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Alongshore Varying Dune Retreat at a Barrier Island
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This research investigates the alongshore variability of shoreline and dune line responses to storm events and long-term changes on Culatra Island, located in the Algarve region of Portugal utilizing a combination of LiDAR data, satellite imagery, and numerical models (ShorelineS and SnapWave). Using a dune model based on Larson et al. (2016), integrated within the ShorelineS framework, to analyze the dynamic interactions between dune erosion, overwash by waves, and dune growth driven by aeolian (wind) transport. These interactions are critical in understanding the long-term and storm-induced changes in shoreline positions.The calibrated ShorelineS model, supported by SnapWave's wave data, reveals that longshore transport gradients are the predominant drivers of shoreline change, significantly influenced by southeast prevailing waves, shallow active heights at the ebb delta, and the presence of the western breakwater.By simplifying these processes into a 1D sand balance equation, where dune interactions are treated as source and sink terms, the model effectively captures several key dynamics of coastal morphology. However, certain idealizations, such as the assumed dune vegetation lines and simplified coastal profiles, result in some processes, like overwash, not being fully represented.To ensure the accuracy and reliability of the model outputs, extensive sensitivity analyses were conducted with parameters such as impact coefficient Cs, median grain size d50, wave output points distances, and sediment transport factor (qscal). Validation of the ShorelineS model against 2011 DEM data and satellite trends reveals varying degrees of accuracy. For shoreline positions, the model demonstrates a strong positive correlation with DEM data (R² = 0.78) and even better alignment with satellite trends (R² = 0.85). However, the model's predictions for dune positions exhibit higher variability and weaker correlations with DEM data (R² = 0.47), indicating significant discrepancies. Interestingly, the model shows a stronger positive correlation with satellite trends for dunes (slope = 0.96).The research identifies several key factors contributing to alongshore variability in dune and shoreline responses during storm events, including initial berm width, storm duration, wave height, and cumulative sediment transport due to dune erosion. Notably, dune responses exhibit higher sensitivity to these coastal parameters compared to shoreline responses, with cumulative sediment transport being a significant driver of dune change (Corr: -0.86).Overall, this study highlights the critical need for integrating comprehensive modeling approaches with empirical data to inform coastal management practices. It offers a robust framework for future research aimed at enhancing the sustainability and resilience of coastal environments.
Title: Alongshore Varying Dune Retreat at a Barrier Island
Description:
This research investigates the alongshore variability of shoreline and dune line responses to storm events and long-term changes on Culatra Island, located in the Algarve region of Portugal utilizing a combination of LiDAR data, satellite imagery, and numerical models (ShorelineS and SnapWave).
Using a dune model based on Larson et al.
(2016), integrated within the ShorelineS framework, to analyze the dynamic interactions between dune erosion, overwash by waves, and dune growth driven by aeolian (wind) transport.
These interactions are critical in understanding the long-term and storm-induced changes in shoreline positions.
The calibrated ShorelineS model, supported by SnapWave's wave data, reveals that longshore transport gradients are the predominant drivers of shoreline change, significantly influenced by southeast prevailing waves, shallow active heights at the ebb delta, and the presence of the western breakwater.
By simplifying these processes into a 1D sand balance equation, where dune interactions are treated as source and sink terms, the model effectively captures several key dynamics of coastal morphology.
However, certain idealizations, such as the assumed dune vegetation lines and simplified coastal profiles, result in some processes, like overwash, not being fully represented.
To ensure the accuracy and reliability of the model outputs, extensive sensitivity analyses were conducted with parameters such as impact coefficient Cs, median grain size d50, wave output points distances, and sediment transport factor (qscal).
Validation of the ShorelineS model against 2011 DEM data and satellite trends reveals varying degrees of accuracy.
For shoreline positions, the model demonstrates a strong positive correlation with DEM data (R² = 0.
78) and even better alignment with satellite trends (R² = 0.
85).
However, the model's predictions for dune positions exhibit higher variability and weaker correlations with DEM data (R² = 0.
47), indicating significant discrepancies.
Interestingly, the model shows a stronger positive correlation with satellite trends for dunes (slope = 0.
96).
The research identifies several key factors contributing to alongshore variability in dune and shoreline responses during storm events, including initial berm width, storm duration, wave height, and cumulative sediment transport due to dune erosion.
Notably, dune responses exhibit higher sensitivity to these coastal parameters compared to shoreline responses, with cumulative sediment transport being a significant driver of dune change (Corr: -0.
86).
Overall, this study highlights the critical need for integrating comprehensive modeling approaches with empirical data to inform coastal management practices.
It offers a robust framework for future research aimed at enhancing the sustainability and resilience of coastal environments.
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