SRCMOD: An Online Database of Finite-Fault Rupture Models

Martin, P.; Thingbaijam, K. K. S.

doi:10.1785/0220140077

Cited by 275 publications

(205 citation statements)

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“…10.1002/2016GL071700 Konca et al, 2008;Mai and Thingbaijam, 2014]-including asperities that constitute the majority of a fault's strength and nonasperities that contribute little to strength (Figure 1). The strength and corresponding stress drop of an asperity may greatly exceed the respective mean values for the whole rupture surface-depending on asperity size relative to rupture area of the earthquake [e.g., Somerville et al, 1999;Mai and Beroza, 2002;Ripperger and Mai, 2004;Kanamori and Brodsky, 2004;Konca et al, 2008;Mai and Thingbaijam, 2014].…”

Section: Geophysical Research Lettersmentioning

confidence: 99%

“…The strength and corresponding stress drop of an asperity may greatly exceed the respective mean values for the whole rupture surface-depending on asperity size relative to rupture area of the earthquake [e.g., Somerville et al, 1999;Mai and Beroza, 2002;Ripperger and Mai, 2004;Kanamori and Brodsky, 2004;Konca et al, 2008;Mai and Thingbaijam, 2014]. Indeed, the inferred coseismic stress drops on those asperities [e.g., Ripperger and Mai, 2004;Mai and Thingbaijam, 2014] compare well with stress drops suggested by high-speed laboratory friction experiments [e.g., Kanamori and Brodsky, 2004;Han et al, 2007;Di Toro et al, 2011]. We conclude that laboratory friction experiments portray "only" the rupture behavior of strength asperities.…”

Section: Geophysical Research Lettersmentioning

confidence: 99%

“…The observed large change in friction (typically Δμ ≥ 0.5) in such experiments, combined with effective normal stresses at seismogenic depths (σ eff ), yields coseismic stress drops Δτ = Δμσ eff that exceed those derived from seismological observations by multiples of 10. Consequently, laboratory-and field-based estimates of coseismic stress drop Δτ are incompatible, questioning the validity of current Δτ estimates and the conclusions that are based on them.We conjecture that the strong discrepancy in Δτ estimates is due to the nonplanarity of natural rupture surfaces [e.g., Power et al, 1988;Sagy et al, 2007;Candela et al, 2012;Brodsky et al, 2016], the spatial heterogeneity of rock strength on the fault (here strength refers to a fault's potential to sustain some amount of shear stress before slippage occurs [e.g., Ripperger and Mai, 2004;Konca et al, 2008;Mai and Thingbaijam, 2014]), and their combined effect on an earthquake's slip distribution and moment release. We employ large-scale numerical simulations to investigate how the surface roughness of a fault and its strength heterogeneity affect average slip D and seismic moment M 0 that are associated to stress drop Δτ.…”

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Fault roughness and strength heterogeneity control earthquake size and stress drop

Zielke

Gális

Martin

2017

Geophysical Research Letters

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An earthquake's stress drop is related to the frictional breakdown during sliding and constitutes a fundamental quantity of the rupture process. High‐speed laboratory friction experiments that emulate the rupture process imply stress drop values that greatly exceed those commonly reported for natural earthquakes. We hypothesize that this stress drop discrepancy is due to fault‐surface roughness and strength heterogeneity: an earthquake's moment release and its recurrence probability depend not only on stress drop and rupture dimension but also on the geometric roughness of the ruptured fault and the location of failing strength asperities along it. Using large‐scale numerical simulations for earthquake ruptures under varying roughness and strength conditions, we verify our hypothesis, showing that smoother faults may generate larger earthquakes than rougher faults under identical tectonic loading conditions. We further discuss the potential impact of fault roughness on earthquake recurrence probability. This finding provides important information, also for seismic hazard analysis.

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Section: Geophysical Research Lettersmentioning

confidence: 99%

Section: Geophysical Research Lettersmentioning

confidence: 99%

mentioning

confidence: 99%

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Fault roughness and strength heterogeneity control earthquake size and stress drop

Zielke

Gális

Martin

2017

Geophysical Research Letters

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“…Herein, scaling relationships that evaluate the source parameters (e.g., rupture size and spectral characteristics of the slip) as a function of moment magnitude are used for stochastic source generation. Such scaling relationships are obtained on the basis of 226 inverted source models in the SRCMOD database (Mai and Thingbaijam 2014).…”

Section: Scaling Relationships Of Earthquake Source Parameters and Stmentioning

confidence: 99%

Simulation-Based Probabilistic Tsunami Hazard Analysis: Empirical and Robust Hazard Predictions

Risi

Goda

2017

Pure Appl. Geophys.

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Abstract-Probabilistic tsunami hazard analysis (PTHA) is the prerequisite for rigorous risk assessment and thus for decisionmaking regarding risk mitigation strategies. This paper proposes a new simulation-based methodology for tsunami hazard assessment for a specific site of an engineering project along the coast, or, more broadly, for a wider tsunami-prone region. The methodology incorporates numerous uncertain parameters that are related to geophysical processes by adopting new scaling relationships for tsunamigenic seismic regions. Through the proposed methodology it is possible to obtain either a tsunami hazard curve for a single location, that is the representation of a tsunami intensity measure (such as inundation depth) versus its mean annual rate of occurrence, or tsunami hazard maps, representing the expected tsunami intensity measures within a geographical area, for a specific probability of occurrence in a given time window. In addition to the conventional tsunami hazard curve that is based on an empirical statistical representation of the simulation-based PTHA results, this study presents a robust tsunami hazard curve, which is based on a Bayesian fitting methodology. The robust approach allows a significant reduction of the number of simulations and, therefore, a reduction of the computational effort. Both methods produce a central estimate of the hazard as well as a confidence interval, facilitating the rigorous quantification of the hazard uncertainties.

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“…For the Tohoku earthquake, Table 2 lists 21 models obtained from the source model database (http://equake-rc. info/srcmod/; Mai & Thingbaijam 2014). These slip models were derived using different inversion techniques and different data sets, and they have different fault parametrizations (e.g.…”

Section: A S E S T U D I E Smentioning

confidence: 99%

Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake

Razafindrakoto¹,

Martin²,

Genton³

et al. 2015

Geophysical Journal International

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SRCMOD: An Online Database of Finite-Fault Rupture Models

Cited by 275 publications

References 71 publications

Fault roughness and strength heterogeneity control earthquake size and stress drop

Fault roughness and strength heterogeneity control earthquake size and stress drop

Simulation-Based Probabilistic Tsunami Hazard Analysis: Empirical and Robust Hazard Predictions

Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake

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