into a maximum relative error of 3.9% and 12.5% on spectral wave parameters for LiDAR and stereo-GoPro, respectively. Optical distortion in imagery, which could not be completely corrected with calibration, was the main source of error. Whilst stereo-video processing workflow remains complex, cost-effective stereo-photogrammetry already opens new opportunities for deriving wave parameters in coastal regions, as well as for various other practical applications. Further tests should try to address specifically challenges associated to variable ambient conditions and acquisition configurations, affecting measurement performance, to guarantee a larger uptake of the technique.

Data-driven fast reliability assessment of offshore structures based on real-time sensor data

With the advancement of monitoring technologies for offshore structures, sensor data are becoming increasingly available in real-time. The objective of this paper is to develop fast methods for reliability assessment of offshore structures for the extreme and fatigue failure modes, based on the latest real-time sensor data, assumed to be four months. The continuously updated assessment informs operators on the failure probability over the next few years. Reliability analysis using real-time data is challenging owing to the need to extrapolate the observed data to more severe sea states and across many orders of magnitudes of probabilities, and there is a lack of related studies. Here, the environment comprises the short-term and long-term wave characteristics. Three data-driven reliability approaches are developed for three types of wave sensor data. The first approach applies statistical models to the response when wave data are unavailable. The second relies on Gaussian Process Regression (GPR) when only the wave spectral parameters are known. The third applies the Gaussian-experienced NARX network to predict the response time series when the wave time series are recorded. The proposed approaches are applied to a jack-up platform, and implementation of benchmark reliability analysis is enabled by establishing an emulator trained from dynamic simulations for fast generation of synthetic sensor data. The GPR approach is found to show good extrapolation capabilities and able to provide relatively accurate and robust reliability predictions.

Validation Of An Efficient Non-Hydrostatic Wave Model As A Design Tool For Foreshores In Physical Models

In the design of physical model experiments in coastal engineering, it is common that the construction of a foreshore is necessary to obtain the desired wave conditions at a given location, usually close to a structure being tested. In addition to the commonly used spectral wave parameters to describe the target wave conditions, the wave height distribution and associated parameters (such as Hmax and H2%), wave periods and infra-gravity waves can be important to reproduce properly as well. Wave height distributions are typically important for tests where e.g. wave run-up or wave forces are of interest. Since the construction of foreshores is labour intensive (and thus expensive), it is useful to be able to check a priori whether the target wave conditions are met with a given foreshore design and whether the chosen transition slope does not significantly influence the wave conditions. One way to do this is by using numerical wave models. For a numerical model to be a useful design tool for physical model layouts, the predicted wave transformation (over the foreshore) needs to be sufficiently accurate. One option is to use detailed CFD wave models for this purpose, such as OpenFOAM, which has been shown to accurately reproduce wave transformation (Jacobsen et al., 2015; Jacobsen et al., 2018). CFD models, however, typically feature high computational demand and consequentially computational times in the order of days. This is a significant disadvantage in the context of designing a physical model experiment, for which the layout and configuration is often an iterative process, which would be hampered by overly long computational times. On the other hand, spectral wave models, like SWAN (Booij et al., 1996), are much faster but do not model all the individual waves rendering it unable to model exceedance distributions. As a middle-ground, it seems that the XBeach model (Roelvink et al., 2009) used in its 2-layer non-hydrostatic mode (De Ridder et al., 2021) might present a workable compromise between computational time and accurate representation of the wave transformation. The model has been validated by De Ridder et al. (2021) on bichromatic waves, complex barred beach geometry and a fringing reef for bulk wave parameters and spectral properties. Expanding on earlier validation work, in this work the ability of the XBeach 2-layer non-hydrostatic model (XBeach-nh) to reproduce wave height exceedance distributions over a sloping foreshore is validated using wave flume data, described in Sections 2 and 3. The preliminary results of the validation effort are shown in Section 4.

Prediction of Wave Spectral Parameters Using Multiple-Output Regression Models to Support the Execution of Marine Operations

Abstract Execution of a marine operation (MO) requires coordinated actions of several vessels conducting simultaneous and sequential offshore activities. These activities have their operational limits given in terms of environmental parameters. Wave parameters are important because of their high energetic level. During the execution of a MO, forecast wave spectral parameters, i.e., significant wave height (Hs), peak period (Tp), and peak direction, are used to make an on-board decision. For critical operations, the use of forecasts can be complemented with buoy measurements. This paper proposes to use synthetic statistics of vessel dynamic responses to predict “real-time” wave spectral parameters using multi-output machine learning (ML) regression algorithms. For a case study of a vessel with no forward speed, it is observed that the random forest model predicts accurate Hs and Tp parameters. The prediction of wave direction is not very accurate but it can be corrected with on-board observations. The random forest model has good performance; it is efficient, useful for practical purposes, and comparable with other deep learning models reported in the scientific literature. Findings from this research can be valuable for real-time assessment of wave spectral parameters, which are necessary to support decision-making during the execution of MOs.

