Source parameters and crustal Q for four earthquakes in South Carolina

Joe B. Fletcher

doi:10.1785/gssrl.66.4.44

Home/Archive/USGS

USGS · 70018833

Source parameters and crustal Q for four earthquakes in South Carolina

Joe B. Fletcher

View original source ↗Export metadata ↓

Abstract

Two three-component seismometers (one surface and one borehole) were re-installed on the Savannah River Site (SRS), South Carolina in July 1992 to determine attenuation in the Coastal Plain sediment wedge and source parameters of local earthquakes. Four earthquakes M ∼ 1.8 to 3.6 were recorded during the next 6 months. The largest event was located near Summerville within the meizoseismal area for the 1886 Charleston earthquake. Two shocks were located 50 km to the east near Neeses, and one was located 20 km north of the SRS near Aiken. Although source parameters have been determined from strong motion data and short-period regional networks for east coast earthquakes, such as the Saguenay, Nahanni, and Mt. Laurier earthquakes (e.g., Atkinson, 1993 ), these are some of the first source parameters determined from broad-band digital recorders. Seismograms for the Summerville event are also available from Chapel Hill, North Carolina and Blacksburg, Virginia, providing estimates of t * beyond 200 km. Here we determine source parameters such as moment, stress drop, and the attenuation parameter t * using a non-linear least-squares algorithm. We do not correct for site response because the deepest borehole is not below the Coastal Plain sediments (about 300m thick at this site) and because only one station is available for most of the data. Values of t* are marginally higher from seismograms recorded at the surface when compared to records from the 91m depth borehole seismograph. A value of 170-200 bars was determined for the Brune stress drop of the Summerville event using the borehole data, which is high compared to a value of 50 bars usually specified for modeling strong motion in western North America, but similar to other estimates for eastern North America. A higher stress drop leads to a higher seismic risk because peak acceleration is approximately proportional to stress drop. Moreover, mid- to upper-crustal Qs are in the range of 2,000 to 3,000, which would permit the propagation of high frequency seismic waves. A comparison of the surface records from the SRS with a record from the USGS dense array at Parkfield, CA for an event at about the same distance range and moment as the Summerville event-SRS case shows that the peak acceleration of the Summerville event is 16 times higher than that for the event from California (stress drop of 21 bars).

Explore related subjects

Seismological Research Letters Article

Source-reported bounding extent: 32.0346° to 35.215402° latitude; -83.353238° to -78.541087° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Joe B. Fletcher. 1995. Source parameters and crustal Q for four earthquakes in South Carolina. https://doi.org/10.1785/gssrl.66.4.44

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

KEEP EXPLORING

Related USGS reports

USGS2026

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↗

USGS2026

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↗

USGS2026

Global seasonal microseism intensity and hemispheric asymmetry

Earth’s microseism wavefield dominates seismic background levels at periods between approximately 4 and 20 s, and reflects periodic and secular variations in ocean swell energy. Ocean wave energy couples to the seismic wavefield via distinct primary microseism and secondary microseism (PM and SM) source mechanisms, which are excited by basal swell tractions and seafloor pressure variations due to crossing seas, respectively. This study examines annual amplitude variations for the globally dominant PM (14–20 s) and SM (4–10 s) period bands. Annual harmonic variations are represented by four‐term Fourier series fits to vertical‐component seasonally smoothed acceleration time series from 73 stations in the Global Seismographic and GEOSCOPE networks with over 20 yr of recording and at least 75% data completeness. These annual periodic functions fit between 14%–95% (PM) and 22%–97% (SM) of signal variance. Station annual peak‐to‐peak variations range between 1.2–14.3 dB (PM) and 1.5–20.6 dB (SM). An asymmetry in microseism features exists between the Northern (NH) and Southern (SH) Hemispheres. High‐latitude NH stations show highly correlated PM and SM annual amplitude variations. This character dominates the wider extratropical NH but diminishes at tropical latitudes, and widespread relative PM–SM decorrelation is observed in the SH. These hemispheric characteristics reflect systematic differences in both extratropical storm activity and ocean wave state. Greater annual variation and seasonal predictability in the NH reflect the influence of the large continental landmasses that enhance both storm intensity seasonality and SM‐generating coastal wave reflection. Notable clusters of low PM–SM correlation stations are also observed in continental Antarctica due to seasonal sea ice influences, and in East Asia, reflecting unusual PM and SM source responses to South Asian monsoonal and tropical cyclone ocean wave influences.

Seismological Research Letters↗