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.
Study Area
| 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 |
| Google Analytic Metrics | Metrics page |