Enhancing overland flow tsunami modelling across urban topography with novel statistical emulation

Lead Research Organisation: University College London
Department Name: Statistical Science

Abstract

Existing tsunami simulation models often rely on bare-earth topography to model inundation and overland flow. In reality, the flow of water inundating coastal regions is far more complex. The presence of buildings, structures, vegetation, and other obstacles, all influence the flow of water during tsunami inundation. However, many tsunami models disregard terrestrial obstacles in favour of increased computation speeds. Smoothed particle hydrodynamics (SPH) models are able to model such complex flows but are computationally demanding, even at a local scale, and require tuning for stability and precision. Furthermore, SPH models cannot quickly or efficiently model the generation and transoceanic propagation. So, we will couple a traditional tsunami model with an SPH solver, DualSPHysics, to generate realistic end-to-end simulations of coastal tsunami impacts, using state-of-the-art GPU clusters. This would constitute a first innovation in tsunami modelling worldwide, as recent work has been done only on simplified settings. This research project will focus on particular case studies (to date, Whakatane, New Zealand, and Cilacap, Indonesia).

In a second step we will explore the use of statistical emulation to produce probabilistic tsunami hazard assessments. Emulators are approximations of complex computer models with orders of magnitude reduction in computation, compared to the simulation-based modelling. We will fit an emulator to the coupled simulators. It will deliver approximations of simulation outputs, including inundation extent, velocity and height, accounting for the urban topography. It will crucially enable the propagation of uncertainties from tsunami sources to possible impacts, a first at this scale.

We will then validate the emulation process by applying it to a range of applications, looking to aid the evaluation of their practical use in disaster management. Such applications have, to date, looked at aiming to quantify pressures and stresses on urban structures and understand fluid velocities within harbours. The research will also test the accuracy and precision of these emulators by modelling past and potential future events, in doing so, comparing outputs produced by simulation models, emulators, and reality. Later, the use of advanced graphical visualisation techniques using Blender, and looking into the future possibilities for these fitted emulators will be investigated and discussed.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007229/1 01/10/2019 30/09/2027
2390153 Studentship NE/S007229/1 01/10/2020 30/09/2024 Jack Dignan