Impact assessment of extreme storm events using a Bayesian network

Impact assessment of extreme storm events using a Bayesian network

Den Heijer, C.
Knipping, D.T.J.A.
Plant, N.G.
Van Thiel de Vries, J.S.M.
Baart, F.
Van Gelder, P.H.A.J.M.

Civil Engineering and Geosciences

Hydraulic Engineering

2012-07-01

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.

dune erosion
extreme conditions
probabilistic approach
Bayesian Network model

http://resolver.tudelft.nl/uuid:f728f864-5c4a-48f3-8d8a-132d14fb8cc8

Coastal Engineering Research Council

2156-1028

ICCE 2012: Proceedings of the 33rd International Conference on Coastal Engineering, Santander, Spain, 1-6 July 2012

Institutional Repository

conference paper

(c) 2012 The Author(s)
Creative Commons BY