Impact assessment of extreme storm events using a Bayesian network
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Abstract
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 type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Impact assessment of extreme storm events using a Bayesian network |
| DOI | 10.9753/icce.v33.management.4 |
| Issue | 33 |
| Year Published | 2012 |
| Language | English |
| Publisher | Coastal Engineering Research Council |
| Contributing office(s) | St. Petersburg Coastal and Marine Science Center |
| Description | 15 p. |
| Larger Work Type | Book |
| Larger Work Subtype | Conference publication |
| Larger Work Title | Coastal Engineering 2012: Proceedings of the 33rd International Conference on Coastal Engineering |
| Conference Title | 33rd International Conference on Coastal Engineering |
| Conference Location | Santander, Spain |
| Google Analytic Metrics | Metrics page |