Probabilistic prediction of barrier-island response to hurricanes

Journal of Geophysical Research
By:  and 



Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

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Publication type Article
Publication Subtype Journal Article
Title Probabilistic prediction of barrier-island response to hurricanes
Series title Journal of Geophysical Research
DOI 10.1029/2011JF002326
Volume 117
Issue F3
Year Published 2012
Language English
Publisher Wiley
Contributing office(s) St. Petersburg Coastal and Marine Science Center
Description 17 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Journal of Geophysical Research
Country United States
State Florida
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