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

2021 ◽  
Vol 9 (5) ◽  
pp. 1223-1237
Author(s):  
Michael Itzkin ◽  
Laura J. Moore ◽  
Peter Ruggiero ◽  
Sally D. Hacker ◽  
Reuben G. Biel
Keyword(s):  
Aspect Ratio ◽  
Storm Event ◽  
Morphologic Change ◽  
Volume Loss ◽  
Dune Erosion ◽  
Beach Width ◽  
Storm Duration ◽  
Hydrodynamic Processes ◽  
Natural Dune ◽  
Dune Height

Abstract. 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.

scholarly journals The Influence of Dune Aspect Ratio, Beach Width and Storm Characteristics on Dune Erosion for Managed and Unmanaged Beaches

2020 ◽  
Author(s):  
Michael Itzkin ◽  
Laura J. Moore ◽  
Peter Ruggiero ◽  
Sally D. Hacker ◽  
Reuben G. Biel
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Storm Event ◽  
Volume Loss ◽  
Dune Erosion ◽  
Low Aspect Ratio ◽  
Beach Width ◽  
Natural Dune ◽  
Storm Characteristics ◽  
Dune Height

Abstract. Dune height is an important predictor of dune impact during a storm event given that taller dunes have a lower likelihood of being overtopped. However, the temporal dominance of the wave collision regime, wherein significant volume loss (erosion) from the dune will occur through dune retreat without the dune being overtopped, 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 during a storm, to analyze 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 storms, especially if they are fronted by a narrow beach. During more intense storms, low aspect ratio dunes experience greater erosion as they are more easily overtopped than high aspect ratio dunes. In managed scenarios where sand fences are used to construct a fenced dune seaward of the existing natural dune, we find that the fenced dune effectively prevents the natural dune behind it 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 also find that beach width exerts a significant influence on dune erosion; a wide beach offers the greatest protection from erosion in all circumstances regardless of dune morphology or storm characteristics. These findings suggest that efforts to maintain a wide beach may be effective at protecting coastal communities from dune loss. However, in maintaining wide beaches and dunes, the protection offered in the short-term must be considered against long-term detrimental effects of potentially limiting overwash fluxes, which are critical to maintaining island elevation as sea level rises.

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

2021 ◽  
Vol 9 (6) ◽  
pp. 635
Author(s):  
Hyeok Jin ◽  
Kideok Do ◽  
Sungwon Shin ◽  
Daniel Cox
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Model Performance ◽  
Coastal Dunes ◽  
Wave Transformation ◽  
Storm Event ◽  
Face Model ◽  
Dune Erosion ◽  
Simulation Performance ◽  
Sand Bar

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.

scholarly journals Impacts of storm chronology on the morphological changes of the Formby beach and dune system, UK

2015 ◽  
Vol 15 (7) ◽  
pp. 1533-1543 ◽  
Author(s):  
P. Dissanayake ◽  
J. Brown ◽  
H. Karunarathna
Keyword(s):  
Extreme Event ◽  
Morphological Changes ◽  
Water Levels ◽  
Storm Event ◽  
Dune System ◽  
Morphological Response ◽  
Cumulative Impact ◽  
Dune Erosion ◽  
Sequence Of Events ◽  
Storm Impact

