Geology topics

Eric M. Thompson

Publications and source records attributed to Eric M. Thompson.

At least 73 records · Page 4Linked to original sources

USGS2020

Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard forecasts: Hawaii tectonic earthquakes and volcanic eruptions

The selection and weighting of ground‐motion models (GMMs) introduces a significant source of uncertainty in U.S. Geological Survey (USGS) National Seismic Hazard Modeling Project (NSHMP) forecasts. In this study, we evaluate 18 candidate GMMs using instrumental ground‐motion observations of horizontal peak ground acceleration (PGA) and 5%‐damped pseudospectral acceleration (0.02–10 s) for tectonic earthquakes and volcanic eruptions, to inform logic‐tree weights for the update of the USGS seismic hazard model for Hawaii. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function (PDF), mean and standard deviations σ "> σ ⁠ , of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Hawaii seismic hazard model logic trees. The total residual PDF approach provides additional information by preserving GMM over‐ and underprediction across a broad spectrum of periods that is not available from a single value LLH score. We apply these GMM evaluation methods to two different data sets: (1) a database of instrumental ground motions from historic earthquakes in Hawaii from 1973 to 2007 ( ⁠ M w "> M w 4–7.3) and (2) available ground motions from recent earthquakes ( ⁠ M w "> M w 4–6.9) associated with 2018 Kilauea eruptions. The 2018 Kilauea sequence contains both volcanic eruptions and tectonic earthquakes allowing for statistically significant GMM comparisons of the two event classes. The Kilauea ground observations provide an independent data set allowing us to evaluate the predictive power of GMMs implemented in the new USGS nshmp‐haz software system. We evaluate GMM performance as a function of earthquake depth and we demonstrate that short‐period volcanic eruption ground motions are not well predicted by any candidate GMMs. Nine of the initial 18 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the update of the Hawaii seismic hazard model. A weighted mean of four top performing GMMs in this study (NGAsubslab, NGAsubinter, ASK14, A10) is 50% lower for PGA than for GMMS used in the previous USGS seismic hazard model for Hawaii.

Hawaii↗

USGS2020

An update of USGS bear-real-time earthquake shaking and impact products

We report on advancements in both hazard and consequence modeling that form the core of the U.S. Geological Survey’s (USGS) strategy to improve rapid earthquake shaking and loss estimates. Whereas our primary goal is to improve our operational capabilities of the USGS National Earthquake Information Center, the science, software, and datasets behind these systems continue to advance uses and studies of earthquake shaking and impact by the seismological, engineering, financial, and risk modeling communities. Several important updates to our integrated shaking and impact products are outlined and we introduce new earthquake information products that have recently been brought online, including rapid ground failure estimates and more spatially refined loss estimates domestically (in the U.S). We continue to compile, develop, and refine key openly available models and datasets that contribute to calibrating these systems and report on the collection and storage of new inventories. We also describe some of the basic operational considerations in the current generation of these shaking and loss-estimation systems. A key aspect of the product integration and development is leveraging earthquake-hazard and loss-modeling science done internally (within the USGS) and by external researchers and collaborators. Lastly, we outline new opportunities for further research and development by emphasizing scientific, data, and application gaps and challenges that must be solved in order to improve our shaking and impact information tools.

Conference Paper↗

USGS2020

2018 and 2023 U. S. National Seismic Hazard Models

During 2017-2018, the National Seismic Hazard Model (NSHM) was updated by incorporating (1) new median ground motion models, new estimates of their epistemic uncertainties and aleatory variabilities, and new soil amplification factors for the central and eastern U.S., (2) amplification of long-period ground motions in deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas, (3) an updated seismicity catalog, which includes new earthquakes that occurred between 2012 and 2017, and (4) improved computer code and implementation details. Results show significantly increased ground shaking in many (but not all) locations across the central and eastern U.S., and increased ground shaking in the four urban areas (listed above) that overlie deep sedimentary basins in the western U.S. During 2019-2023, the NSHM will consider additional updates for the 2023 NSHM including: 3D simulations in urban areas of Los Angeles and Seattle, additional soil amplification models for other urban areas (e.g., eastern and southern coastal plains of the U.S., Reno, and Las Vegas), non-ergodic ground motion models that reconsider epistemic and aleatory uncertainty, topographic amplification, and new geological and geodetic models for faults. These maps will be considered by the Building Seismic Safety Council, American Society of Civil Engineers, and International Building Code committees for inclusion in upcoming building codes. Due to population growth, more people live and work in areas of moderate or high seismic hazard than ever before, leading to higher risk of undesirable consequences from future ground shaking.

