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Probabilistic Imaging and Dynamic Modeling of Earthquake Source Processes

Citation

Jiang, Junle (2016) Probabilistic Imaging and Dynamic Modeling of Earthquake Source Processes. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9639MQC. https://resolver.caltech.edu/CaltechTHESIS:10142015-142502895

Abstract

Investigation of large, destructive earthquakes is challenged by their infrequent occurrence and the remote nature of geophysical observations. This thesis sheds light on the source processes of large earthquakes from two perspectives: robust and quantitative observational constraints through Bayesian inference for earthquake source models, and physical insights on the interconnections of seismic and aseismic fault behavior from elastodynamic modeling of earthquake ruptures and aseismic processes.

To constrain the shallow deformation during megathrust events, we develop semi-analytical and numerical Bayesian approaches to explore the maximum resolution of the tsunami data, with a focus on incorporating the uncertainty in the forward modeling. These methodologies are then applied to invert for the coseismic seafloor displacement field in the 2011 Mw 9.0 Tohoku-Oki earthquake using near-field tsunami waveforms and for the coseismic fault slip models in the 2010 Mw 8.8 Maule earthquake with complementary tsunami and geodetic observations. From posterior estimates of model parameters and their uncertainties, we are able to quantitatively constrain the near-trench profiles of seafloor displacement and fault slip. Similar characteristic patterns emerge during both events, featuring the peak of uplift near the edge of the accretionary wedge with a decay toward the trench axis, with implications for fault failure and tsunamigenic mechanisms of megathrust earthquakes.

To understand the behavior of earthquakes at the base of the seismogenic zone on continental strike-slip faults, we simulate the interactions of dynamic earthquake rupture, aseismic slip, and heterogeneity in rate-and-state fault models coupled with shear heating. Our study explains the long-standing enigma of seismic quiescence on major fault segments known to have hosted large earthquakes by deeper penetration of large earthquakes below the seismogenic zone, where mature faults have well-localized creeping extensions. This conclusion is supported by the simulated relationship between seismicity and large earthquakes as well as by observations from recent large events. We also use the modeling to connect the geodetic observables of fault locking with the behavior of seismicity in numerical models, investigating how a combination of interseismic geodetic and seismological estimates could constrain the locked-creeping transition of faults and potentially their co- and post-seismic behavior.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Earthquake source; Inverse problem; Bayesian inference; Elastodynamic modeling
Degree Grantor:California Institute of Technology
Division:Geological and Planetary Sciences
Major Option:Geophysics
Minor Option:Computational Science and Engineering
Awards:Demetriades-Tsafka-Kokkalis Prize in Seismo-Engineering, Prediction, and Protection, 2016
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Lapusta, Nadia (co-advisor)
  • Simons, Mark (co-advisor)
Thesis Committee:
  • Ampuero, Jean-Paul (chair)
  • Avouac, Jean-Philippe
  • Heaton, Thomas H.
  • Lapusta, Nadia
  • Simons, Mark
Defense Date:9 December 2015
Non-Caltech Author Email:junle.jiang (AT) gmail.com
Funders:
Funding AgencyGrant Number
NASA1447107
United States Geological SurveyG14AP00033
NSFEAR1142183, EAR1520907
Southern California Earthquake CenterEAR-0529922, 07HQAG0008
Record Number:CaltechTHESIS:10142015-142502895
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:10142015-142502895
DOI:10.7907/Z9639MQC
ORCID:
AuthorORCID
Jiang, Junle0000-0002-8796-5846
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9221
Collection:CaltechTHESIS
Deposited By: Junle Jiang
Deposited On:03 Oct 2016 23:03
Last Modified:04 Oct 2019 00:10

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