Simulation of earthquakes in the Upper Rhinegraben using empirical Green functions

Wössner, Jochen; Treml, M.; Wenzel, Friedemann

doi:10.1046/j.1365-246x.2002.01785.x

Cited by 13 publications

(15 citation statements)

References 27 publications

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“…The use of more than one EGF in order to reduce the possible effect of different location of the EGF and of the modelled event has been suggested, e.g. by Wössner et al (2002). Only those EGFs were combined whose correlation maximum exceeded 0.7 within a lag of ±2 sample intervals, otherwise the corresponding phase was not modelled.…”

Section: Modelling Of Multiple Eventsmentioning

confidence: 99%

“…The EGF method has also been used for modelling large earthquakes (e.g. Hutchings 1991; Wössner et al 2002); the author is, however, not aware of any similar study of small earthquakes. This could have resulted from the fact that some researches observed an apparent breakdown in self‐similarity of earthquakes of magnitude less than about 3 (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Modelling of multiple events using empirical Green’s functions: method, application to swarm earthquakes and implications for their rupture propagation

Fischer¹

2005

Geophysical Journal International

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S U M M A R YRecent studies of source-time functions (STFs) of small earthquakes have shown that some of the M L < 3 events may display complicated waveforms indicating multiple rupturing episodes. The STFs of such earthquakes consist of several pulses whose relative positions provide information on the mutual position of the subevents. I have used the waveform modelling method to analyse multiple events in order to disclose the geometry of the rupture. The P and S waveforms of multiple events (MEs) are modelled as the sum of waveforms of single subevents with different hypocentre coordinates and scalar moments. To construct the waveform of each single event composing the ME, the waveform of a co-located small event is used as an empirical Green's function (EGF). Assuming similar focal mechanisms of the subevents and of the EGF, the method seeks the coordinates and origin times of the subevents and their relative seismic moments. The non-linear problem is solved using the genetic algorithms method. Synthetic tests have shown that the method is capable of locating reliably up to three subevents with an accuracy better than 40 m. The method was applied to the records of the 2000 earthquake swarm in NW-Bohemia/Vogtland in Central Europe. By the EGF deconvolution, 54 MEs were identified in the magnitude range from 1.2 to 3.3, and 18 of them were successfully modelled as double or triple events with separate rupture positions. The separation of subsources reached 100 ms in time and 320 m in space. The relative positions of the subevents with respect to the orientation of the fault indicate that most of them occurred on a common fault plane. The space-time separation of the subevents corresponds to a speed of 3.0 ± 0.9 km s −1 , a value typical for rupture propagation of large earthquakes. The later subevents occur farther than the nominal rupture radius of the first subevent, and their mutual distance scales with magnitude. These observations suggest that the analysed MEs share a common fault surface and that their subevents represent individual rupture episodes. The angular distribution of the position vectors of later subevents indicates that many of them result from slip-parallel rupture growth, while some of the ruptures propagate upwards.

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Section: Modelling Of Multiple Eventsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling of multiple events using empirical Green’s functions: method, application to swarm earthquakes and implications for their rupture propagation

Fischer¹

2005

Geophysical Journal International

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“…They concluded that the method produces useful time histories. One other study by Wossner et al (2002) compared peak horizontal acceleration and response spectra in terms of spectral accelerations and peak horizontal accelerations with the attenuation laws proposed for Europe. Their results encouraged the application of the approach as a supplementary tool for site-specific ground motion prediction.…”

Section: Discussionmentioning

confidence: 99%

“…These models are mostly explained as quasi-dynamics models (Boatwright 1981), which depend on field observations, laboratory experiments, and numerical modeling. The methodology has been validated several times (Hutchings and Wu 1990;Hutchings 1991;Heuze et al 1994;Hutchings 1994;Foxall et al 1996;Hutchings and Jarpe 1996;Hutchings et al 1997Hutchings et al , 1998Hutchings et al , 2007Jarpe and Kasameyer 1996;Rosset et al 1998;Wossner et al 2002;Scognamiglio and Hutchings 2009;Nicknam and Eslamian 2011;Golara and Jazany 2013;Papoulia et al 2015).…”

