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Published September 2012 | metadata_only
Book Section - Chapter

A Recursive Division Stochastic Strike-Slip Seismic Source Algorithm Using Insights from Laboratory Earthquakes


There are a sparse number of credible source models available from past earthquakes and a stochastic source model generation algorithm thus becomes necessary for robust risk quantification using scenario earthquakes. We present an algorithm that combines the physics of fault rupture as imaged in laboratory earthquakes with stress estimates on the fault constrained by field observations to generate probability distributions of rise-time and rupture-speed for strike-slip earthquakes. The algorithm is validated through a statistical comparison of peak ground velocity at 636 sites in Southern California from synthetic ground motion histories simulated for 10 rupture scenarios using a stochastically generated source model against that generated using a kinematic source model from a finite source inversion. This model, selected from a set of 5 stochastically generated source models, produces ground shaking intensities in Southern California with a median that is closest to the median intensity of shaking from all 5 source models (and 10 rupture scenarios per model).

Additional Information

This work is funded in part by NSF: CMMI Award No. 0926962. We thank Thomas Heaton (Caltech), Jean Paul Ampuero (Caltech), Dimitri Komatitsch (University of Pau, France), Martin Mai (KAUST), Rob Graves (USGS), and Chen Ji (UCSB) for offering valuable insights into various aspects of source physics and seismic wave propagation.

Additional details

August 19, 2023
August 19, 2023