Source Scaling Properties from Finite-Fault-Rupture Models

2000 ◽  
Vol 90 (3) ◽  
pp. 604-615 ◽  
Author(s):  
P. M. Mai
2019 ◽  
Vol 109 (6) ◽  
pp. 2582-2593 ◽  
Author(s):  
Diego Melgar ◽  
Gavin P. Hayes

Abstract Here, we revisit the issue of slip distributions modeled as spatially random fields. For each earthquake in the U.S. Geological Survey’s database of finite‐fault models (M 7–9), we measure the parameters of a best‐fitting von Karman autocorrelation function. We explore the source scaling properties of the correlation lengths and the Hurst exponent. We find that the behavior previously observed for more moderate events generally still holds at higher magnitudes and larger source dimensions. However, we find slightly larger correlation lengths and a lower mean Hurst exponent. The most important effect of these differences is that using our preferred parameters to generate stochastic slip models will lead to slightly larger asperities and more small‐scale structure in between them. We also define a new scaling relationship for the standard deviation of slip necessary for a full description of a spatially random field. Here, we also explore the patterns of where hypocenters are located within a fault. We find that strongly unilateral ruptures are comparatively rare and propose several probability density functions that can be used to randomly assign hypocentral positions when creating stochastic sources. When compared to simply randomly assigning the hypocenter anywhere on the fault, this leads to overall shorter duration sources.


2012 ◽  
Vol 191 (2) ◽  
pp. 803-812 ◽  
Author(s):  
Maren Böse ◽  
Thomas H. Heaton ◽  
Egill Hauksson

1996 ◽  
Vol 86 (1A) ◽  
pp. 79-92 ◽  
Author(s):  
A. M. Rogers ◽  
D. M. Perkins

Abstract A finite-fault statistical model of the earthquake source is used to confirm observed magnitude and distance saturation scaling in a large peak-acceleration data set. This model allows us to determine the form of peak-acceleration attenuation curves without a priori assumptions about their shape or scaling properties. The source is composed of patches having uniform size and statistical properties. The primary source parameters are the patch peak-acceleration distribution mean, the distribution standard deviation, the patch size, and patch-rupture duration. Although our model assumes no scaling of peak acceleration with magnitude at the patch, the peak-acceleration attenuation curves, nevertheless, strongly scale with magnitude (dap/dM) ≠ 0, and the scaling is distance dependent (dap/dM) ∝ f(r). The distance-dependent magnitude scaling arises from two principal sources in the model. For a propagating rupture, loci exist on the fault from which radiated energy arrives at a particular station at the same time. These loci are referred to as isochrones. As fault size increases, the length of the isochrones and, hence, the number of additive pulses increase. Thus, peak accelerations increase with magnitude. The second effect, which arises in a completely different manner, is due to extreme-value properties. That is, as the fault size increases, the number of patches on the fault and the number of peak values at the station increase. Because these attenuated pulses are produced by a statistical distribution at the patch, the largest value will depend on the total number of peak values available on the seismogram. We refer to this result as the extremal effect, because it is predicted by the theory of extreme values. Both the extremal and isochrone effects are moderated by attenuation and distance to the fault, leading to magnitude- and distance-dependent peak-acceleration scaling. Remarkably, the scaling produced by both effects is very similar, although the underlying mechanisms are completely different. Because this model approximates data characteristics we have observed in an earlier study, we adjusted the parameters of the model to fit a set of smoothed peak accelerations from earthquakes worldwide. These data have not been preselected for particular magnitude or distance ranges and contain earthquake records for magnitudes ranging from about M 3 to M 8 and distance ranging from a few kilometers to about 400 km. In fitting the data, we use a trial-and-error procedure, varying the mean and standard deviation of the patch peak-acceleration distribution, the patch size, and the pulse duration. The model explicitly includes triggering bias, and the triggering threshold is also a model parameter. The data can be approximated equally well by a model that includes the isochrone effect alone, the extremal effect alone, or both effects. Inclusion of both effects is likely to be closest to reality, but because both effects produce similar results, it is not possible to determine the relative contribution of each one. In any case, the model approximates the complex features of the observed data, including a decrease in magnitude scaling with increasing magnitude at short distances and increase in magnitude scaling with magnitude at large distances.


2015 ◽  
Vol 86 (6) ◽  
pp. 1692-1704 ◽  
Author(s):  
M. Böse ◽  
C. Felizardo ◽  
T. H. Heaton
Keyword(s):  

2011 ◽  
Vol 63 (7) ◽  
pp. 797-801 ◽  
Author(s):  
Thorne Lay ◽  
Yoshiki Yamazaki ◽  
Charles J. Ammon ◽  
Kwok Fai Cheung ◽  
Hiroo Kanamori

2021 ◽  
Author(s):  
Claudia Abril ◽  
Martin Mai ◽  
Benedikt Halldórsson ◽  
Bo Li ◽  
Alice Gabriel ◽  
...  

