Bulletin of the Seismological Society of America; October 2005; v. 95; no. 5;
p. 1594-1603; DOI: 10.1785/0120030208
© 2005 Seismological Society of America
Viscoelasticity, Postseismic Slip, Fault Interactions, and the Recurrence of Large Earthquakes
Andrew J. Michael1
1 U.S. Geological Survey
MS
977
345 Middlefield Road
Menlo Park, California
94025
michael{at}usgs.gov
The Brownian Passage Time (BPT) model for earthquake recurrence is
modified to include transient deformation due to either viscoelasticity or deep
postseismic slip. Both of these processes act to increase the rate of loading on
the seismogenic fault for some time after a large event. To approximate these
effects, a decaying exponential term is added to the BPT
models uniform loading term. The resulting interevent time distributions
remain approximately lognormal, but the balance between the level of noise
(e.g., unknown fault interactions) and the coefficient of variability of the
interevent time distribution changes depending on the shape of the loading
function. For a given level of noise in the loading process, transient
deformation has the effect of increasing the coefficient of variability of
earthquake interevent times. Conversely, the level of noise needed to achieve a
given level of variability is reduced when transient deformation is included.
Using less noise would then increase the effect of known fault interactions
modeled as stress or strain steps because they would be larger with respect to
the noise. If we only seek to estimate the shape of the interevent time
distribution from observed earthquake occurrences, then the use of a transient
deformation model will not dramatically change the results of a probability
study because a similar shaped distribution can be achieved with either uniform
or transient loading functions. However, if the goal is to estimate earthquake
probabilities based on our increasing understanding of the seismogenic process,
including earthquake interactions, then including transient deformation is
important to obtain accurate results. For example, a loading curve based on the
1906 earthquake, paleoseismic observations of prior events, and observations of
recent deformation in the San Francisco Bay region produces a 40% greater
variability in earthquake recurrence than a uniform loading model with the same
noise level.
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