Modelling the Effect of ‘Roller Dynamics’ on Storm Erosion: Sylt, North Sea

Coastal storm erosion can lead to episodic morphological changes and hinterland flooding that requires sustainable management. An accurate estimation of storm erosion can determine the success of hazard mitigation strategies. Two morphological models, Delft3D and XBeach, were applied separately to a stormy period with “Roller” and “No Roller” wave dynamics activated, to estimate erosion of the beach and dune system on the Sylt island. This is the first numerical impact assessment of roller dynamics on coastal erosion using the two models. The choice of model had more impact on the hydrodynamic and morphological predictions than the option to include or omit roller dynamics. Agreement between measured and simulated waves was higher in Delft3D (R2 > 0.90 and RMSE < 0.15 m) than XBeach. Storm erosion in both models had the highest sensitivity to the roller parameter Beta. Both models predicted a similar storm erosion pattern along the coast, albeit different magnitudes. It is found that Delft3D cannot produce comparable storm erosion to XBeach, when the roller dynamics and avalanching are considered. Delft3D is less sensitive to the roller dynamics than XBeach. Including roller dynamics in Delft3D increased storm erosion up to 31% and in XBeach decreased the erosion down to 58% in the nearshore area, while the erosion in the dune area increased up to 13% in Deflt3D and up to 97% in XBeach. Both models are skilled in simulating storm impact. For the simulation of a storm period with intermittent calm periods, it is suggested that applying a time-varying parameter setting for wave dynamics and sediment transport to capture storm erosion and post-storm beach recovery processes could improve results. Such a modelling approach may ultimately increase the accuracy of estimating storm erosion to support coastal management activities (e.g., sand nourishment volume).

Considering the Effect of Land-Based Biomass on Dune Erosion Volumes in Large-Scale Numerical Modeling

This paper presents and validates a novel root model which accounts for the effect of belowground biomass on dune erosion volumes in XBeach, based on a small-scale wave flume experiment that was translated to a larger scale. A 1D-XBeach model was calibrated by using control runs considering a dune without vegetation. Despite calibration, a general model–data mismatch was observed in terms of overestimated erosion volumes around the waterline. Furthermore, the prediction of overwash had to be induced by increasing the maximum nearshore wave height within the XBeach simulation. Subsequently, applying the root model resulted in a good agreement with the belowground biomass cases, and the consideration of spatially varying rooting depths further improved the results. Predictions of the root model while using locally increased friction coefficients were in line with the aboveground and belowground biomass cases. However, the effect of the root model on the erosion predictions varied among the hydrodynamic conditions, so further improvements are required. Therefore, future research should focus on quantifying the effects of land-based biomass and individual plant characteristics, such as root density, on dune erodibility at large scales, along with their influences on the temporal evolution of dune scarping and avalanching.

Improved Calculation of Nonlinear Near-Bed Wave Orbital Velocity in Shallow Water: Validation against Laboratory and Field Data

A new parameterization for calculating the nonlinear near-bed wave orbital velocity in the shallow water was presented. The equations proposed by Isobe and Horikawa (1982) were modified in order to achieve more accurate predictions of the peak orbital velocities. Based on field data from Egmond Beach in the Netherlands, the correction coefficient and maximum skewness were determined as functions of the Ursell number. The obtained equations were validated against measurements from Egmond Beach, and with laboratory data from small-scale wave flume experiments at Delft University of Technology and from large-scale wave flume experiments at Delft Hydraulics. Inter-comparisons with other previously developed parameterizations were also carried out. The model simulations by the present study were in good agreement with the measurements and have been improved compared to the previous ones. For Egmond Beach, the root-mean-square errors for the peak onshore (uc) and offshore (ut) orbital velocities were approximately 21%. The relative biases were small, approximately 0.013 for uc and −0.068 for ut. The coefficient of determination was in the range between 0.64 and 0.68. For laboratory experiments, the root-mean-square errors in a range of 7.2%–24% for uc, and 7.9%–15% for ut.

Contribution of Infragravity Waves to Run-up and Overwash in the Pertuis Breton Embayment (France)

Wave run-up and dune overwash are typically assessed using empirical models developed for a specific range of often-simplistic conditions. Field experiments are essential in extending these formulae; yet obtaining comprehensive field data under extreme conditions is often challenging. Here, we use XBeach Surfbeat (XB-SB)—a shortwave-averaged but wave-group resolving numerical model—to complement a field campaign, with two main objectives: i) to assess the contribution of infragravity (IG) waves to washover development in a partially-sheltered area, with a highly complex bathymetry; and ii) to evaluate the unconventional nested-modeling approach that was applied. The analysis shows that gravity waves rapidly decrease across the embayment while IG waves are enhanced. Despite its exclusion of gravity-band swash, XB-SB is able to accurately reproduce both the large-scale hydrodynamics—wave heights and mean water levels across the 30 × 10 km embayment; and the local morphodynamics—steep post-storm dune profile and washover deposit. These findings show that the contribution of IG waves to dune overwash along the bay is significant and highlight the need for any method or model to consider IG waves when applied to similar environments. As many phase-averaged numerical models that are typically used for large-scale coastal applications exclude IG waves, XB-SB may prove to be a suitable alternative.

Simple estimate of entrainment rate of pollutants from a coastal discharge into the surf zone

Microbial pollutants from coastal discharges can increase illness risks for swimmers and cause beach advisories. There is presently no predictive model for estimating the entrainment of pollution from coastal discharges into the surf zone. We present a novel, quantitative framework for estimating surf zone entrainment of pollution at a wave-dominant open beach. Using physical arguments, we identify a dimensionless parameter equal to the quotient of the surf zone width l(sz) and the cross-flow length scale of the discharge la = M(j) (1/2)/U(sz), where M(j) is the discharge's momentum flux and U(sz) is a representative alongshore velocity in the surf zone. We conducted numerical modeling of a nonbuoyant discharge at an alongshore uniform beach with constant slope using a wave-resolving hydrodynamic model. Using results from 144 numerical experiments we develop an empirical relationship between the surf zone entrainment rate α and l(sz)/(la). The empirical relationship can reasonably explain seven measurements of surf zone entrainment at three diverse coastal discharges. This predictive relationship can be a useful tool in coastal water quality management and can be used to develop predictive beach water quality models.

Remote sensing of the nearshore

The shallow waters of the nearshore ocean are popular, dynamic, and often hostile. Prediction in this domain is usually limited less by our understanding of the physics or by the power of our models than by the availability of input data, such as bathymetry and wave conditions. It is a challenge for traditional in situ instruments to provide these inputs with the appropriate temporal or spatial density or at reasonable logistical or financial costs. Remote sensing provides an attractive alternative. We discuss the range of different sensors that are available and the differing physical manifestations of their interactions with the ocean surface. We then present existing algorithms by which the most important geophysical variables can be estimated from remote sensing measurements. Future directions and opportunities will depend on expected developments in sensors and platforms and on improving processing algorithms, including data assimilation formalisms.