Preprints
https://doi.org/10.5194/nhess-2021-63
https://doi.org/10.5194/nhess-2021-63

  09 Mar 2021

09 Mar 2021

Review status: this preprint is currently under review for the journal NHESS.

Probabilistic, high-resolution tsunami predictions in North Cascadia by exploiting sequential design for efficient emulation

Dimitra M. Salmanidou1, Joakim Beck2, and Serge Guillas1 Dimitra M. Salmanidou et al.
  • 1Department of Statistical Science, University College London, Gower Street London WC1E 6BT, United Kingdom
  • 2Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science & Technology (KAUST), Thuwal, Saudi Arabia

Abstract. The potential of a full-margin rupture along the Cascadia subduction zone poses a significant threat over a populous region of North America. Traditional probabilistic tsunami hazard assessments produce hazard maps based on simulated prediction of tsunami waves either under limited ranges of scenarios or at low resolution, due to cost. We use the GPU-accelerated tsunami simulator VOLNA-OP2 with a detailed representation of topographic and bathymetric features. We replace the simulator by a Gaussian Process emulator at each output location to overcome the large computational burden. The emulators are statistical approximations of the simulator behaviour. We train the emulators on a set of input-output pairs and use them to generate approximate output values over a six-dimensional scenario parameter space, e.g., uplift/subsidence ratio, maximum uplift, that represent the seabed deformation. We implement an advanced sequential design algorithm for the optimal selection of only sixty simulations. This approach allows for a first emulation-accelerated computation of probabilistic tsunami hazard in the region of the city of Victoria, British Columbia. The low cost of emulation provides for additional flexibility in the shape of the deformation, which we illustrate here, considering two families, buried rupture and splay-faulting, of 2,000 potential scenarios.

Dimitra M. Salmanidou et al.

Status: open (until 20 Apr 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Dimitra M. Salmanidou et al.

Model code and software

Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model Beck, J. and Guillas, S. https://doi.org/10.1137/140989613

The VOLNA-OP2 tsunami code415(version 1.5) Reguly, I. Z., Giles, D., Gopinathan, D., Quivy, L., Beck, J. H., Giles, M. B., Guillas, S., and Dias, F. https://doi.org/10.5194/gmd-11-4621-2018

Dimitra M. Salmanidou et al.

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Short summary
The potential of large magnitude earthquakes in Cascadia poses a significant threat over a populous region of North America. We use statistical emulation to assess the probabilistic tsunami hazard from such events in the region of the city of Victoria, British Columbia. The emulators are built following a sequential design approach for information gain over the input space. To predict the hazard at coastal locations of the region, two families of potential seabed deformation are considered.
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