Search USGS⌕ Search

USGS · 70186624

Triggering of the Ms = 5.4 Little Skull Mountain, Nevada, earthquake with dynamic strains

Abstract

We have developed an approach to test the viability of dynamic strains as a triggering mechanism by quantifying the dynamic strain tensor at seismogenic depths. We focus on the dynamic strains at the hypocenter of the M s = 5.4 Little Skull Mountain ( LSM ), Nevada, earthquake. This event is noteworthy because it is the largest earthquake demonstrably triggered at remote distances (∼280 km) by the M s = 7.4 Landers, California, earthquake and because of its ambiguous association with magmatic activity. Our analysis shows that, if dynamic strains initiate remote triggering, the orientation and modes of faulting most favorable for being triggered by a given strain transient change with depth. The geometry of the most probable LSM fault plane was favorably oriented with respect to the geometry of the dynamic strain tensor. We estimate that the magnitude of the peak dynamic strains at the hypocentral depth of the LSM earthquake were ∼4 μstrain (∼.2 MPa) which are ∼50% smaller than those estimated from velocity seismograms recorded at the surface. We suggest that these strains are too small to cause Mohr-Coulomb style failure unless the fault was prestrained to near failure levels, the fault was exceptionally weak, and/or the dynamic strains trigger other processes that lead to failure.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 36.7071096190553° to 36.83416633494588° latitude; -116.26116425515113° to -116.07920319558086° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Joan Gomberg, Paul Bodin. 1994. Triggering of the Ms = 5.4 Little Skull Mountain, Nevada, earthquake with dynamic strains. https://doi.org/10.1785/bssa0840030844

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↗