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The 2023 National Seismic Hazard Assessment for Australia. Model Input and Output Data

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Created 20/01/2025

Updated 20/01/2025

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This Geoscience Australia Record contains technical data and input files that, when used with the Global Earthquake Model’s (GEM’s) OpenQuake-engine probabilistic seismic hazard analysis software (Pagani et al., 2023), will enable end users to explore and reproduce the 2023 National Seismic Hazard Assessment (NSHA23) of Australia (Allen et al., 2023b). Output data, as calculated by Geoscience Australia using Version 3.16.1 of the OpenQuake-engine, are also provided. This report describes the NSHA23 input and output data only and does not discuss the scientific rationale behind the model development or the development of the NSHA23 earthquake catalogue. These details are provided in Allen et al. (2023b) and (Allen et al., 2024), and respective references therein. The NSHA23 provides estimates of seismic hazard for the six Australian states and two mainland territories. However, it does not provide updated hazard factors for Australia’s Antarctic and other offshore territories (e.g., Christmas Island, Cocos Island, Heard Island, Lord Howe Island, Macquarie Island and Norfolk Island).

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Title The 2023 National Seismic Hazard Assessment for Australia. Model Input and Output Data
Language eng
Licence notspecified
Landing Page https://devweb.dga.links.com.au/data/dataset/96ca51a5-a16b-4241-a5cb-9b1093250c3b
Contact Point
Geoscience Australia
clientservices@ga.gov.au
Reference Period 15/03/2024
Geospatial Coverage {"type": "Polygon", "coordinates": [[[112.0, -44.0], [154.0, -44.0], [154.0, -9.0], [112.0, -9.0], [112.0, -44.0]]]}
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "The 2023 National Seismic Hazard Assessment for Australia. Model Input and Output Data". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/the-2023-national-seismic-hazard-assessment-for-australia-model-input-and-output-data

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No duplicate datasets found.