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| Titel |
Recurrent large earthquakes in a fault region: What can be inferred from small and intermediate events? |
| VerfasserIn |
G. Zöller, S. Hainzl, M. Holschneider |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250026906
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| Zusammenfassung |
| We present a renewal model for the recurrence of large earthquakes in a fault zone consisting
of a major fault and surrounding smaller faults with Gutenberg-Richter type seismicity
represented by seismic moment release drawn from a truncated power-law distribution. The
recurrence times of characteristic earthquakes for the major fault are explored. It is
continuously loaded (plate motion) and undergoes positive and negative fluctuations due to
adjacent smaller faults, with a large number Neq of such changes between two major
earthquakes. Since the distribution has a finite variance, in the limit Neq -- the central
limit theorem implies that the recurrence times follow a Brownian passage-time (BPT)
distribution. This allows to calculate individual recurrence time distributions for
specific fault zones without tuning free parameters: the mean recurrence time can
be estimated from geological or paleoseismic data, and the standard deviation is
determined from the frequency-size distribution, namely the Richter b value, of an
earthquake catalog. The approach is demonstrated for the Parkfield segment of the San
Andreas fault in California as well as for a long simulation of a numerical fault
model. Assuming power-law distributed earthquake magnitudes up to the size of
the recurrent Parkfield event (M = 6), we find a coefficient of variation that is
higher than the value obtained by a direct fit of the BPT distribution to seven large
earthquakes. Finally we show that uncertainties in the earthquake magnitudes, e.g.
from magnitude grouping, can cause a significant bias in the results. A method to
correct for the bias as well as a Baysian technique to account for evolving data are
provided. |
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