Abstract. Impacts of storm chronology within a storm cluster on beach/dune erosion are investigated by applying the state-of-the-art numerical model XBeach to the Sefton coast, northwest England. Six temporal storm clusters of different storm chronologies were formulated using three storms observed during the 2013/2014 winter. The storm power values of these three events nearly halve from the first to second event and from the second to third event. Cross-shore profile evolution was simulated in response to the tide, surge and wave forcing during these storms. The model was first calibrated against the available post-storm survey profiles. Cumulative impacts of beach/dune erosion during each storm cluster were simulated by using the post-storm profile of an event as the pre-storm profile for each subsequent event. For the largest event the water levels caused noticeable retreat of the dune toe due to the high water elevation. For the other events the greatest evolution occurs over the bar formations (erosion) and within the corresponding troughs (deposition) of the upper-beach profile. The sequence of events impacting the size of this ridge–runnel feature is important as it consequently changes the resilience of the system to the most extreme event that causes dune retreat. The highest erosion during each single storm event was always observed when that storm initialised the storm cluster. The most severe storm always resulted in the most erosion during each cluster, no matter when it occurred within the chronology, although the erosion volume due to this storm was reduced when it was not the primary event. The greatest cumulative cluster erosion occurred with increasing storm severity; however, the variability in cumulative cluster impact over a beach/dune cross section due to storm chronology is minimal. Initial storm impact can act to enhance or reduce the system resilience to subsequent impact, but overall the cumulative impact is controlled by the magnitude and number of the storms. This model application provides inter-survey information about morphological response to repeated storm impact. This will inform local managers of the potential beach response and dune vulnerability to variable storm configurations.

scholarly journals Ensemble models from machine learning: an example of wave runup and coastal dune erosion

2019 ◽  
Vol 19 (10) ◽  
pp. 2295-2309 ◽  
Author(s):  
Tomas Beuzen ◽  
Evan B. Goldstein ◽  
Kristen D. Splinter
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Coastal Dune ◽  
Data Driven ◽  
Storm Event ◽  
Wave Runup ◽  
Dune Erosion ◽  
Unseen Data ◽  
Uncertainty Estimates ◽  
Narrabeen Beach

Abstract. After decades of study and significant data collection of time-varying swash on sandy beaches, there is no single deterministic prediction scheme for wave runup that eliminates prediction error – even bespoke, locally tuned predictors present scatter when compared to observations. Scatter in runup prediction is meaningful and can be used to create probabilistic predictions of runup for a given wave climate and beach slope. This contribution demonstrates this using a data-driven Gaussian process predictor; a probabilistic machine-learning technique. The runup predictor is developed using 1 year of hourly wave runup data (8328 observations) collected by a fixed lidar at Narrabeen Beach, Sydney, Australia. The Gaussian process predictor accurately predicts hourly wave runup elevation when tested on unseen data with a root-mean-squared error of 0.18 m and bias of 0.02 m. The uncertainty estimates output from the probabilistic GP predictor are then used practically in a deterministic numerical model of coastal dune erosion, which relies on a parameterization of wave runup, to generate ensemble predictions. When applied to a dataset of dune erosion caused by a storm event that impacted Narrabeen Beach in 2011, the ensemble approach reproduced ∼85 % of the observed variability in dune erosion along the 3.5 km beach and provided clear uncertainty estimates around these predictions. This work demonstrates how data-driven methods can be used with traditional deterministic models to develop ensemble predictions that provide more information and greater forecasting skill when compared to a single model using a deterministic parameterization – an idea that could be applied more generally to other numerical models of geomorphic systems.

scholarly journals Impacts of storm chronology on the morphological changes of the Formby beach and dune system, UK

2015 ◽  
Vol 3 (4) ◽  
pp. 2565-2597 ◽  
Author(s):  
P. Dissanayake ◽  
J. Brown ◽  
H. Karunarathna
Keyword(s):  
Extreme Event ◽  
Morphological Changes ◽  
Water Levels ◽  
Storm Event ◽  
Dune System ◽  
Morphological Response ◽  
Cumulative Impact ◽  
Dune Erosion ◽  
Sequence Of Events ◽  
Storm Impact

