Predicting Dune Erosion With Combined Process-Based And Multivariate Statistical Models

Abstract

The new modelling framework presented here uses advanced statistical models to simulate plausible sea-storm events covering data outside the observational range and machine-learning algorithms to develop meta-models capable of mimicking a state-of-the-art numerical model to simulate dune response during storm events in a computationally highly efficient way. Our results show great potential of the framework be used for both probabilistic long-term coastal change hazard simulations and short-term (ensemble) forecasting (using wave and water level forecast information). The framework itself is transferrable to other coastline stretches where water level and wave observations as well as bathymetric information are available.

Publication Date

1-1-2018

Publication Title

Proceedings of the Coastal Engineering Conference

Volume

36

Issue

2018

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

85074113792 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85074113792

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