Assessing Margin-Wide Rupture Behaviors Along the Cascadia Megathrust With 3-D Dynamic Rupture Simulations

Marlon Ramos, Yihe Huang, Thomas Ulrich, D. Li, Alice-Agnes Gabriel, Amanda M. Thomas

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From California to British Columbia, the Pacific Northwest coast bears an omnipresent earthquake and tsunami hazard from the Cascadia subduction zone. Multiple lines of evidence suggests that magnitude eight and greater megathrust earthquakes have occurred - the most recent being 321 years ago (i.e., 1700 A.D.). Outstanding questions for the next great megathrust event include where it will initiate, what conditions are favorable for rupture to span the convergent margin, and how much slip may be expected. We develop the first 3-D fully dynamic rupture simulations for the Cascadia subduction zone that are driven by fault stress, strength and friction to address these questions. The initial dynamic stress drop distribution in our simulations is constrained by geodetic coupling models, with segment locations taken from geologic analyses. We document the sensitivity of nucleation location and stress drop to the final seismic moment and coseismic subsidence amplitudes. We find that the final earthquake size strongly depends on the amount of slip deficit in the central Cascadia region, which is inferred to be creeping interseismically, for a given initiation location in southern or northern Cascadia. Several simulations are also presented here that can closely approximate recorded coastal subsidence from the 1700 A.D. event without invoking localized high-stress asperities along the down-dip locked region of the megathrust. These results can be used to inform earthquake and tsunami hazards for not only Cascadia, but other subduction zones that have limited seismic observations but a wealth of geodetic inference.
Original languageEnglish (US)
JournalJournal of Geophysical Research: Solid Earth
Issue number7
StatePublished - Jul 16 2021
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2021-08-19
Acknowledged KAUST grant number(s): ORS-2017-CRG6 3389.02
Acknowledgements: We extend our gratitude to the Associate Editor, Sylvain Barbot, Yongfei Wang and two anonymous reviewers for their constructive evaluation of this study. Marlon D. Ramos, Yihe Huang and Amanda M. Thomas acknowledge funding through the National Science Foundation PREEVENTS grant No. 1663769. Thomas Ulrich, Duo Li and Alice-Agnes Gabriel acknowledge funding from the European Research Council under the European Union's Horizon 2020 research and innovation programme (TEAR, grant no. 852992 and ChEESE, grant no. 823844), by the German Research Foundation (DFG) (grants no. GA 2465/2-1, GA 2465/3-1), by KAUST-CRG (grant no. ORS-2017-CRG6 3389.02) and by KONWIHR (project NewWave). Yihe Huang and Alice-Agnes Gabriel additionally acknowledge travel funding from BaCaTeC (project A4 2015-1).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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