<p>The Tjörnes Fracture Zone (TFZ) in North Iceland is the largest and most complex zone of transform faulting in Iceland, formed due to a ridge-jump between two spreading centers of the Mid-Atlantic Ridge, the Northern Volcanic Zone and Kolbeinsey Ridge in North Iceland. Strong earthquakes (Ms>6) have repeatedly occurred in the TFZ and affected the North Icelandic population. In particular the large historical earthquakes of 1755 (Ms 7.0) and 1872 (doublet, Ms 6.5), have been associated with the Húsavı́k-Flatey Fault (HFF), which is the largest linear strike-slip transform fault in the TFZ, and in Iceland. We simulate fault rupture on the HFF and the corresponding near-fault ground motion for several potential earthquake scenarios, including scenario events that replicate the large 1755 and 1872 events. Such simulations are relevant for the town of Húsavı́k in particular, as it is located on top of the HFF and is therefore subject to the highest seismic hazard in the country. Due to the mostly offshore location of the HFF, its precise geometry has only recently been studied in more detail. We compile updated seismological and geophysical information in the area, such as a recently derived three-dimensional velocity model for P and S waves. Seismicity relocations using this velocity model, together with bathymetric and geodetic data, provide detailed information to constrain the fault geometry. In addition, we use this 3D velocity model to simulate seismic wave propagation. For this purpose, we generate a variety of kinematic earthquake-rupture scenarios, and apply a 3D finite-difference method (SORD) to propagate the radiated seismic waves through Earth structure. Slip distributions for the different scenarios are computed using a von Karman autocorrelation function whose parameters are calibrated with slip distributions available for a few recent Icelandic earthquakes. Simulated scenarios provide synthetic ground motion and time histories and estimates of peak ground motion parameters (PGA and PGV) at low frequencies (<2 Hz) for Húsavík and other main towns in North Iceland along with maps of ground shaking for the entire region [130 km x 110 km]. Ground motion estimates are compared with those provided by empirical ground motion models calibrated to Icelandic earthquakes and dynamic fault-rupture simulations for the HFF. Directivity effects towards or away from the coastal areas are analyzed to estimate the expected range of shaking. Thick sedimentary deposits (up to ∼4 km thick) located offshore on top of the HFF (reported by seismic, gravity anomaly and tomographic studies) may affect the effective depth of the fault's top boundary and the surface rupture potential. The results of this study showcase the extent of expected ground motions from significant and likely earthquake scenarios on the HFF. Finite fault earthquake simulations complement the currently available information on seismic hazard for North Iceland, and are a first step towards a systematic and large-scale earthquake scenario database on the HFF, and for the entire fault system of the TFZ, that will enable comprehensive and physics-based hazard assessment in the region.</p>


2020 ◽  
Vol 110 (2) ◽  
pp. 920-936 ◽  
Author(s):  
Jiawei Li ◽  
Maren Böse ◽  
Max Wyss ◽  
David J. Wald ◽  
Alexandra Hutchison ◽  
...  

ABSTRACT Large earthquakes, such as Wenchuan in 2008, Mw 7.9, Sichuan, China, provide an opportunity for earthquake early warning (EEW), as many heavily shaken areas are far (∼50  km) from the epicenter and warning times could be sufficient (≥5  s) to take preventive action. On the other hand, earthquakes with magnitudes larger than ∼M 6.5 are challenging for EEW because source dimensions need to be defined to adequately estimate shaking. Finite-fault rupture detector (FinDer) is an approach to identify fault rupture extents from real-time seismic records. In this study, we playback local and regional onscale strong-motion waveforms of the 2008 Mw 7.9 Wenchuan, 2013 Mw 6.6 Lushan, and 2017 Mw 6.5 Jiuzhaigou earthquakes to study the performance of FinDer for the current layout of the China Strong Motion Network. Overall, the FinDer line-source models agree well with the observed spatial distribution of aftershocks and models determined from waveform inversion. However, because FinDer models are constructed to characterize seismic ground motions (as needed for EEW) instead of source parameters, the rupture length can be overestimated for events radiating high levels of high-frequency motions. If the strong-motion data used had been available in real time, 50%–80% of sites experiencing intensity modified Mercalli intensity IV–VII (light to very strong) and 30% experiencing VIII–IX (severe to violent) could have been issued a warning with 10 and 5 s, respectively, before the arrival of the S wave. We also show that loss estimates based on the FinDer line source are more accurate compared to point-source models. For the Wenchuan earthquake, for example, they predict a four to six times larger number of fatalities and injured, which is consistent with official reports. These losses could be provided 1/2∼3  hr faster than if they were based on more complex inversion rupture models.


2014 ◽  
Vol 85 (6) ◽  
pp. 1348-1357 ◽  
Author(s):  
P. M. Mai ◽  
K. K. S. Thingbaijam

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