A deep learning super-resolution model to speed up computations of coastal sea states

In this paper, the potential of a super-resolution technique is presented in the context of coastal wave forecasting. The method uses a neural network to predict a high-resolution spatial estimation of spectral wave parameters from a lower resolution numerical computation. In this particular example, one year of training data is sufficient to achieve satisfying accuracy for practical applications. The error of this method in reproducing the results of a high-resolution spectral model is an order of magnitude lower than the usual accuracy of spectral models. Simultaneously, it reduces the computation time by a factor of up to 50. Moreover, utilizing complementary training data of extreme events allows for a further improvement in accuracy. The study also shows that super-resolution is more accurate, albeit slower, than surrogate models, thus providing a trade-off solution between accuracy and speed. Overall, incorporation of the present approach into wave forecasting systems has the potential to rapidly generate “zoomed-in” areas of interest or to speed up ensemble forecasts without supplementary calculations at higher resolution.

Hybrid modelling to improve operational wave forecasts by combining process-based and machine learning models

Operational wave forecasting plays an important role in ensuring safe navigation and in the prediction of tidal windows for harbour approach channels. The underlying nearshore process-based wave models need to be accurate for a wide range of different conditions, from more common mild wave conditions to the occasional high energy (storm) conditions. In this work, an innovative hybrid modelling approach is proposed to improve the accuracy of operational wave forecasts. An operational wave model is combined with a machine learning model which is trained using wave measurements within the wave model domain. This hybrid modelling approach is applied to the Dutch North Sea, covering four major harbour approach channels.The final hybrid operational wave model results in a significant average error decrease compared to just the process-based model, amounting to 21.7% for the wave energy density and 25.3% for the wave direction. The error reduction for the spectral wave parameters is even larger, with a 33.3% smaller error in spectral wave height and a 38.8% smaller error in spectral wave period. As this approach is generically applicable to spectral wave models, it contains the potential for significant improvements in operational modelling.

Effects of inhomogeneous wave modeling on extreme responses of a very long floating bridge

Floating bridges are usually deployed in fjords where the wave fields are inhomogeneous. The wave inhomogeneity has been found to induce significant effects on dynamic responses, however, it was rarely considered during the extreme response analyses of floating bridges. The present study deals with the effects of inhomogeneous wave modeling on extreme responses of a very long end-anchored floating bridge. The inhomogeneous wave field modeling accounts for the spatial variation of wave spectral parameters as well as the coherence of wave elevations between different positions. Structural responses under various wave conditions are simulated through fully-coupled hydro-elastic simulations. The long-term extreme responses are investigated by a simplified environmental contour method, where the long-term extremes are approximated by extremes at a high quantile in carefully selected short-term sea states. The characteristics of simulated waves and responses are first analyzed to serve as a basis for extreme prediction. Uncertainties associated with extreme analyses are also studied. It is found that the coherence of wave elevations has significant influences on the standard deviation and the spatial correlation of the responses. The extreme values of the axial force vary between different modeling of inhomogeneous wave loads and become significantly larger considering partially correlated wave fields.

Wave Hydrodynamics across Steep Platform Reefs: A Laboratory Study

This paper presents a laboratory study on wave transmission across steep platform reefs, aiming at furthering knowledge of wave hydrodynamics and establishing empirical formulations of spectral wave parameters across the reef flat. The ultimate aim of this study is to determine the design wave load to design fixed offshore structures on coral reefs flat. The process of wave transmission across the underground coral strip with a large front slope has been studied on a physical model in the wave trough with nearly 300 experimental cases combined from 05 underground band models and many random wave scenarios and scenarios at different submerged depths. Experimental results show that the abrupt transition in depth from deep water ahead to relatively shallow water in the reef is responsible for the difference in the wave at the top of the strip compared to the wave on the normal beach, especially regarding the statistical distribution of the wave height. Breaking waves at the abrupt transition have deviated the wave height distribution curve from the deep-water (Rayleigh) theoretical distributions and even the existing shallow-water distributions, including the effect of breaking waves. Two sets of empirical formulations of the spectral wave parameters (Hm0 and Tm-1, 0) are eventually derived for the surf zone and the region behind the surf zone, respectively. These local wave parameters can be used as inputs to a wave height distribution model for determining other design characteristic wave heights on steep platform reefs. Doi: 10.28991/CEJ-2022-08-08-015 Full Text: PDF

