Eric M Thompson
Eric Thompson is a research geophysicist with the USGS in Golden. He joined the USGS in 2015 where he participates in research, development, and operations of many earthquake hazard products, including near-real-time earthquake hazard products.
Professional Experience
5/2015-Present: Research Geophysicist, USGS, Golden, Colorado.
4/2013-4/2015: Adjunct Professor, Geological Sciences, San Diego State University.
1/2014-3/2015: Lecturer, Department of Civil and Environmental Engineering, University of California, Los Angeles.
9/2010-9/2013: Research Assistant Professor, Civil and Environmental Engineering, Tufts University.
3/2009-8/2010: Postdoctoral Researcher/Lecturer, Civil and Environmental Engineering, Tufts University.
Education and Certifications
2009 Ph.D., Tufts University, Civil and Environmental Engineering.
2002 B.S., University of California at Santa Cruz, Earth Science.
Honors and Awards
2022: Superior Service Award for activities in the planning and development of ground motion processing software named gmprocess.
2019: FEMA Certificate of Appreciation for outstanding contributions in support of national level earthquake exercise.
2018: Western States Seismic Policy Council (WSSPC) Award for Excellence Use of Technology for developing the ShakeMap Scenario Suite.
Science and Products
An updated geospatial liquefaction model for global application
Integrating landslide and liquefaction hazard and loss estimates with existing USGS real-time earthquake information products
Characterizing the Kathmandu Valley sediment response through strong motion recordings of the 2015 Gorkha earthquake sequence
USGS approach to real-time estimation of earthquake-triggered ground failure - Results of 2015 workshop
Uncertainty in Vs30-based site response
Compilation of VS30 Data for the United States
Soil amplification with a strong impedance contrast: Boston, Massachusetts
Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks
Revisions to some parameters used in stochastic-method simulations of ground motion
Surface wave site characterization at 27 locations near Boston, Massachusetts, including 2 strong-motion stations
Path durations for use in the stochastic‐method simulation of ground motions
Predicting the spatial extent of liquefaction from geospatial and earthquake specific parameters
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
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An updated geospatial liquefaction model for global application
We present an updated geospatial approach to estimation of earthquake-induced liquefaction from globally available geospatial proxies. Our previous iteration of the geospatial liquefaction model was based on mapped liquefaction surface effects from four earthquakes in Christchurch, New Zealand, and Kobe, Japan, paired with geospatial explanatory variables including slope-derived VS30, compound topAuthorsJing Zhu, Laurie G. Baise, Eric M. ThompsonIntegrating landslide and liquefaction hazard and loss estimates with existing USGS real-time earthquake information products
The U.S. Geological Survey (USGS) has made significant progress toward the rapid estimation of shaking and shakingrelated losses through their Did You Feel It? (DYFI), ShakeMap, ShakeCast, and PAGER products. However, quantitative estimates of the extent and severity of secondary hazards (e.g., landsliding, liquefaction) are not currently included in scenarios and real-time post-earthquake productAuthorsKate E. Allstadt, Eric M. Thompson, Mike Hearne, M. Anna Nowicki Jessee, J. Zhu, David J. Wald, Hakan TanyasCharacterizing the Kathmandu Valley sediment response through strong motion recordings of the 2015 Gorkha earthquake sequence
We analyze strong motion records and high-rate GPS measurements of the M 7.8 Gorkha mainshock, M 7.3 Dolakha, and two moderate aftershock events recorded at four stations on the Kathmandu basin sediments, and one on rock-outcrop. Recordings on soil from all four events show systematic amplification relative to the rock site at multiple frequencies in the 0.1–2.5 Hz frequency range, and de-amplificAuthorsS. Rajaure, Domniki Asimaki, Eric M. Thompson, Susan E. Hough, Stacey Martin, J.P. Ampuero, M.R. Dhital, A Inbal, N Takai, M. Shigefuji, S Bijukchhen, M Ichiyanagi, T Sasatani, L PaudelUSGS approach to real-time estimation of earthquake-triggered ground failure - Results of 2015 workshop
The U.S. Geological Survey (USGS) Earthquake Hazards and Landslide Hazards Programs are developing plans to add quantitative hazard assessments of earthquake-triggered landsliding and liquefaction to existing real-time earthquake products (ShakeMap, ShakeCast, PAGER) using open and readily available methodologies and products. To date, prototype global statistical models have been developed and arAuthorsKate E. Allstadt, Eric M. Thompson, David J. Wald, Michael W. Hamburger, Jonathan W. Godt, Keith L. Knudsen, Randall W. Jibson, M. Anna Jessee, Jing Zhu, Michael Hearne, Laurie G. Baise, Hakan Tanyas, Kristin D. MaranoUncertainty in Vs30-based site response
Methods that account for site response range in complexity from simple linear categorical adjustment factors to sophisticated nonlinear constitutive models. Seismic‐hazard analysis usually relies on ground‐motion prediction equations (GMPEs); within this framework site response is modeled statistically with simplified site parameters that include the time‐averaged shear‐wave velocity to 30 m (VS30AuthorsEric M. Thompson, David J. WaldCompilation of VS30 Data for the United States
VS30, the time-averaged shear-wave velocity (VS) to a depth of 30 meters, is a key index adopted by the earthquake engineering community to account for seismic site conditions. VS30 is typically based on geophysical measurements of VS derived from invasive and noninvasive techniques at sites of interest. Owing to cost considerations, as well as logistical and environmental concerns, VS30 data areAuthorsAlan Yong, Eric M. Thompson, David J. Wald, Keith L. Knudsen, Jack K. Odum, William J. Stephenson, Scott HaefnerSoil amplification with a strong impedance contrast: Boston, Massachusetts