Section: Simulation Methodologymentioning

confidence: 99%

Physically based probabilistic seismic hazard analysis using broadband ground motion simulation: a case study for the Prince Islands Fault, Marmara Sea

et al. 2016

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The main motivation for this study was the impending occurrence of a catastrophic earthquake along the Prince Island Fault (PIF) in the Marmara Sea and the disaster risk around the Marmara region, especially in Istanbul. This study provides the results of a physically based probabilistic seismic hazard analysis (PSHA) methodology, using broadband strong ground motion simulations, for sites within the Marmara region, Turkey, that may be vulnerable to possible large earthquakes throughout the PIF segments in the Marmara Sea. The methodology is called physically based because it depends on the physical processes of earthquake rupture and wave propagation to simulate earthquake ground motion time histories. We included the effects of all considerable-magnitude earthquakes. To generate the high-frequency (0.5-20 Hz) part of the broadband earthquake simulation, real, small-magnitude earthquakes recorded by a local seismic array were used as empirical Green's functions. For the frequencies below 0.5 Hz, the simulations were obtained by using synthetic Green's functions, which are synthetic seismograms calculated by an explicit 2D/3D elastic finite difference wave propagation routine. By using a range of rupture scenarios for all considerablemagnitude earthquakes throughout the PIF segments, we produced a hazard calculation for frequencies of 0.1-20 Hz. The physically based PSHA used here followed the same procedure as conventional PSHA, except that conventional PSHA utilizes point sources or a series of point sources to represent earthquakes, and this approach utilizes the full rupture of earthquakes along faults. Furthermore, conventional PSHA predicts ground motion parameters by using empirical attenuation relationships, whereas this approach calculates synthetic seismograms for all magnitudes of earthquakes to obtain ground motion parameters. PSHA results were produced for 2, 10, and 50 % hazards for all sites studied in the Marmara region.

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“…Additionally, according to Wossner et al (2002), the number of EGFs affects the amplitude of synthesized seismograms. They found that when frequencies are higher than the source corner frequency, these amplitudes tend to be higher if a single EGF is used to interpolate records over the fault.…”

Section: Methodsmentioning

confidence: 99%

A physically based strong ground-motion prediction methodology; application to PSHA and the 1999 Athens earthquake

Hutchings¹,

Ioannidou²,

Foxall³

et al. 2007

Geophysical Journal International

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S U M M A R YWe present a physically based methodology to predict the range of ground-motion hazard for earthquakes along specific faults or within specific source volumes, and we demonstrate how to incorporate this methodology into probabilistic seismic hazard analyses (PSHA). By 'physically based,' we refer to ground-motion syntheses derived from physics and an understanding of the earthquake process. This approach replaces the aleatory uncertainty that current PSHA studies estimate by regression of empirical parameters with epistemic uncertainty that is expressed by the variability in the physical parameters of the earthquake rupture. Epistemic uncertainty can be reduced by further research. We modelled wave propagation with empirical Green's functions. We applied our methodology to the 1999 September 7 M w = 6.0 Athens earthquake for frequencies between 1 and 20 Hz. We developed constraints on rupture parameters based on prior knowledge of the earthquake rupture process and on sources within the region, and computed a sufficient number of scenario earthquakes to span the full variability of ground motion possible for a magnitude M w = 6.0 earthquake with our approach. We found that: (1) our distribution of synthesized ground motions spans what actually occurred and that the distribution is realistically narrow; (2) one of our source models generates records that match observed time histories well; (3) certain combinations of rupture parameters produced 'extreme,' but not unrealistic ground motions at some stations; (4) the best-fitting rupture models occur in the vicinity of 38.05 • N, 23.60 • W with a centre of rupture near a 12-km depth and have nearly unilateral rupture toward the areas of high damage, which is consistent with independent investigations. We synthesized ground motion in the areas of high damage where strong motion records were not recorded from this earthquake. We also developed a demonstration PSHA for a single magnitude earthquake and for a single source region near Athens. We assumed an average return period of 1000 yr for this magnitude earthquake and synthesized 500 earthquakes distributed throughout the source zone, thereby having simulated a sample catalogue of ground motion for a period of 500 000 yr. We then used the synthesized ground motions rather than traditional attenuation relations for the PSHA.In this paper, we present a physically based methodology to predict a range of ground motions at a particular site that may occur from a particular magnitude earthquake along a specific fault or within a specific source volume, and demonstrate a means to incorporate this into traditional probabilistic seismic hazard analyses (PSHA). The prediction methodology is based upon the work first presented by Hutchings (1991Hutchings ( , 1994 and further developed by . The physical model proposed by the previous studies has been further developed in this study and the methodology expanded to include PSHA. We apply the methodology to the M w = 6.0, 1999 Athens earthquake. The full methodology i...

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Simulation of earthquakes in the Upper Rhinegraben using empirical Green functions

Cited by 13 publications

References 27 publications

Modelling of multiple events using empirical Green’s functions: method, application to swarm earthquakes and implications for their rupture propagation

Modelling of multiple events using empirical Green’s functions: method, application to swarm earthquakes and implications for their rupture propagation

Physically based probabilistic seismic hazard analysis using broadband ground motion simulation: a case study for the Prince Islands Fault, Marmara Sea

A physically based strong ground-motion prediction methodology; application to PSHA and the 1999 Athens earthquake

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