Combining numerical and statistical models to predict storm-induced dune erosion

Journal of Geophysical Research: Earth Surface
By: , and 



Dune erosion is an important aspect to consider when assessing coastal flood risk, as dune elevation loss makes the protected areas more susceptible to flooding. However, most advanced dune erosion numerical models are computationally expensive, which hinders their application in early-warning systems. Based on a combination of probabilistic and process-based numerical modeling, we develop an efficient statistical tool to predict dune erosion during storms. The analysis focuses on Dauphin Island, AL in the northern Gulf of Mexico, where we combine synthetic sea storms with a calibrated and validated XBeach model to develop and test a range of different surrogate models for their ability to predict barrier-island geometric parameters under storm conditions. Surrogate models are developed by combining the oceanographic forcing from 100 optimally sampled sea-storm events covering the entire multivariate parameter space (used as XBeach input) and associated changes in the dune system (XBeach output). We test four surrogate models using a k-fold approach for validation. All models perform well in predicting changes in dune elevation, barrier-island area, and width, but are less accurate in predicting alterations in the cross-shore locations of dune morphological features. Multivariate adaptive regression splines are identified as the best surrogate model based on their fast development and good performance, attaining a modified Mielke index of 0.81 for dune crest height. As demonstrated at Dauphin Island, our approach shows potential to be used in an operational framework to predict dune response (in particular crest elevation change) when water level and wave forecasts are available.

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Publication type Article
Publication Subtype Journal Article
Title Combining numerical and statistical models to predict storm-induced dune erosion
Series title Journal of Geophysical Research: Earth Surface
DOI 10.1029/2019JF005016
Volume 124
Issue 7
Year Published 2019
Language English
Publisher American Geophysical Union
Contributing office(s) St. Petersburg Coastal and Marine Science Center
Description 18 p.
First page 1817
Last page 1834
Country United States
State Alabama
Other Geospatial Dauphin Island
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