Surrogate model development for coastal dune erosion under storm conditions

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Abstract

Early coastal dune erosion predictions are essential to avoid potential flood consequences but most dune erosion numerical models are computationally expensive, hence their application in Early Warning Systems is limited. Here, based on a combination of optimally sampled synthetic sea storms with a calibrated and validated XBeach model, we develop a surrogate model capable of producing fast and accurate dune erosion predictions under storm conditions when water level and wave forecasts are available. The analysis is performed on Dauphin Island, AL, where we train Multiple Linear Regression Models with oceanographic forcing from the selected sea storms (i.e., XBeach input) and predicted changes in the dune system (i.e., XBeach output). Surrogate model performance is assessed with a rigorous k-fold cross validation. Although changes in the location of dune features are not well predicted, the model attains good performance when predicting changes in dune elevation, barrier-island width and volume.

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Additional publication details

Publication type Conference Paper
Publication Subtype Conference Paper
Title Surrogate model development for coastal dune erosion under storm conditions
DOI 10.1142/9789811204487_0116
Year Published 2019
Language English
Contributing office(s) St. Petersburg Coastal and Marine Science Center
Description 13 p.
Larger Work Type Book
Larger Work Subtype Conference publication
Larger Work Title Proceedings of the 9th Coastal Sediments Conference
First page 1327
Last page 1339
Country United States
State Alabama
Other Geospatial Dauphin Island