Search USGS⌕ Search

USGS · 70030256

Fault parameter constraints using relocated earthquakes: A validation of first-motion focal-mechanism data

Abstract

We estimate the strike and dip of three California fault segments (Calaveras, Sargent, and a portion of the San Andreas near San Jaun Bautistia) based on principle component analysis of accurately located microearthquakes. We compare these fault orientations with two different first-motion focal mechanism catalogs: the Northern California Earthquake Data Center ( NCEDC ) catalog, calculated using the FPFIT algorithm (Reasenberg and Oppenheimer, 1985), and a catalog created using the HASH algorithm that tests mechanism stability relative to seismic velocity model variations and earthquake location (Hardebeck and Shearer, 2002). We assume any disagreement (misfit >30° in strike, dip, or rake) indicates inaccurate focal mechanisms in the catalogs. With this assumption, we can quantify the parameters that identify the most optimally constrained focal mechanisms. For the NCEDC/FPFIT catalogs, we find that the best quantitative discriminator of quality focal mechanisms is the station distribution ratio ( STDR ) parameter, an indicator of how the stations are distributed about the focal sphere. Requiring STDR > 0.65 increases the acceptable mechanisms from 34%–37% to 63%–68%. This suggests stations should be uniformly distributed surrounding, rather than aligning, known fault traces. For the HASH catalogs, the fault plane uncertainty ( FPU ) parameter is the best discriminator, increasing the percent of acceptable mechanisms from 63%–78% to 81%–83% when FPU ≤ 35°. The overall higher percentage of acceptable mechanisms and the usefulness of the formal uncertainty in identifying quality mechanisms validate the HASH approach of testing for mechanism stability.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Debi Kilb, J.L. Hardebeck. 2006. Fault parameter constraints using relocated earthquakes: A validation of first-motion focal-mechanism data. https://doi.org/10.1785/0120040239

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↗