Comparison of the predicted and the observed wave spectral parameters during the storms at Filyos coasts, The Southwestern Black Sea

In-situ wave measurement data are mainly used to validate the bulk wave parameters predicted by numerical models. Although the frequently used third-generation wave models are spectral models, determination of various spectral parameters and validation with the observed data are not common. This study covers the spectral analysis of selected storm records of a nearshore wave measurement campaign carried out at Filyos coasts with the complex bottom topography in Turkey, Southwestern Black Sea. The bulk wave and the spectral parameters are also calculated by a third-generation nearshore wave model, SWAN (Simulating Waves Nearshore), forced by the ERA5 offshore wave data, which is the newest re-analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) for the selected storms. Before using ERA5 offshore wave data, they are calibrated by the wave data of the satellite radar altimeter. In-situ measured bathymetry data are used in the SWAN model. Observed and predicted bulk wave and spectral parameters are compared, and the statistical error measures are calculated not only for the significant wave height, the peak period, and the peak wave direction but also for the three different spectral periods, three different frequency width parameters, a directional width and, a spectral peakedness parameter for the first time. Low values of statistical error measures show that the current wave predictions have a good agreement with the observed ones in terms of the significant wave height, Hs, and the peak period, Tp. However, the SWAN model predicts a slightly narrower frequency and directional spectrum with higher peaks, although the error measures are low. Moreover, SWAN can not predict the wide range of spectral shape occurrences that the observed spectra have. The development of the various spectral parameters during the storms is also investigated for the first time. It is found that the frequency and directional spreading of the observed spectra become wider and unsharpened in the late stages of the storm compared to the early stages. However, the same tendency is not observed clearly in the predicted directional spreading.

A generic method for assessment of inhomogeneous wave load effects of very long floating bridges

Floating bridges are promising infrastructures used to cross wide and deep fjords. During the design of floating bridges, the wave field is usually assumed long-crested and homogeneous. However, the real wave field in fjords is short-crested and inhomogeneous due to the complicated topography. To evaluate the uncertainties implied by the homogeneous assumption, a generic method is proposed in this study for the assessment of inhomogeneous wave load effects of very long floating bridges. The inhomogeneous wave field is represented by the long-term variation and correlation of wave spectral parameters at the location of each pontoon and by coherence functions of wave elevations between pontoons. The correlated and inhomogeneous wave field is simulated by applying the Cholesky decomposition techniques based on auto- and cross-spectra of waves at pontoons. The wave spectral parameters can be determined with consideration of their long-term correlation while the coherence functions of wave elevations can be obtained by using phase-resolved methods. Based on the simulated wave elevations at each pontoon, the time series of first-order and second-order wave excitation forces are created by using the transfer functions and applied externally to each pontoon in the numerical model of the floating bridge. The proposed method is validated and applied to investigate the dynamic behavior of a floating bridge for the Bjørnafjord crossing as a case study. The inhomogeneous wave load effects are assessed by carrying out fully coupled time-domain simulations. It is found that the assumption of homogeneous wave conditions is conservative for the strong axis and weak axis bending moments, but significantly nonconservative for the axial force. The proposed method can also be applied for other very large floating structures subjected to the inhomogeneous wave field.

Wave Analysis for Offshore Aquaculture Projects: A Case Study for the Eastern Mediterranean Sea

The investigation of wave climate is of primary concern for the successful implementation of offshore aquaculture systems as waves can cause significant loads on them. Up until now, site selection and design (or selection) of offshore cage system structures on extended sea areas do not seem to follow any specific guidelines. This paper presents a novel methodology for the identification of favorable sites for offshore aquaculture development in an extended sea area based on two important technical factors: (i) the detailed characterization of the wave climate, and (ii) the water depth. Long-term statistics of the significant wave height, peak wave period, and wave steepness are estimated on an annual and monthly temporal scale, along with variability measures. Extreme value analysis is applied to estimate the design values and associated return periods of the significant wave height; structures should be designed based on this data, to avoid partial or total failure. The Eastern Mediterranean Sea is selected as a case study, and long-term time series of wave spectral parameters from the ERA5 dataset are utilized. Based on the obtained results, the most favorable areas for offshore aquaculture installations have been identified.

