Earthquake forecasting from paleoseismic records.

Autor: Wang T; Department of Mathematics and Statistics, University of Otago, Dunedin, 9016, New Zealand. ting.wang@otago.ac.nz., Griffin JD; Community Safety Branch, Geoscience Australia, Symonston, 2609, ACT, Australia., Brenna M; Department of Geology, University of Otago, Dunedin, 9016, New Zealand., Fletcher D; David Fletcher Consulting Limited, 67 Stornoway Street, Karitane, 9471, New Zealand., Zeng J; Department of Preventive and Social Medicine, Otago Medical School, University of Otago, Dunedin, 9016, New Zealand., Stirling M; Department of Geology, University of Otago, Dunedin, 9016, New Zealand., Dillingham PW; Department of Mathematics and Statistics, University of Otago, Dunedin, 9016, New Zealand.; Coastal People: Southern Skies Centre of Research Excellence, University of Otago, Dunedin, 9016, New Zealand., Kang J; Beef + Lamb New Zealand Genetics, 3 Crawford Street, PO Box 5501, Dunedin, 9054, New Zealand.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2024 Mar 02; Vol. 15 (1), pp. 1944. Date of Electronic Publication: 2024 Mar 02.
DOI: 10.1038/s41467-024-46258-z
Abstrakt: Forecasting large earthquakes along active faults is of critical importance for seismic hazard assessment. Statistical models of recurrence intervals based on compilations of paleoseismic data provide a forecasting tool. Here we compare five models and use Bayesian model-averaging to produce time-dependent, probabilistic forecasts of large earthquakes along 93 fault segments worldwide. This approach allows better use of the measurement errors associated with paleoseismic records and accounts for the uncertainty around model choice. Our results indicate that although the majority of fault segments (65/93) in the catalogue favour a single best model, 28 benefit from a model-averaging approach. We provide earthquake rupture probabilities for the next 50 years and forecast the occurrence times of the next rupture for all the fault segments. Our findings suggest that there is no universal model for large earthquake recurrence, and an ensemble forecasting approach is desirable when dealing with paleoseismic records with few data points and large measurement errors.
(© 2024. The Author(s).)
Databáze: MEDLINE
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