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Subaerial Profiles at Two Beaches: Equilibrium and Machine Learning

Mika Natalie Siegelman,Ryan A. McCarthy,Adam P. Young,W. C. O’Reilly,Hironori Matsumoto, Mele O Johnson, Chelsea J. Mack,R. T. Guza

Authorea (Authorea)(2023)

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摘要
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.
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关键词
beaches,machine learning,equilibrium
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