conterminous United States↗

USGS2019

Earthquakes, ShakeMap

ShakeMap® is an open-source software program employed to automatically produce a suite of maps and products that portray the geographical extent and severity of potentially damaging shaking following an earthquake. ShakeMap’s primary purpose is to provide post-earthquake situational awareness for emergency management and response as well as damage and loss estimation. The availability of ShakeMaps immediately after a significant earthquake is critical for the identification of areas likely to be most damaged. Principal users include first responders, utility companies, response and aid agencies, scientists and engineers, and the media. Maps are made publicly available via the Internet within several minutes of an earthquake’s occurrence. ShakeMap is widely deployed in seismically active, well-instrumented portions of the USA and internationally in numerous countries including Italy, Iceland, Greece, Costa Rica, and Switzerland, among others, and the US...

Book chapter↗

USGS2019

Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence

Instrumental ground‐motion recordings from the 2018 Anchorage, Alaska ( ⁠ M w "> M w 7.1), earthquake sequence provide an independent data set allowing us to evaluate the predictive power of ground‐motion models (GMMs) for intraslab earthquakes associated with the Alaska subduction zone. In this study, we evaluate 15 candidate GMMs using instrumental ground‐motion observations of peak ground acceleration and 5% damped pseudospectral acceleration (0.02–10 s) to inform logic‐tree weights for the update of the U.S. Geological Survey seismic hazard model for Alaska. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function, mean, and standard deviations σ "> σ of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Alaska seismic hazard model logic trees. To test logic branches in previous seismic hazard models, we evaluate GMM performance as a function of depth and we demonstrate that some GMMs show improved performance for earthquakes with focal depths greater than 50 km. Ten of the initial 15 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the next update of the Alaska seismic hazard model.

Alaska↗

USGS2019

USGS near-real-time products-and their use-for the 2018 Anchorage earthquake

In the minutes to hours after a major earthquake, such as the recent 2018 M w "> M w 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

Alaska↗

USGS2019

The 2018 update of the US National Seismic Hazard Model: Overview of model and implications

During 2017–2018, the National Seismic Hazard Model for the conterminous United States was updated as follows: (1) an updated seismicity catalog was incorporated, which includes new earthquakes that occurred from 2013 to 2017; (2) in the central and eastern United States (CEUS), new ground motion models were updated that incorporate updated median estimates, modified assessments of the associated epistemic uncertainties and aleatory variabilities, and new soil amplification factors; (3) in the western United States (WUS), amplified shaking estimates of long-period ground motions at sites overlying deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas were incorporated; and (4) in the conterminous United States, seismic hazard is calculated for 22 periods (from 0.01 to 10 s) and 8 uniform V S30 maps (ranging from 1500 to 150 m/s). We also include a description of updated computer codes and modeling details. Results show increased ground shaking in many (but not all) locations across the CEUS (up to ~30%), as well as near the four urban areas overlying deep sedimentary basins in the WUS (up to ~50%). Due to population growth and these increased hazard estimates, more people live or work in areas of high or moderate seismic hazard than ever before, leading to higher risk of undesirable consequences from forecasted future ground shaking.

