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.
|Title||Impact assessment of extreme storm events using a Bayesian network|
|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|
|Record Source||USGS Publications Warehouse|
|USGS Organization||St. Petersburg Coastal and Marine Science Center|