Broadband Synthetic Seismograms for Magnitude 9 Earthquakes on the Cascadia Megathrust Based on 3D Simulations and Stochastic Synthetics, Part 2: Rupture Parameters and Variability

Wirth, Erin A.; Frankel, Arthur; Marafi, Nasser A.; Vidale, John E.; Stephenson, William J.

doi:10.1785/0120180029

Cited by 68 publications

(64 citation statements)

References 43 publications

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“…We suggest that this is due to the variation in the angle of incidence, as some studies have shown that basin effects in Mexico City may be a combination of path and site effects. Other studies in basins worldwide have noted both path and site effects as the cause of basin amplification (Wirth et al, 2018) In addition to observing large residuals in Mexico City for these earthquakes, we also see large residuals in the city of Puebla for both the Tehuantepec and Puebla-Morelos earthquakes at longer periods (SA < 0:5 s; Figs. 2, 3, 6, and 7).…”

Section: Basin Effectssupporting

confidence: 77%

Ground Motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, Earthquakes

Sahakian

Melgar

Quintanar

et al. 2018

Bulletin of the Seismological Society of America

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The 2017 M 8.2 Tehuantepec and M 7.1 Puebla-Morelos earthquakes were deep inslab normal-faulting events that caused significant damage to several central-to-southern regions of Mexico. Inslab earthquakes are an important component of seismicity and seismic hazard in Mexico. Ground-motion prediction equations (GMPEs) are an integral part of seismic hazard assessment as well as risk and rapid-response products. This work examines the observed ground motions from these two events in comparison to the predicted median ground motions from four GMPEs. The residuals between the observed and modeled ground motions allow us to study regional differences in shaking, the effects of each earthquake, and basin effects in Mexico City, Puebla, and Oaxaca. We find that the ground motions from these two earthquakes are generally well modeled by the GMPEs. However, the Tehuantepec event shows larger than expected ground motions at greater distances and longer periods, which suggests a waveguide effect from the subduction zone geometry. Finally, Mexico City and the cities of Puebla and Oaxaca exhibit very large ground motions, indicative of well-known site and basin effects that are much stronger than the basin terms included in some of the GMPEs. Simple and rapid ground-motion parameter estimates that include site effects are key for hazard and real-time risk assessments in regions such as Mexico, where the vast majority of the population lives in areas where the aforementioned effects are relevant. However, GMPEs based on site correction terms dependent on topographic slope proxies underestimate, at least in the three cities tackled in this work, the observed amplification. Therefore, there is a need to improve models of seismic amplification in basins that could be included in GMPEs.Electronic Supplement: Tables of ground-motion intensity measures for each station and earthquake, as well as the residual uncertainties for each model, over all distances, and figures showing comprehensive ground-motion prediction equation (GMPE) and residuals results, for every period considered in this study, and the uncertainties.

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Section: Basin Effectssupporting

confidence: 77%

Ground Motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, Earthquakes

Sahakian

Melgar

Quintanar

et al. 2018

Bulletin of the Seismological Society of America

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“…In fact, negative shear stress rates in the gap appear to be a necessary condition to fit the vertical geodetic data, irrespective of imposed locking depth (Bruhat & Segall, 2016). These results support a seismic hazard source model that extends below the locked region, which can be directly implemented in current kinematic rupture models Wirth et al, 2018). We find that shear stress and friction levels in the gap play a principal role in governing downdip rupture propagation.…”

Section: Introductionsupporting

confidence: 72%

“…While we also employed an elastic half-space model to simulate dynamic rupture, inelastic material effects around the fault zone and upper plate, or a nonplanar free-surface could also influence predicted coseismic uplift and subsidence signals (Tinti & Armigliato, 2002). It is also unclear whether the next Cascadia earthquake will rupture in a similar way as the 1700 Cascadia earthquake (P. L. Wang et al, 2013;Wirth et al, 2018). It is also unclear whether the next Cascadia earthquake will rupture in a similar way as the 1700 Cascadia earthquake (P. L. Wang et al, 2013;Wirth et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…Alternatively, the gap in southern Cascadia may behave as a barrier to downdip rupture relative to the ETS region if dynamic friction levels exceed 0.3 in the gap (i.e., Figure S6) or if viscous-shear effects can impact coseismic rupture (Gao & Wang, 2017). It is also unclear whether the next Cascadia earthquake will rupture in a similar way as the 1700 Cascadia earthquake (P. L. Wang et al, 2013;Wirth et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

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How the Transition Region Along the Cascadia Megathrust Influences Coseismic Behavior: Insights From 2‐D Dynamic Rupture Simulations

Ramos

Huang

2019

Geophysical Research Letters

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There is a strong need to model potential rupture behaviors for the next Cascadia megathrust earthquake. However, there exists significant uncertainty regarding the extent of downdip rupture and rupture speed. To address this problem, we study how the transition region (i.e., the gap), which separates the locked from slow‐slip regions, influences coseismic rupture propagation using 2‐D dynamic rupture simulations governed by a slip‐weakening friction law. We show that rupture propagation through the gap is strongly controlled by the amount of accumulated tectonic initial shear stress and gap friction level. A large amplitude negative dynamic stress drop is needed to arrest downdip rupture. We also observe downdip supershear rupture when the gradient in effective normal stress from the locked to slow‐slip regions is dramatic. Our results justify kinematic rupture models that extend below the gap and suggests the possibility of high‐frequency energy radiation during the next Cascadia megathrust earthquake.

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“…In recent years, significant progress has been made in modeling synthetic ground motions. With the advance of modern computing power, studies such as Bydlon et al (), Graves and Pitarka (), Mai et al (), Taborda et al (), Imperatori and Mai (), Frankel et al (), Wirth et al (), Withers, Olsen, Day, and Shi,(), Withers, Olsen, Shi, and Day, (), Olsen et al (), Graves and Pitarka (), Andrews and Ma (), Hartzell et al (), Pitarka et al (), Pitarka et al (), and Moschetti et al () have incorporated increasingly accurate physics into simulations. Some of these improvements include explicitly accounting for complex rupture processes and the propagation of waves through realistic 3‐D crustal structure to simulate ground motions at a wider range of frequencies for a variety of end‐use cases (from assessing regional seismic hazard related to basin amplification to better understanding the role of anelasticity in nuclear monitoring).…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions

Withers

Moschetti

Thompson

2020

Geophysical Research Letters

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We use a machine learning approach to build a ground motion model (GMM) from a synthetic database of ground motions extracted from the Southern California CyberShake study. An artificial neural network is used to find the optimal weights that best fit the target data (without overfitting), with input parameters chosen to match that of state‐of‐the‐art GMMs. We validate our synthetic‐based GMM with empirically based GMMs derived from the globally based Next Generation Attenuation West2 data set, finding near‐zero median residuals and similar amplitude and trends (with period) of total variability. Additionally, we find that the artificial neural network GMM has similar bias and variability to empirical GMMs from records of the recent Mw7.1 Ridgecrest event, which neither GMM has included in its formulation. As simulations continue to better model broadband ground motions, machine learning provides a way to utilize the vast amount of synthetically generated data and guide future parameterization of GMMs.

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Broadband Synthetic Seismograms for Magnitude 9 Earthquakes on the Cascadia Megathrust Based on 3D Simulations and Stochastic Synthetics, Part 2: Rupture Parameters and Variability

Cited by 68 publications

References 43 publications

Ground Motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, Earthquakes

Ground Motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, Earthquakes

How the Transition Region Along the Cascadia Megathrust Influences Coseismic Behavior: Insights From 2‐D Dynamic Rupture Simulations

A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions

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