Statistical emulation of a tsunami model for sensitivity analysis and uncertainty quantification

Abstract

Due to the catastrophic consequences of tsunamis, early warnings need to be issued quickly in order to mitigate the hazard. Additionally, there is a need to represent the uncertainty in the predictions of tsunami characteristics corresponding to the uncertain trigger features (e.g. either position, shape and speed of a landslide, or sea floor deformation associated with an earthquake). Unfortunately, computer models are expensive to run. This leads to significant delays in predictions and makes the uncertainty quantification impractical. Statistical emulators run almost instantaneously and may represent well the outputs of the computer model. In this paper, we use the Outer Product Emulator to build a fast statistical surrogate of a landslide-generated tsunami computer model. This Bayesian framework enables us to build the emulator by combining prior knowledge of the computer model properties with a few carefully chosen model evaluations. The good performance of the emulator is validated using the Leave-One-Out method.

Cited by in corpus (9)

• Generating Random Earthquake Events for PTHA
• Can Small Islands Protect Nearby Coasts From Tsunamis? An Active Experimental Design Approach
• On the modelling of tsunami generation and tsunami inundation
• Quantifying Uncertainties in Fault Slip Distribution during the Tōhoku Tsunami using Polynomial Chaos
• Quantifying Uncertainties in the 2004 Sumatra-Andaman Earthquake Source Parameters by Stochastic Inversion
• Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness
• Surrogate-based Optimization using Mutual Information for Computer Experiments (optim-MICE)
• Computationally efficient surrogate-based optimization of coastal storm waves heights and run-ups
• Efficient solvers for shallow-water Saint-Venant equations and debris transportation-deposition models