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A simple model to simulate beach state variability

BLESSING NWANOSIKE, Dominic Reeve, Harshinie Karunarathna Orcid Logo

Coastal Engineering Journal, Volume: 67, Issue: 3, Pages: 495 - 514

Swansea University Authors: BLESSING NWANOSIKE, Dominic Reeve, Harshinie Karunarathna Orcid Logo

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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...

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Published in: Coastal Engineering Journal
ISSN: 2166-4250 1793-6292
Published: Informa UK Limited 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa69724
first_indexed 2025-06-12T08:29:33Z
last_indexed 2025-10-18T09:46:29Z
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spelling 2025-10-17T11:16:37.5221727 v2 69724 2025-06-12 A simple model to simulate beach state variability 11f136428ee7b99247d9885250fa6030 BLESSING NWANOSIKE BLESSING NWANOSIKE true false 3e76fcc2bb3cde4ddee2c8edfd2f0082 Dominic Reeve Dominic Reeve true false 0d3d327a240d49b53c78e02b7c00e625 0000-0002-9087-3811 Harshinie Karunarathna Harshinie Karunarathna true false 2025-06-12 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. Journal Article Coastal Engineering Journal 67 3 495 514 Informa UK Limited 2166-4250 1793-6292 Dean’s parameter, cross-shore beach change, XBeach, empirical beach state change model 17 6 2025 2025-06-17 10.1080/21664250.2025.2520084 COLLEGE NANME COLLEGE CODE Swansea University SU Library paid the OA fee (TA Institutional Deal) This research was funded by The Petroleum Technology Trust Fund (PTDF), Nigeria [Grants No. OSS/PHD/POF/1317/17]. 2025-10-17T11:16:37.5221727 2025-06-12T09:26:23.1835148 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering BLESSING NWANOSIKE 1 Dominic Reeve 2 Harshinie Karunarathna 0000-0002-9087-3811 3 69724__34610__7f1cebef6e34414683471c1feab1e84a.pdf 69724.VOR.pdf 2025-06-27T12:49:41.2644534 Output 17160179 application/pdf Version of Record true © 2025 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY). true eng http://creativecommons.org/licenses/by/4.0/
title A simple model to simulate beach state variability
spellingShingle A simple model to simulate beach state variability
BLESSING NWANOSIKE
Dominic Reeve
Harshinie Karunarathna
title_short A simple model to simulate beach state variability
title_full A simple model to simulate beach state variability
title_fullStr A simple model to simulate beach state variability
title_full_unstemmed A simple model to simulate beach state variability
title_sort A simple model to simulate beach state variability
author_id_str_mv 11f136428ee7b99247d9885250fa6030
3e76fcc2bb3cde4ddee2c8edfd2f0082
0d3d327a240d49b53c78e02b7c00e625
author_id_fullname_str_mv 11f136428ee7b99247d9885250fa6030_***_BLESSING NWANOSIKE
3e76fcc2bb3cde4ddee2c8edfd2f0082_***_Dominic Reeve
0d3d327a240d49b53c78e02b7c00e625_***_Harshinie Karunarathna
author BLESSING NWANOSIKE
Dominic Reeve
Harshinie Karunarathna
author2 BLESSING NWANOSIKE
Dominic Reeve
Harshinie Karunarathna
format Journal article
container_title Coastal Engineering Journal
container_volume 67
container_issue 3
container_start_page 495
publishDate 2025
institution Swansea University
issn 2166-4250
1793-6292
doi_str_mv 10.1080/21664250.2025.2520084
publisher Informa UK Limited
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
document_store_str 1
active_str 0
description 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.
published_date 2025-06-17T05:25:24Z
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