| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 01013 | |
| Number of page(s) | 9 | |
| Section | Intelligent Computing in Healthcare and Bioinformatics | |
| DOI | https://doi.org/10.1051/itmconf/20268401013 | |
| Published online | 06 April 2026 | |
Study on Coastal Erosion Prediction, Environmental Response and Buffer System Optimization of the Gold Coast, Australia
1 Faculty of Engineering School of Project Management, The University of Sydney, Sydney, Australia, 2006
2 Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China, 999078
* Corresponding author’s email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Coastal erosion poses a severe threat to the ecological security, infrastructure protection, and economic development of sandy coasts, particularly under the combined impact of global climate change and human activities. Taking the Gold Coast of Australia as a case study, this paper aims to address the challenge of continuous shoreline retreat. Based on the Coastal Sediment Transport Balance (CSTB) theory, a multi-factor coupled annual shoreline retreat rate prediction model was constructed. This model systematically integrates key drivers, including Sea-Level Rise (SLR), wave action, aeolian sand transport, and river sediment supply. Scenario simulations indicate that a 0.5 m sea-level rise could increase the erosion rate by 28% over 20 years. Furthermore, a coastal buffer system optimization model was developed using the Sequential Least Squares Programming (SLSQP) algorithm to balance protection costs and effects. The results show that a mixed scheme combining vegetation restoration, beach nourishment, and seawalls can reduce the erosion rate by 78% while satisfying cost constraints. This study provides a scientific basis for the dynamic prediction of sandy coastal erosion and the sustainable management of coastal zones.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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