Spatial Evaluation and Verification of Earthquake Simulators

Wilson, John Max; Yoder, Mark R.; Rundle, John B.; Turcotte, Donald L.; Schultz, Kasey W.

doi:10.1007/s00024-016-1385-x

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…In agreement with Wilson et al (2017), we may conclude that the size and the quality of the historical seismicity observed in the study area are too limited for achieving a robust comparison with the simulations.…”

Section: Magnitude Distributionsupporting

confidence: 82%

“…Recall that the magnitude distribution of the earthquakes in the synthetic catalog is not assigned. It is a consequence of the self-organized physical process of the simulator mode and can be changed by the choice of the free parameters S-R and A-R. As mentioned by Wilson et al (2017), these simulation parameters are adjusted so that real earthquake catalogs are matched by synthetic catalogs in their scaling properties. For an analysis of the role of the S-R and A-R parameters in our simulation algorithm, see Console et al (2017).…”

Section: Algorithm Of the Simulator Codementioning

confidence: 99%

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Seismic hazard in southern Calabria (Italy) based on the analysis of a synthetic earthquake catalog

et al. 2018

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The application of a newly developed physics-based earthquake simulator to the active faults inferred by aeromagnetism in southern Calabria has produced a synthetic catalog lasting 100 ky including more than 18,000 earthquakes of magnitude C 4.0. This catalog exhibits temporal, spatial and magnitude features, which resemble those of the observed seismicity. As an example of the potential use of synthetic catalogs, a map of the peak ground acceleration (PGA) for a given exceedance probability on the territory under investigation has been produced by means of a simple attenuation law applied to all the events reported in the synthetic catalog. This map was compared with the existing hazard map that is presently used in the national seismic building regulations. The comparison supports a strong similarity of our results with the values given in the present Italian seismic building code, despite the latter being based on a different methodology. The same similarity cannot be recognized for the comparison of our present study with the results obtained from a previous study based on our same methodology but with a different geological model.

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Section: Magnitude Distributionsupporting

confidence: 82%

Section: Algorithm Of the Simulator Codementioning

confidence: 99%

Seismic hazard in southern Calabria (Italy) based on the analysis of a synthetic earthquake catalog

et al. 2018

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“…We assigned the global frictional parameters of the fault model based on the best‐fit results of these studies. Multiple simulations were carried out in order to tune the frictional parameters to match observed earthquake magnitude‐rupture area scaling relations (Leonard, 2010; Wells & Coppersmith, 1994), a procedure followed by numerous modeling studies before (e.g., Console, Vannoli, & Carluccio, 2018; Shaw et al., 2018; Wilson et al., 2018). It is an iterative process and the aim is to generate a frequency distribution of moderate‐sized events similar to the behavior of instrumental seismicity in the Eastern Betic region, with a Gutenberg‐Richter b‐value close to 1.0 ± 0.1 (García‐Mayordomo, 2005; IGN‐UPM, 2013; Villamor, 2002).…”

Section: Methodsmentioning

confidence: 99%

Physics‐Based Earthquake Simulations in Slow‐Moving Faults: A Case Study From the Eastern Betic Shear Zone (SE Iberian Peninsula)

et al. 2021

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Earthquake hazard forecasting often has to deal with the scarcity of seismicity data, the complexity of fault segmentation, the uncertainties derived from the characterization of seismogenic sources, the dynamics of earthquake rupture and the recurrence model used. Instrumental earthquake recordings are available only since about 1900 and they are not reliable until several decades later. There are a few regions with representative historical data of large earthquakes for more than 2000 years in Italy (Boschi, 2000), Japan (Ishibashi, 2004), and China (Liu et al., 2011) that allow acquisition of reliable major earthquake magnitudes and recurrence statistics. In regions with low to moderate seismicity, such as some zones of the western Mediterranean or intracontinental areas, earthquake hazard estimation is especially challenging (see e.g., Estay et al., 2016;Gamage & Venkatesan, 2019;Perea & Atakan, 2007). Most of the large, and consequently damaging earthquakes, have recurrence times on the order of hundreds or thousands of years. Since historical catalogs are often scarce and imprecise, the paleoseismic record provides valuable data about rare but devastating major events and long-term recurrence times, but these data usually have large uncertainties (McCalpin, 2009). Often, the slow fault systems, besides generating low seismicity in terms of frequency, show little geomorphological expression. This makes it difficult to define the segmentation of fault traces and the parameters relating to their 3D geometry and their kinematics. Fault system geometry also plays an important role in the stress interactions that control the earthquake ruptures and therefore magnitude and recurrence statistics (e.g.

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Earthquake Simulators Development and Application

Console¹,

Carluccio

2021

Statistical Methods and Modeling of Seismogenesis

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Spatial Evaluation and Verification of Earthquake Simulators

Cited by 6 publications

References 36 publications

Seismic hazard in southern Calabria (Italy) based on the analysis of a synthetic earthquake catalog

Seismic hazard in southern Calabria (Italy) based on the analysis of a synthetic earthquake catalog

Physics‐Based Earthquake Simulations in Slow‐Moving Faults: A Case Study From the Eastern Betic Shear Zone (SE Iberian Peninsula)

Earthquake Simulators Development and Application

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