USGS Science⌕ Search

USGS · 70180069

Reply to “Comment on ‘Near-surface location, geometry, and velocities of the Santa Monica fault zone, Los Angeles, California’ by R. D. Catchings, G. Gandhok, M. R. Goldman, D. Okaya, M. J. Rymer, and G. W. Bawden” by T. L. Pratt and J. F. Dolan

Abstract

In a comment on our 2008 paper (Catchings, Gandhok, et al. , 2008) on the Santa Monica fault in Los Angeles, California, Pratt and Dolan (2010) (herein referred to as P&D) cite numerous objections to our work, inferring that our study is flawed. However, as shown in our reply, their objections contradict their own published works, published works of others, and proven seismic methodologies. Rather than responding to each repeated invalid objection, we address their objections by topic in the subsequent sections. In Catchings, Gandhok, et al. (2008), we presented high-resolution seismic-reflection images that showed two near-surface faults in the upper 50 m beneath the grounds of the Wadsworth Veterans Administration Hospital (WVAH). Although P&D suggest we effectively duplicated their seismic acquisition, our survey was not a duplication of their efforts. Rather, we conducted a seismic-imaging survey over a similar profile as Pratt et al. (1998) but used a different data acquisition system and different data processing methods to evaluate methods of seismically imaging blind faults in the wake of the 17 January 1994 M 6.7 Northridge earthquake. We used an acquisition method that provides both tomographic seismic velocities and reflection images. Our combined-data approach allowed for shallower imaging (∼2.5 m minimum) than the ∼20-m minimum of Pratt et al. (1998), clearer images of the fault zone, and more accurate depth determinations (rather than time images). In processing the reflection images, we used prestack depth migration, which is generally accepted as the only proper imaging method for imaging subsurface structures with strong lateral velocity variations (Versteeg, 1993), a condition shown to exist at the WVAH site. We correlated our reflection images with refraction tomography images, borehole lithology, and velocity data, Interferometric Synthetic Aperture Radar images, and changes in groundwater depths. Except for some minor differences, our seismic-reflection images coincide with previously published seismic-reflection images by Dolan and Pratt (1997) and Pratt et al. (1998), and a paleoseismic study by Dolan et al. (2000). Principal differences among our interpretations and those of Pratt et al. (1998) relate to the upper 20 m and the south side of the fault, which Pratt et al. (1998) did not clearly image. In contrast, our seismic images included structures on both sides of the fault zone from about 2.5 m depth to about 100 m depth at WVAH, allowing us to interpret more details.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 34.00073124300159° to 34.09218887374251° latitude; -118.54694366455077° to -118.37322235107422° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rufus D. Catchings, Michael J. Rymer, Mark R. Goldman, Gerald W. Bawden. 2010-09-20. Reply to “Comment on ‘Near-surface location, geometry, and velocities of the Santa Monica fault zone, Los Angeles, California’ by R. D. Catchings, G. Gandhok, M. R. Goldman, D. Okaya, M. J. Rymer, and G. W. Bawden” by T. L. Pratt and J. F. Dolan. https://doi.org/10.1785/0120090335

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↗