USGS ScienceSearch

USGS · 70210593

When source and path components trade off in ground-motion prediction equations

Abstract

Current research on ground‐motion models (also known as ground‐motion prediction equations [GMPEs]) and their uncertainties focus on the separate contributions of source, path, and site to both median values and their variability. Implicit here is the assumption that the event term, path term, and site term reflect only properties of the source, path, and site, respectively. Events with larger stress drop generate more high‐frequency energy, and thus more ground motion. Therefore, the correlation of high‐frequency (i.e., peak ground acceleration [PGA] or peak ground velocity [PGV]) event terms in GMPEs with stress drop is taken to be genuine. However, PGA and PGV ground‐motion observations of the 2014 M "> M 6.0 South Napa, California, earthquake clearly violate these assumptions. For this earthquake, high‐frequency ground‐motion residuals of recorded ground motion with respect to Next Generation Attenuation‐West2 Project (NGA‐West2) ground‐motion models show a dependence on distance, biasing the calculation of the event term by incorrectly mapping a regional attenuation effect into it. We examine the trade‐off between source and path effects for the South Napa earthquake and a well‐recorded California subset of the NGA‐West2 data. We fit near‐source (i.e., within 20 or 50 km) event terms and remaining differential geometrical spreading and anelastic attenuation terms in comparison to a simultaneous inversion for the source and path terms. This South Napa instance highlights one situation for which the high‐frequency event term can be interpreted as relative stress drop only when the distance dependence of the ground motions does not bias the residuals.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 38.17235306715556° to 38.33411604971082° latitude; -122.35336303710938° to -122.23526000976561° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Annemarie S. Baltay, Lauren S. Abrahams, Thomas C. Hanks. 2020-05-27. When source and path components trade off in ground-motion prediction equations. https://doi.org/10.1785/0220190379

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

KEEP EXPLORING

Related USGS reports

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters