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Subaerial Profiles at Two Beaches: Equilibrium and Machine Learning
  • +5
  • Mika Natalie Siegelman,
  • Ryan A McCarthy,
  • Adam Patrick Young,
  • William O'Reilly,
  • Hironori Matsumoto,
  • Mele O Johnson,
  • Connor Mack,
  • R.T. Guza
Mika Natalie Siegelman
Scripps Institution of Oceanography

Corresponding Author:[email protected]

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Ryan A McCarthy
Scripps Institution of Oceanography
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Adam Patrick Young
Scripps Institution of Oceanography
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William O'Reilly
University of California, San Diego
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Hironori Matsumoto
Scripps Institution of Oceanography
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Mele O Johnson
Scripps Institution of Oceanography
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Connor Mack
Scripps Institution of Oceanography
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R.T. Guza
Scripps Institution of Oceanography
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Abstract

Weekly to quarterly beach elevation surveys spanning 700-800 m alongshore and 8 years at two beaches were each supplemented with several months of ∼100 sub-weekly surveys. These beaches, which have different sediment types (sand vs. sand-cobble mix), both widen in summer in response to the seasonal wave climate, in agreement with a generic equilibrium model. Results suggest differences in backshore erodability contribute to differing beach responses in the stormiest (El Niño) year. At both sites, the time dependence of the equilibrium modeled shoreline resembles the first mode of an EOF decomposition of the observations. With sufficient training, an equilibrium-informed Extra Tree Regression model, that includes features motivated by equilibrium modelling, can significantly outperform a generic equilibrium model.
13 Nov 2023Submitted to ESS Open Archive
14 Nov 2023Published in ESS Open Archive