Quantification of uncertainties of the tsunami risk in Cascadia

We first show new realistic simulations of earthquake-generated tsunamis in Cascadia (Western Canada and USA) using VOLNA. VOLNA is a solver of nonlinear shallow water equations on unstructured meshes that is accelerated on the new GPU system Emerald. Primary outputs from these runs are tsunami inundation maps, accompanied by site-specific wave trains and flow velocity histories. The variations in inputs (here seabed deformations due to earthquakes) are time-varying shapes difficult to sample, and they require an integrated statistical and geophysical analysis. Furthermore, the uncertainties in the bathymetry require extensive investigation and optimization of the resolutions at the source and impact. Thus we need to run VOLNA for well chosen combinations of the inputs and the bathymetry to reflect the various sources of uncertainties, and we interpolate in between using a so-called statistical emulator that keeps track of the additional uncertainties due to the interpolation itself. We present novel adaptive sequential designs that enable such choices of the combinations for our Gaussian Process (GP) based emulator in order to maximize the information from the limited number of runs of VOLNA that can be computed. GPs show strength in the approximation of the response surface but suffer from large computer costs associated with the fitting. Hence, a careful selection of the inputs is necessary to optimize the trade-off fit versus computations. Finally, we also propose to assess the frequencies and intensities of the earthquakes along the Cascadia subduction zone that have been demonstrated by geological palaeoseismic, palaeogeodetic and tsunami deposit studies in Cascadia. As a result, the hazard assessment aims to reflect the multiple non-linearities and uncertainties for the tsunami risk in Cascadia.