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Impact assessment of extreme storm events using a Bayesian network

January 1, 2012

This paper describes an investigation on the usefulness of Bayesian Networks in the safety assessment of dune coasts. A network has been created that predicts the erosion volume based on hydraulic boundary conditions and a number of cross-shore profile indicators. Field measurement data along a large part of the Dutch coast has been used to train the network. Corresponding storm impact on the dunes was calculated with an empirical dune erosion model named duros+. Comparison between the Bayesian Network predictions and the original duros+ results, here considered as observations, results in a skill up to 0.88, provided that the training data covers the range of predictions. Hence, the predictions from a deterministic model (duros+) can be captured in a probabilistic model (Bayesian Network) such that both the process knowledge and uncertainties can be included in impact and vulnerability assessments.

Publication Year 2012
Title Impact assessment of extreme storm events using a Bayesian network
DOI 10.9753/
Authors C.(Kees) den Heijer, Dirk T.J.A. Knipping, Nathaniel G. Plant, Jaap S. M. van Thiel de Vries, Fedor Baart, Pieter H. A. J. M. van Gelder
Publication Type Conference Paper
Publication Subtype Conference Paper
Index ID 70118345
Record Source USGS Publications Warehouse
USGS Organization St. Petersburg Coastal and Marine Science Center