Deformation along the San Andreas Fault south of the coseismic and postseismic October 18, 1989, Loma Prieta ML 7.1 earthquake rupture

2000 ◽  
Author(s):  
Robert J. Mueller ◽  
M.J. Johnston
1990 ◽  
Vol 17 (9) ◽  
pp. 1445-1448 ◽  
Author(s):  
J. Behr ◽  
R. Bilham ◽  
P. Bodin ◽  
R. O. Burfoid ◽  
R. Bürgmann

2011 ◽  
Vol 27 (2) ◽  
pp. 293-313 ◽  
Author(s):  
Rui Chen ◽  
Mark D. Petersen

We apply a probabilistic method to develop fault displacement hazard maps and profiles for the southern San Andreas Fault. Two slip models are applied: (1) scenario slip, defined by the ShakeOut rupture model, and (2) empirical slip, calculated using regression equations relating global slip to earthquake magnitude and distance along the fault. The hazard is assessed using a range of magnitudes defined by the Uniform California Earthquake Rupture Forecast and the ShakeOut. For hazard mapping we develop a methodology to partition displacement among multiple fault branches based on geological observations. Estimated displacement hazard extends a few kilometers wide in areas of multiple mapped fault branches and poor mapping accuracy. Scenario and empirical displacement hazard differs by a factor of two or three, particularly along the southernmost section of the San Andreas Fault. We recommend the empirical slip model with site-specific geological data to constrain uncertainties for engineering applications.


Author(s):  
Morgan T. Page

ABSTRACT Did the third Uniform California Earthquake Rupture Forecast (UCERF3) go overboard with multifault ruptures? Schwartz (2018) argues that there are too many long ruptures in the model. Here, I address his concern and show that the UCERF3 rupture-length distribution matches empirical data. I also present evidence that, if anything, the UCERF3 model could be improved by adding more connectivity to the fault system. Adding more connectivity would improve model misfits with data, particularly with paleoseismic data on the southern San Andreas fault; make the model less characteristic on the faults; potentially improve aftershock forecasts; and reduce model sensitivity to inadequacies and unknowns in the modeled fault system.


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