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A simple model to simulate beach state variability
Coastal Engineering Journal, Volume: 67, Issue: 3, Pages: 495 - 514
Swansea University Authors:
BLESSING NWANOSIKE, Dominic Reeve, Harshinie Karunarathna
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© 2025 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY).
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DOI (Published version): 10.1080/21664250.2025.2520084
Abstract
Predicting cross-shore profile shape is critical for understanding and managing dynamic coastal change. This study presents a novel empirical method to characterize and predict variability of cross-shore beach profile shape. The method was developed using a vast amount of synthetic cross-shore beach...
| Published in: | Coastal Engineering Journal |
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| ISSN: | 2166-4250 1793-6292 |
| Published: |
Informa UK Limited
2025
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa69724 |
| Abstract: |
Predicting cross-shore profile shape is critical for understanding and managing dynamic coastal change. This study presents a novel empirical method to characterize and predict variability of cross-shore beach profile shape. The method was developed using a vast amount of synthetic cross-shore beach change data generated from the process-based coastal morphodynamic model XBeach. The model was calibrated and validated using a large-scale experimental dataset on beach profile change, ensuring accuracy and reliability of the synthetic data. The dataset replicated cross-shore beach change of a wide range of beach characteristics from a broad spectrum of wave conditions. Four cross-shore beach morphology proxies that characterise the profile shape were extracted from those data. Then, empirical relationships were derived to link them to the Dean’s Number. The robustness of these relationships was tested and validated using beach profile change data from three diverse field sites and one experimental case on a gravel beach, demonstrating strong correlations and predictive capability. The findings highlight the significant role of physical drivers, such as incident wave characteristics, sediment characteristics, and beach slope, in influencing beach morphology and state transitions. This study advances the understanding of beach morphodynamics while providing a simple and practical approach for predicting profile change. |
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| Keywords: |
Dean’s parameter, cross-shore beach change, XBeach, empirical beach state change model |
| College: |
Faculty of Science and Engineering |
| Funders: |
This research was funded by The Petroleum Technology Trust Fund (PTDF), Nigeria [Grants No. OSS/PHD/POF/1317/17]. |
| Issue: |
3 |
| Start Page: |
495 |
| End Page: |
514 |