Geology Reports⌕ Search

USGS · 70042494

Epistemic uncertainty in California-wide synthetic seismicity simulations

Also available from

Abstract

The generation of seismicity catalogs on synthetic fault networks holds the promise of providing key inputs into probabilistic seismic-hazard analysis, for example, the coefficient of variation, mean recurrence time as a function of magnitude, the probability of fault-to-fault ruptures, and conditional probabilities for foreshock–mainshock triggering. I employ a seismicity simulator that includes the following ingredients: static stress transfer, viscoelastic relaxation of the lower crust and mantle, and vertical stratification of elastic and viscoelastic material properties. A cascade mechanism combined with a simple Coulomb failure criterion is used to determine the initiation, propagation, and termination of synthetic ruptures. It is employed on a 3D fault network provided by Steve Ward (unpublished data, 2009) for the Southern California Earthquake Center (SCEC) Earthquake Simulators Group. This all-California fault network, initially consisting of 8000 patches, each of ∼12 square kilometers in size, has been rediscretized into Graphic patches, each of ∼1 square kilometer in size, in order to simulate the evolution of California seismicity and crustal stress at magnitude M∼5–8. Resulting synthetic seismicity catalogs spanning 30,000 yr and about one-half million events are evaluated with magnitude-frequency and magnitude-area statistics. For a priori choices of fault-slip rates and mean stress drops, I explore the sensitivity of various constructs on input parameters, particularly mantle viscosity. Slip maps obtained for the southern San Andreas fault show that the ability of segment boundaries to inhibit slip across the boundaries (e.g., to prevent multisegment ruptures) is systematically affected by mantle viscosity.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fred F. Pollitz. 2011-09-26. Epistemic uncertainty in California-wide synthetic seismicity simulations. https://doi.org/10.1785/0120100303

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Re-evaluation of shaking, dynamic strain, and the source of the 1886 Charleston, South Carolina, earthquake

As the largest historical event in the eastern United States, the 1886 Charleston, South Carolina, earthquake, plays a prominent role in our nation’s seismological and human history and an outsized role in our probabilistic ground‐motion hazard estimates, affecting building codes, insurance rates, and geophysical monitoring. Thus, constraining the characteristics of the 1886 earthquake source, as well as the nature of its shaking distribution and impacts to the extent possible, is essential. Given its vintage, however, societal, geological, and geophysical datasets are limited compared with those used in modern seismological analyses. Because of these limitations, some characteristics of the rupture model are fundamentally nonunique. Still, by re‐evaluating all available data, I can constrain several key aspects of this earthquake. I show that several interpretations in recent analyses are inconsistent regarding the inferred source; shaking; ground failure; and, particularly, railway impacts. Importantly, I have shown that although dynamic strain caused the ground failure that led to track deformation, without the intermediate liquefaction step, dynamic strain alone was unlikely to be the source of rail deformation, contrary to earlier studies. Had earlier pronouncements that dynamic strain is a real concern for bending railways held true, there would be serious ramifications for railway engineering as well as for other above‐ and below‐ground linear infrastructure.

South Carolina↗

ETAS-positive: Extracting unbiased epidemic-type aftershock models from incomplete earthquake catalogs

Earthquake catalogs are inherently incomplete, and short-term fluctuations in catalog completeness can strongly bias estimates of seismicity parameters. Here, we extend the positive statistics framework recently introduced for estimating Gutenberg–Richter a and b values to the Epidemic-Type Aftershock Sequence (ETAS) model. The approach focuses on complete magnitude–time intervals defined by pairs of earthquakes in which the second event is larger than the first. Comprehensive synthetic tests demonstrate that the proposed ETAS + method retrieves nearly unbiased parameter estimates even from highly incomplete catalogs, whereas parameters obtained using classical estimation approaches are strongly biased. Application to Southern California reveals a similar trend, with the productivity scaling parameter α approaching the b value, consistent with self-similar earthquake triggering within estimation uncertainties. Owing to its robustness against catalog incompleteness and computational efficiency, the ETAS + method provides a powerful new tool for seismicity analysis and earthquake forecasting.

California↗