Geology Reports⌕ Search

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

Time for an updated macroseismic scale

Macroseismology plays a crucial role in earthquake hazard and risk analyses, linking past earthquake occurrences and impacts with those of the present and future. The popularity of internet-based community contributions and the usefulness of intensities for communicating seismic hazards, early warning, and impacts to the public have all bolstered the use of macroseismology beyond its traditional utility in characterizing sources and shaking from historical and modern earthquakes (Wald et al., 2023). Nevertheless, many modern approaches for collecting building damage data and assigning macroseismic intensities suffer limitations. Many countries do not or no longer routinely collect such data, and even after significant and even catastrophic earthquakes, building damage data are often not collected or shared systematically, nor are field-based macroseismic intensities professionally assigned. Additionally, the United States (U.S.), Canada, and other nations still use variations of the Modified Mercalli Intensity (MMI) scale (Wood and Neumann, 1931) for assigning macroseismic intensities. At nearly 100 years old, the MMI scale predates most modern building types. As a result, the scale is silent about and blind to building damage that now matters to most domestic occupants. It says nothing about single- or multi-unit wood-frame buildings, the predominant type of residential structure in the US and Canada, whose damage is a particularly important indicator of shaking intensity, nor about the collapse or safety of modern building types. Importantly, the dependence on the U.S. Geological Survey’s “Did You Feel It?” (DYFI) for domestic intensity data collection limits their accuracy type at higher, damaging intensity levels, where attention to building type is requisite. The MMI and some of its widely used variants are often poorly documented; there is no official version, nor is it even clear which version of the scale was employed in many studies (Musson, 2002). The MMI scale is consistent with—but is more limited than—the 1998 European Macroseismic Scale (EMS-98, Grünthal, 1998). The new International Macroseismic Scale of 2025 (IMS-25; Grünthal et al., 2025) builds on EMS-98—a well-documented, modern scale already widely used in Europe and well beyond. IMS-25 further expands EMS-98 internationally by enhancing the EMS-98 vulnerability table and damage grade collections to include more worldwide building types and their evolving design codes. Because the IMS requires well-defined vulnerability classes and damage grades specific to various structural types, its worldwide adoption will help unify post-event data collection on building damage. Similarly, the IMS requires statistical analyses of damage levels for specific structural types, ensuring that building damage sampling is sufficient for other important engineering analyses, such as the derivation of fragility functions, calibration of loss models, and the assessment of losses and damages after significant events

Seismological Research Letters↗

Intensity prediction equations for intraslab earthquakes in the Cascadia Subduction Zone

In the U.S. Pacific Northwest (PNW), intraslab earthquakes located within the subducting Juan de Fuca slab are responsible for most of the region’s moderate‐magnitude seismicity. Historically, these earthquakes have caused significant damage, such as the 2001 M 6.8 Nisqually, 1965 M 6.5 Seattle, and 1949 M 6.8 Olympia events. Intensity prediction equations (IPEs) aim to relate source‐to‐site distance and earthquake magnitude to the resultant felt shaking intensity at a particular location, and help to estimate hazard from earthquakes. We find that a commonly used IPE developed by Atkinson et al. (2014) does not accurately describe shaking intensity from most intraslab events in the PNW, likely because it was developed using primarily crustal fault earthquakes. In this study, we develop two new IPEs that provide an improved fit to observed intensities from Cascadia subduction zone intraslab earthquakes. To develop our IPEs, we compute linear mixed‐effects regressions using community decimal intensity data from the U.S. Geological Survey’s ‘Did You Feel It?’ program from 36 intraslab events that occurred in British Columbia, Canada, Washington, Oregon, and northern California from 2000 to 2025. We also investigate the relationship between the new intraslab IPEs and select parameters related to near‐surface conditions and deeper geologic structure that may be related to ground‐motion intensities, but find no correlations. These new IPEs provide a better fit to observations of intraslab earthquakes in the PNW than Atkinson et al. (2014) , particularly within 300 km of the epicenter. They also provide a better fit to the 2018 M 7.1 Anchorage, Alaska, intraslab earthquake, suggesting that they may have broader applicability to global subduction zones.

California, Oregon, Washington↗

Amploc: A complete Python workflow for amplitude-based locations

Amplitude‐based locations are well suited for characterizing long‐duration seismic sources that may migrate with time, such as debris flows, avalanches, rockfall, and volcanic tremor. Although amplitude‐based location methods have existed for decades, their adoption in real‐time monitoring systems remains limited. We present a complete Python‐based workflow that includes station corrections, amplitude‐based location algorithms, and interactive review tools that are appropriate for real‐time use. The algorithms themselves are not new; however, Amploc integrates several previously published methods into a unified operational framework. The workflow also introduces a browser‐based graphical interface that allows users to review real‐time location results using formats familiar to many observatories. By integrating calibration, location algorithms, and visualization tools, Amploc lowers the barrier to operational use of amplitude‐based locations and improves characterization of phenomena that inform hazard assessments such as long‐period earthquakes, volcanic tremor, and debris flows.

British Columbia, Oregon, Washington↗