In this study, we evaluate the effect of strong sediment/bedrock impedance contrasts on soil amplification in Boston, Massachusetts, for typical sites along the Charles and Mystic Rivers. These sites can be characterized by artificial fill overlying marine sediments overlying glacial till and bedrock, where the depth to bedrock ranges from 20 to 80 m. The marine sediments generally consist of orgaAuthorsLaurie G. Baise, James Kaklamanos, Bradford M Berry, Eric M. ThompsonGeotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks
This article summarizes the geotechnical effects of the 25 April 2015 M 7.8 Gorkha, Nepal, earthquake and aftershocks, as documented by a reconnaissance team that undertook a broad engineering and scientific assessment of the damage and collected perishable data for future analysis. Brief descriptions are provided of ground shaking, surface fault rupture, landsliding, soil failure, and infrastructAuthorsRobb E. S. Moss, Eric M. Thompson, D Scott Kieffer, Binod Tiwari, Youssef M A Hashash, Indra Acharya, Basanta Adhikari, Domniki Asimaki, Kevin B. Clahan, Brian D. Collins, Sachindra Dahal, Randall W. Jibson, Diwakar Khadka, Amy Macdonald, Chris L M Madugo, H Benjamin Mason, Menzer Pehlivan, Deepak Rayamajhi, Sital UpretyRevisions to some parameters used in stochastic-method simulations of ground motion
The stochastic method of ground‐motion simulation specifies the amplitude spectrum as a function of magnitude (M) and distance (R). The manner in which the amplitude spectrum varies with M and R depends on physical‐based parameters that are often constrained by recorded motions for a particular region (e.g., stress parameter, geometrical spreading, quality factor, and crustal amplifications), whicAuthorsDavid Boore, Eric M. ThompsonSurface wave site characterization at 27 locations near Boston, Massachusetts, including 2 strong-motion stations
The geotechnical properties of the soils in and around Boston, Massachusetts, have been extensively studied. This is partly due to the importance of the Boston Blue Clay and the extent of landfill in the Boston area. Although New England is not a region that is typically associated with seismic hazards, there have been several historical earthquakes that have caused significant ground shaking (forAuthorsEric M. Thompson, Bradley A. Carkin, Laurie G. Baise, Robert E. KayenPath durations for use in the stochastic‐method simulation of ground motions
The stochastic method of ground‐motion simulation assumes that the energy in a target spectrum is spread over a duration DT. DT is generally decomposed into the duration due to source effects (DS) and to path effects (DP). For the most commonly used source, seismological theory directly relates DS to the source corner frequency, accounting for the magnitude scaling of DT. In contrast, DP is relateAuthorsDavid M. Boore, Eric M. ThompsonPredicting the spatial extent of liquefaction from geospatial and earthquake specific parameters
The spatially extensive damage from the 2010-2011 Christchurch, New Zealand earthquake events are a reminder of the need for liquefaction hazard maps for anticipating damage from future earthquakes. Liquefaction hazard mapping as traditionally relied on detailed geologic mapping and expensive site studies. These traditional techniques are difficult to apply globally for rapid response or loss estiAuthorsJing Zhu, Laurie G. Baise, Eric M. Thompson, David J. Wald, Keith L. KnudsenNon-USGS Publications**
Thompson, E.M., Baise, L.G., Tanaka, Y. and Kayen, R.E., 2012. A taxonomy of site response complexity. Soil Dynamics and Earthquake Engineering, 41, pp.32-43.Boore, D.M. and Thompson, E.M., 2012. Empirical improvements for estimating earthquake response spectra with random‐vibration theory. Bulletin of the Seismological Society of America, 102(2), pp.761-772.Kaklamanos, J., Bradley, B.A., Thompson, E.M. and Baise, L.G., 2013. Critical parameters affecting bias and variability in site‐response analyses using KiK‐net downhole array data. Bulletin of the Seismological Society of America, 103(3), pp.1733-1749.Kaklamanos, J., Baise, L.G., Thompson, E.M. and Dorfmann, L., 2015. Comparison of 1D linear, equivalent-linear, and nonlinear site response models at six KiK-net validation sites. Soil Dynamics and Earthquake Engineering, 69, pp.207-219.Moss, R.E., Thompson, E.M., Kieffer, D.S., Tiwari, B., Hashash, Y.M., Acharya, I., Adhikari, B.R., Asimaki, D., Clahan, K.B., Collins, B.D. and Dahal, S., 2015. Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks. Seismological Research Letters, 86(6), pp.1514-1523.Thompson, E.M., Baise, L.G. and Vogel, R.M., 2007. A global index earthquake approach to probabilistic assessment of extremes. Journal of Geophysical Research: Solid Earth, 112(B6).Zhu, J., Daley, D., Baise, L.G., Thompson, E.M., Wald, D.J. and Knudsen, K.L., 2015. A geospatial liquefaction model for rapid response and loss estimation. Earthquake Spectra, 31(3), pp.1813-1837.Thompson, E.M., Hewlett, J.B., Baise, L.G. and Vogel, R.M., 2011. The Gumbel hypothesis test for left censored observations using regional earthquake records as an example. Natural Hazards and Earth System Sciences, 11(1), pp.115-126.Baise, L.G., Lenz, J.A. and Thompson, E.M., 2008. Discussion of “Mapping liquefaction potential considering spatial correlations of CPT measurements” by Chia-Nan Liu and Chien-Hsun Chen. Journal of geotechnical and geoenvironmental engineering, 134(2), pp.262-263.**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
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