Abstract. Impacts of storm chronology within a storm cluster on beach/dune erosion are investigated by applying the state-of-the-art numerical model XBeach to the Sefton coast, northwest England. Six temporal storm clusters of different storm chronologies were formulated using three storms observed during the 2013/14 winter. The storm power values of these three events nearly halve from the first to second event and from the second to third event. Cross-shore profile evolution was simulated in response to the tide, surge and wave forcing during these storms. The model was first calibrated against the available post-storm survey profiles. Cumulative impacts of beach/dune erosion during each storm cluster were simulated by using the post-storm profile of an event as the pre-storm profile for each subsequent event. For the largest event the water levels caused noticeable retreat of the dune toe due to the high water elevation. For the other events the greatest evolution occurs over the bar formations (erosion) and within the corresponding troughs (deposition) of the upper beach profile. The sequence of events impacting the size of this ridge-runnel feature is important as it consequently changes the resilience of the system to the most extreme event that causes dune retreat. The highest erosion during each single storm event was always observed when that storm initialised the storm cluster. The most severe storm always resulted in the most erosion during each cluster, no matter when it occurred within the chronology, although the erosion volume due to this storm was reduced when it was not the primary event. The greatest cumulative cluster erosion occurred with increasing storm severity; however, the variability in cumulative cluster impact over a beach/dune cross-section due to storm chronology is minimal. Initial storm impact can act to enhance or reduce the system resilience to subsequent impact, but overall the cumulative impact is controlled by the magnitude and number of the storms. This model application provides inter-survey information about morphological response to repeated storm impact. This will inform local managers of the potential beach response and dune vulnerability to variable storm configurations.

scholarly journals SIMULATION MODELING OP DUNE EROSION

1988 ◽  
Vol 1 (21) ◽  
pp. 137 ◽  
Author(s):  
M.F. Overton ◽  
J.S. Fisher
Keyword(s):  
Simulation Modeling ◽  
Significant Wave Height ◽  
Basic Assumption ◽  
Time History ◽  
Storm Event ◽  
Numerical Techniques ◽  
Dune Erosion ◽  
History Of ◽  
Dune Morphology ◽  
The Relationship

Using a combination of laboratory, field, and numerical techniques, we have developed a methodology for predicting the extent of dune erosion due to a given set of wave conditions and the beach and dune morphology. A basic assumption in this model is that the volume eroded from the dune is a function of the swash acting on the dune. Because the model is built on this premise, it is necessary to look at the mechanics of two ongoing processes in the storm environment. The first is the relationship between the swash characteristics and the volume of material eroded from the dune face. The second is the relationship between the time history of the swash characteristics at the dune face and the statistics of the storm event, the significant wave height and wave period.

scholarly journals Ensemble models from machine learning: an example of wave runup and coastal dune erosion

2019 ◽  
Author(s):  
Tomas Beuzen ◽  
Evan B. Goldstein ◽  
Kristen D. Splinter
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Coastal Dune ◽  
Data Driven ◽  
Storm Event ◽  
Wave Runup ◽  
Dune Erosion ◽  
Unseen Data ◽  
Uncertainty Estimates ◽  
Narrabeen Beach

Abstract. After decades of study and significant data collection of time-varying swash on sandy beaches, there is no single deterministic prediction scheme for wave runup that eliminates prediction error – even bespoke, locally tuned predictors present scatter when compared to observations. Scatter in runup prediction is meaningful and can be used to create probabilistic predictions of runup for a given wave climate and beach slope. This contribution demonstrates this using a data-driven Gaussian process predictor; a probabilistic machine learning technique. The runup predictor is developed using one year of hourly wave runup data (8328 observations) collected by a fixed LIDAR at Narrabeen Beach, Sydney, Australia. The Gaussian process predictor accurately predicts hourly wave runup elevation when tested on unseen data with a root mean-squared-error of 0.18 m and bias of 0.02 m. The uncertainty estimates output from the probabilistic GP predictor are then used practically in a deterministic numerical model of coastal dune erosion, which relies on a parameterization of wave runup, to generate ensemble predictions. When applied to a dataset of dune erosion caused by a storm event that impacted Narrabeen Beach in 2011, the ensemble approach reproduced ~ 85 % of the observed variability in dune erosion along the 3.5 km beach and provided clear uncertainty estimates around these predictions. This work demonstrates how data-driven methods can be used with traditional deterministic models to develop ensemble predictions that provide more information and greater forecasting skill when compared to a single model using a deterministic parameterization; an idea that could be applied more generally to other numerical models of geomorphic systems.

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