Role of Storm Erosion Potential and Beach Morphology in Controlling Dune Erosion

Coastal erosion is controlled by two sets of factors, one related to storm intensity and the other related to a location’s vulnerability. This study investigated the role of each set in controlling dune erosion based on data compiled for eighteen historical events in New Jersey. Here, storm intensity was characterized by the Storm Erosion Index (SEI) and Peak Erosion Intensity (PEI), factors used to describe a storm’s cumulative erosion potential and maximum erosive power, respectively. In this study, a direct relationship between these parameters, beach morphology characteristics, and expected dune response was established through a classification tree ensemble. Of the seven input parameters, PEI was the most important, indicating that peak storm conditions with time scales on the order of hours were the most critical in predicting dune impacts. Results suggested that PEI, alone, was successful in distinguishing between storms most likely to result in no impacts (PEI < 69) and those likely to result in some (PEI > 102), regardless of beach condition. For intensities in between, where no consistent behavior was observed, beach conditions must be considered. Because of the propensity for beach conditions to change over short spatial scales, it is important to predict impacts on a local scale. This study established a model with the computational effectiveness to provide such predictions.

A Clustering Approach for Predicting Dune Morphodynamic Response to Storms Using Typological Coastal Profiles: A Case Study at the Dutch Coast

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.

The relative influence of dune aspect ratio and beach width on dune erosion as a function of storm duration and surge level

Dune height is an important predictor of impact during a storm event given that taller dunes have a lower likelihood of being overtopped than shorter dunes. However, the temporal dominance of the wave collision regime, wherein volume loss (erosion) from the dune occurs through dune retreat without overtopping, suggests that dune width must also be considered when evaluating the vulnerability of dunes to erosion. We use XBeach, a numerical model that simulates hydrodynamic processes, sediment transport, and morphologic change, to analyze storm-induced dune erosion as a function of dune aspect ratio (i.e., dune height versus dune width) for storms of varying intensity and duration. We find that low aspect ratio (low and wide) dunes lose less volume than high aspect ratio (tall and narrow) dunes during longer and more intense storms when the beach width is controlled for. In managed dune scenarios, where sand fences are used to construct a “fenced” dune seaward of the existing “natural” dune, we find that fenced dunes effectively prevent the natural dune behind them from experiencing any volume loss until the fenced dune is sufficiently eroded, reducing the magnitude of erosion of the natural dune by up to 50 %. We then control for dune morphology to assess volume loss as a function of beach width and confirm that beach width exerts a significant influence on dune erosion; a wide beach offers the greatest protection from erosion in all circumstances while the width of the dune determines how long the dune will last under persistent scarping. These findings suggest that efforts to maintain a wide beach may be effective at protecting coastal communities from dune loss. However, a trade-off may exist in maintaining wide beaches and dunes in that the protection offered in the short-term must be considered in concert with potentially long-term detrimental effects of limiting overwash, a process which is critical to maintaining island elevation as sea level rises.

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.

Process-Based Model Prediction of Coastal Dune Erosion through Parametric Calibration

Coastal dunes are important morphological features for both ecosystems and coastal hazard mitigation. Because understanding and predicting dune erosion phenomena is very important, various numerical models have been developed to improve the accuracy. In the present study, a process-based model (XBeachX) was tested and calibrated to improve the accuracy of the simulation of dune erosion from a storm event by adjusting the coefficients in the model and comparing it with the large-scale experimental data. The breaker slope coefficient was calibrated to predict cross-shore wave transformation more accurately. To improve the prediction of the dune erosion profile, the coefficients related to skewness and asymmetry were adjusted. Moreover, the bermslope coefficient was calibrated to improve the simulation performance of the bermslope near the dune face. Model performance was assessed based on the model-data comparisons. The calibrated XBeachX successfully predicted wave transformation and dune erosion phenomena. In addition, the results obtained from other two similar experiments on dune erosion with the same calibrated set matched well with the observed wave and profile data. However, the prediction of underwater sand bar evolution remains a challenge.

Use of Nanosilica for Increasing Dune Erosion Resistance during a Sea Storm

Dune recovery interventions that integrate natural, sustainable, and soft solutions have become increasingly popular in coastal communities. In the present study, the reliability of an innovative non-toxic colloidal silica-based solution for coastal sand dunes has been verified for the first time by means of laboratory experiments. An extensive experimental campaign aimed at studying the effectiveness of the use of nanosilica has been conducted in the 2D wave flume of the EUMER laboratory at the University of Salento (Italy). The study was first based on a horizontal seabed and then a cross-shore beach-dune profile was drawn similar to those generally observed in nature. Detailed measurements of wave characteristics and observed bed and cross-shore beach-dune profiles were analyzed for a wide range of wave conditions. In both cases, two sets of experiments were carried out. After the first set of experiments performed resembling the native conditions of the models composed with natural sand, the effects of the injection of the mineral colloidal silica-based grout were investigated. The observations show that mineral colloidal silica increases the mechanical strength of non-cohesive sediments reducing the volume of dune erosion, thus improving the resistance and longevity of the beach-dune system.