An integrated framework of coastal flood modelling under the failures of sea dikes: a case study in Shanghai

Climate change leads to sea level rise worldwide, as well as increases in the intensity and frequency of tropical cyclones (TCs). Storm surge induced by TC’s, together with spring tides, threatens to cause failure of flood defenses, resulting in massive flooding in low-lying coastal areas. However, limited research has been done on the combined effects of the increasing intensity of TCs and sea level rise on the characteristics of coastal flooding due to the failure of sea dikes. This paper investigates the spatial variation of coastal flooding due to the failure of sea dikes subject to past and future TC climatology and sea level rise, via a case study of a low-lying deltaic city- Shanghai, China. Using a hydrodynamic model and a spectral wave model, storm tide and wave parameters were calculated as input for an empirical model of overtopping discharge rate. The results show that the change of storm climatology together with relative sea level rise (RSLR) largely exacerbates the coastal hazard for Shanghai in the future, in which RSLR is likely to have a larger effect than the TC climatology change on future coastal flooding in Shanghai. In addition, the coastal flood hazard will increase to a large extent in terms of the flood water volume for each corresponding given return period. The approach developed in this paper can also be utilized to investigate future flood risk for other low-lying coastal regions.

A non-breaking-wave-generated turbulence mixing scheme for a global ocean general circulation model

A novel vertical mixing scheme to describe the influence of the non-breaking surface waves in ocean general circulation models is proposed based on the second-order turbulence closure model and a mathematical relationship fitted between the in situ observations of the turbulence kinetic energy dissipation rate and the calculated velocity shear module of non-breaking surface waves. The non-breaking-wave-generated turbulence mixing coefficients can be calculated empirically in terms of the wave spectral parameters including ΦSW, K, and ω, where ΦSW is the wave number spectrum of the significant wave height, K is the wave number, ω is the surface wave frequency. The effect of the new mixing scheme on global ocean circulation simulation was tested using the MArine Science and NUmerical Modeling ocean model. The results indicate significant improvement in the upper-ocean temperature structure and the mixed layer depth, i.e., the non-breaking-wave-generated turbulence mixing plays an important role in the upper ocean at high latitudes in summer for both hemispheres compared with traditional Mellor-Yamada 2.5 scheme.

The role of frequency spread on swash dynamics

The swash zone is the most dynamic part of the upper beach. Here breaking waves interact with sediments, leading to beach morphodynamics, and eventually to coastal erosion and flooding. An understanding of swash characteristics such as the vertical excursion and mean swash period is of vital importance to identify and predict the possible impact of storms in coastal areas. The prediction of these swash parameters is commonly based on bulk offshore spectral wave parameters and the beach slope, the latter being expensive to monitor. In this study, a dataset from an intermediate beach on the south-west coast of Sylt, Germany was derived to analyze swash characteristics. Field observations show high variability in swash excursion even for similar incident wave conditions if expressed by bulk parameters. Here, the role of frequency spread was further investigated. An inverse relationship between swash frequency spread and swash characteristics (excursion and mean period) was identified. A parameterization for the swash frequency spread based on incident wave parameters is proposed, and a new approach to obtain total swash excursion and mean swash period is developed. The parameterization is validated using two independent swash datasets (Duck 1982 and Duck 1994) and compared to the predictive ability of other parameterizations. It is highlighted that common parameterizations based on peak period do not perform well in characterizing incident conditions when bi-modal spectra are present. The choice of the right descriptor for wave periods may have a more pronounced influence on the predictive skill than the inclusion of the beach slope.

Development of waves under explosive cyclones in the Northwestern Pacific

The development of ocean waves under explosive cyclones (ECs) is investigated in the Northwestern Pacific Ocean using a hindcast wave simulation around Japan during the period 1994 through 2014. A composite analysis of the ocean wave fields under ECs is used to investigate how the spatial patterns of the spectral wave parameters develop over time. Using dual criteria of a drop in sea level pressure below 980 hPa at the center of a cyclone and a decrease of at least 12 hPa over a 12-h period, ECs are identified in atmospheric reanalysis data. Two areas under an EC were identified with narrow directional spectra: the cold side of a warm front and the right-hand side of an EC (relative to the propagating direction). Because ECs are associated with atmospheric fronts, ocean waves develop very differently under ECs than they do under tropical cyclones. Moreover, ECs evolve very rapidly such that the development of the ocean wave field lags behind the peak wind speed by hours. In a case study of an EC that occurred in January 2013, the wave spectrum indicates that a warm front played a critical role in generating distinct ocean wave systems in the warm and cold zones along the warm front. Both the warm and cold zones have narrow directional and frequency spectra. In contrast, the ocean wave field in the third quadrant (rear left area relative to the propagation direction) of the EC is composed of swell and wind sea systems propagating in different directions.

