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  • Long-term prediction of longshore sediment transport in the context of climate change

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    Etemad Shahidi510266-Published.pdf (953.5Kb)
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    Version of Record (VoR)
    Author(s)
    Zarifsanayei, AR
    Etemad-Shahidi, A
    Cartwright, N
    Strauss, D
    Griffith University Author(s)
    Strauss, Darrell R.
    Cartwright, Nick B.
    Etemad Shahidi, Amir F.
    Year published
    2020
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    Abstract
    Due to climate change impacts on atmospheric circulation, global and regional wave climate in many coastal regions around the world might change. Any changes in wave parameters could result in significant changes in wave energy flux, the patterns of coastal sediment transport, and coastal evolution. Although some studies have tried to address the potential impacts of climate change on longshore sediment transport (LST) patterns, they did not sufficiently consider the uncertainties arising from different sources in the projections. In this study, the uncertainty associated with the choice of model used for the estimation of ...
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    Due to climate change impacts on atmospheric circulation, global and regional wave climate in many coastal regions around the world might change. Any changes in wave parameters could result in significant changes in wave energy flux, the patterns of coastal sediment transport, and coastal evolution. Although some studies have tried to address the potential impacts of climate change on longshore sediment transport (LST) patterns, they did not sufficiently consider the uncertainties arising from different sources in the projections. In this study, the uncertainty associated with the choice of model used for the estimation of LST is examined. The models were applied to a short stretch of coastline located in Northern Gold Coast, Australia, where a huge volume of sediment is transported along the coast annually. The ensemble of results shows that the future mean annual and monthly LST rate might decrease by about 11 %, compared to the baseline period. The results also show that uncertainty associated with LST estimation is significant. Hence, it is proposed that this uncertainty, in addition to that from other sources, should be considered to quantify the contribution of each source in total uncertainty. In this way, a probabilistic-based framework can be developed to provide more meaningful output applicable to long-term coastal planning.
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    Conference Title
    Proceedings of virtual Conference on Coastal Engineering 2020
    Volume
    36
    Issue
    2020
    DOI
    https://doi.org/10.9753/icce.v36v.papers.15
    Copyright Statement
    © The Author(s) 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Civil engineering
    Publication URI
    http://hdl.handle.net/10072/412406
    Collection
    • Conference outputs

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