Global EarthquakE ScEnarios (GEESE): An OpenQuake Engine-Based Rupture Matching Algorithm and Scenarios Database for Seismic Source Model Testing and Rapid Post-Event Response Analysis

The Global EarthquakE ScEnarios (GEESE) algorithm retrieves from a seismic hazard input model the ruptures matching a set of criteria (e.g., magnitude, location, focal mechanism). We applied the GEESE algorithm to create a publicly available database (version 1.0) of finite rupture models for past...

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Bibliographic Details
Main Authors: Christopher Brooks, Marco Pagani, Manuela Villani, Kendra Johnson, Richard Styron, Kirsty Bayliss
Format: Article
Language:English
Published: McGill University 2025-07-01
Series:Seismica
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Online Access:https://seismica.library.mcgill.ca/article/view/1654
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Summary:The Global EarthquakE ScEnarios (GEESE) algorithm retrieves from a seismic hazard input model the ruptures matching a set of criteria (e.g., magnitude, location, focal mechanism). We applied the GEESE algorithm to create a publicly available database (version 1.0) of finite rupture models for past earthquakes which can be used for scenario seismic hazard and risk analysis applications. To this end, we selected earthquakes with a moment magnitude larger than 7.0 and hypocentral depth less than 200 km in the ISC-GEM catalogue (version 10.0) and retrieved the best matching ruptures from the seismic hazard models in the GEM Mosaic. The GEESE algorithm also automatically computes a set of ground-motion fields using each matched rupture, which are also provided in the database. The ability of the GEESE algorithm to test whether a Mosaic model can generate a rupture sufficiently representative of a queried event is a useful means of evaluating the Mosaic model's seismic source characterisation (SSC). Sufficiently matching ruptures are retrieved from the Global Mosaic for 90 percent of the tested ISC-GEM events. The GEESE algorithm can also be used in post-event response analysis to rapidly obtain an initial finite rupture when only minimal event information is initially available. A demonstration of these capabilities of the GEESE algorithm is provided using the 2023 Morocco earthquake, the 1994 Northridge earthquake, and the 2023 Kahramanmaras earthquake.
ISSN:2816-9387