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Tsunami risk modelling for Australia: understanding the impact of data

Hocking, G.ORCID: 0000-0002-5812-6015, Jakeman, J., Sexton, J. and Wand, M. (2008) Tsunami risk modelling for Australia: understanding the impact of data. In: 2008 Mathematics and Statistics in Industry Study Group, MISG2008, 28 January - 1 February, Wollongong, Australia pp. 23-36.

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Modelling the impacts from tsunami events is a complex task. The approach taken by Geoscience Australia is a hybrid one where two models are combined. The first is one which models the earthquake rupture and subsequent propagation in deep water with the second propagating the tsunami through shallow water and focusing on subsequent inundation and impact ashore. The computer model ANUGA is used for the latter part of the approach and was developed collaboratively between the Australian National University and geoscience Australia.

A critical requirement for reliable modelling is an accurate representation of the earth’s surface that extends from the open ocean through the inter-tidal zone into the onshore areas. However, this elevation data may come from a number of sources and will have a range of reliability.

There are two questions that arise when data is requested. The first deals with the true variability of the topography. E.g. a flat surface needn’t be sampled as finely as a highly convoluted surface. The second relates to sensitivity; how large if the error in the modelled output if the range of errors in the elevation data is known? ANUGA and similar models can take up days of computer time to simulate a particular scenario, and so full comparative tests for a range of input values is not viable. The main aim of this project was to understand the uncertainties on the outputs of the inundation model based on possible uncertainty on the input data.

Item Type: Conference Paper
Murdoch Affiliation(s): School of Chemical and Mathematical Science
Publisher: University of Wollongong
Copyright: MISG2008 (Mathematics and Statistics in Industry Study Group, School of Mathematics and Applied Statistics, University of Wollongong)
Notes: In: Marchant, T., Edwards, M. and Mercer, G. (eds) Proceedings of the 2008 Mathematics and Statistics in Industry Study Group, MISG2008, University of Wollongong, 2009, pp 23 - 36.
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