From Geoscience Australia

Towards spatially distributed quantitative assessment of tsunami inundation models

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Created 14/01/2025

Updated 14/01/2025

In this paper a new benchmark for tsunami model validation is pro- posed. The benchmark is based upon the 2004 Indian Ocean tsunami, which provides a uniquely large amount of observational data for model comparison. Unlike the small number of existing benchmarks, the pro- posed test validates all three stages of tsunami evolution - generation, propagation and inundation. Specifically we use geodetic measurements of the Sumatra{Andaman earthquake to validate the tsunami source, al- timetry data from the jason satellite to test open ocean propagation, eye-witness accounts to assess near shore propagation and a detailed inundation survey of Patong Bay, Thailand to compare model and observed inundation. Furthermore we utilise this benchmark to further validate the hydrodynamic modelling tool anuga which is used to simulate the tsunami inundation. Important buildings and other structures were incorporated into the underlying computational mesh and shown to have a large inuence of inundation extent. Sensitivity analysis also showed that the model predictions are comparatively insensitive to large changes in friction and small perturbations in wave weight at the 100 m depth contour.

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Field Value
Title Towards spatially distributed quantitative assessment of tsunami inundation models
Language eng
Licence notspecified
Landing Page https://devweb.dga.links.com.au/data/dataset/826277f7-497a-438d-827c-902a1fa1763b
Contact Point
Geoscience Australia
clientservices@ga.gov.au
Reference Period 20/04/2018
Geospatial Coverage http://www.ga.gov.au/place-names/PlaceDetails.jsp?submit1=GA1
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "Towards spatially distributed quantitative assessment of tsunami inundation models". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/towards-spatially-distributed-quantitative-assessment-of-tsunami-inundation-models

No duplicate datasets found.