Back-reaction of gravitational waves revisited

We study the back-reaction of gravitational waves in early universe cosmology, focusing both on super-Hubble and sub-Hubble modes. Sub-Hubble modes lead to an effective energy density which scales as radiation. Hence, the relative contribution of such gravitational waves to the total energy density is constrained by big bang nucleosynthesis. This leads to an upper bound on the tensor spectral slope nT which also depends on the tensor to scalar ratio r. Super-Hubble modes, on the other hand, lead to a negative contribution to the effective energy density, and to an equation of state of curvature. Demanding that the early universe is not dominated by the back-reaction leads to constraints on the gravitational wave spectral parameters which are derived.

Estimation of significant wave period from wave spectrum

Although the significant wave period is one of the key parameters in the design of coastal structures, it is not calculated by the spectral wave model because it is obtained by the zero-crossing analysis. The present paper examines several formulas that relate the significant wave period to wave spectral parameters such as peak period, mean period, and peakedness parameter. The formulas are derived based on the wave measurements in two locations in the Japan/East Sea (JES). The derived formulas are then compared with the measured significant wave periods in other locations in JES. It is shown that the formula using the mean wave period, Tm−1,0, is the most accurate. This formula is further used in a spectral wave model, the significant wave periods from which are compared with the measurement. Additionally, the relationship between the significant wave height and period is obtained based on the wave hindcasting, from which the most probable significant wave period can be determined for a specific significant wave height. A comparison with the measurement shows that the relationship is relatively inaccurate in the locations where southerly swell waves are significant, which are not accurately taken into account in the numerical model.

In-situ Measurements of Wave Impact Pressure on a Composite Breakwater: Preliminary Results

Larroque, B.; Arnould P.; Luthon F.; Poncet, P.A.; Rahali, A., and Abadie, S., 2018. In-situ measurements of wave impact pressure on a composite breakwater: preliminary results. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1086–1090. Coconut Creek (Florida), ISSN 0749-0208.A detached horizontally composite breakwater protecting the Saint Jean de Luz bay (French Basque Coast, Bay of Biscay, France) has been equipped with two pressure sensors displayed vertically onto the vertical wall. The two sensors recorded wave impact pressure in ten minute burst each hour at 10 kHz. In parallel, incoming waves were also recorded about 1 km off the structure with a directional wave buoy giving access to spectral wave parameters as well as raw data. Finally water level, wind magnitude and direction were also acquired. The whole dataset covers winter 2015–2016 from January to March.The results show first the statistical distribution of the measured parameters confirming preceding similar studies in which significantly lower impact pressure values were obtained compared to physical experiments or numerical simulations. A linear multivariate model has then been adjusted showing the overwhelming influence of wave heights to explain maximum pressure variability, followed by water level. Nevertheless this result has still to be confirmed for data reduced to impulsive impacts. Finally, interesting events supposedly corresponding to, or approaching flip-through impact type, have been identified and need further investigations.

Mapping the coastal risk for the next century, including sea level rise and changes in the coastline: application to Charlestown RI, USA

A source–pathway-receptor method is used to assess the risk of the coastal community of Charlestown, RI, USA, to the 100-year storm, including effects of sea level rise (SLR) and shoreline/dune erosion. The 100-year storm is simulated using a chain of stochastic and physics-based models combined with a scenario-based approach. Storm surge and wave spectral parameters, obtained from the U.S. Army Corps of Engineers’ North Atlantic Coast Comprehensive Study (NACCS), are used as boundary conditions for high-resolution wave simulations, performed in the coastal and inundation zones using the steady-state spectral wave model STWAVE. Selected scenarios are defined to assess the magnitude of the variability in predicted damage resulting from the uncertainty in SLR, erosion rate, and time at which the 100-year storm would occur. Erosion rates are based on empirical analyses of historic rates of shoreline change, SLR measurements, and coastal erosion theory. The risk is measured in terms of damage to individual houses, based on damage curves developed in the U.S. Army Corps of Engineers, NACCS study. In addition, remediation scenarios are explored, demonstrating that a combination of dune replenishment and an increase in the residential resilience by elevating structures can significantly diminish the risk to the coastal community.