Earthquake Spectra↗

USGS2019

Ground-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW=7.1 Anchorage earthquake

We measure pseudospectral and peak ground motions from 44 intermediate‐depth M w ≥ 4.9 "> M w ≥ 4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 M w "> M w 7.1 earthquake near Anchorage, to identify regional amplification features ( ⁠ 0.1 – 5    s "> 0.1 – 5 s period). Ground‐motion residuals are computed with respect to an empirical ground‐motion model for intraslab subduction earthquakes, and we compute bias, between‐, and within‐event terms through a linear mixed‐effects regression. Between‐event residuals are analyzed to assess the relative source characteristics of the Cook Inlet earthquakes and suggest a difference in the scaling of the source with depth, relative to global observations. The within‐event residuals are analyzed to investigate regional amplification, and various spatial patterns manifest, including correlations of amplification with depth of the Cook Inlet basin and varying amplifications east and west of the center of the basin. Three earthquake clusters are analyzed separately and indicate spatial amplification patterns that depend on source location and exhibit variations in the depth scaling of long‐period basin amplification. The observations inform future seismic hazard modeling efforts in the Cook Inlet region. More broadly, they suggest a greater complexity of basin and regional amplification than is currently used in seismic hazard analyses.

Alaska↗

USGS2019

Ground failure from the Anchorage, Alaska, earthquake of 30 November 2018

Investigation of ground failure triggered by the 2018 M w "> M w Mw 7.1 Anchorage earthquake showed that landslides, liquefaction, and ground cracking all occurred and caused significant damage. Shallow rock falls and rock slides were the most abundant types of landslides, but they occurred in smaller numbers than global models that are based on earthquake magnitude predict; this might result from the 2018 earthquake being an intraslab event. Liquefaction was common in alluvial and intertidal areas; ground deformation probably related to liquefaction damaged numerous houses and port facilities in Anchorage. Ground cracking was pervasive near the edges of slopes in hilly areas and caused perhaps the most significant property damage of all types of ground failure. A complex of slump–earth flows was triggered along coastal bluffs in southern Anchorage where slides also occurred in 1964; the 2018 slides involved both mobilization of new landside material and reactivation of parts of the 1964 landslide deposits. Large translational slides that formed during the 1964 Alaska earthquake showed evidence of deformation along pre‐existing failure surfaces but did not reactivate with new net downslope displacement. Modeling suggests that ground motion in 2018 was of insufficient duration and too high frequency to trigger reactivation of the deep landslides.

Alaska↗

USGS2018

Evaluation of ground motion models for USGS seismic hazard forecasts: Induced and tectonic earthquakes in the Central and Eastern U.S.

Ground motion model (GMM) selection and weighting introduces a significant source of uncertainty in United States Geological Survey (USGS) seismic hazard models. The increase in moderate moment magnitude induced earthquakes (Mw 4 to 5.8) in Oklahoma and Kansas since 2009, due to increased wastewater injection related to oil and gas production (Keranen et al., 2013; 2014; Weingarten et al., 2015; McNamara et al., 2015a), provides useful near-source (< 40 km) instrumental ground-motion observations for comparisons between central and eastern US (CEUS) induced (Rennolet et al., 2017) and tectonic (Goulet et al., 2014) earthquakes. In this study, we evaluate over 50 GMMs using two well-established probabilistic scoring methods: log likelihood (LLH) (Scherbaum et al., 2004; 2009) and multivariate LLH (MLLH) (Mak et al., 2017). The LLH approach compares the mean and standard deviation (σ) of the observed and modeled ground motions. The MLLH approach advances the LLH method by considering the variability (φ,τ) of multiple correlated variables namely intra- (within) and inter- (between) event residuals. For the probabilistic scoring GMM evaluation methods (LLH, MLLH), we compute horizontal component peak ground acceleration (PGA) and 1s period pseudo spectral acceleration (PSA1.0) total residuals using GMM software (nshmp-haz) recently implemented by the USGS National Seismic Hazard Model Project (NSHMP). We observe from LLH and MLLH scores that: 1) newer GMMs with lower standard deviations (σ,φ,τ) score better than older GMMs with higher published uncertainty; 2) 2014 CEUS GMMs score better for CEUS tectonic earthquakes than induced earthquakes; 3) NGA-West2, G17 and A15 GMMs score well for CEUS induced earthquake ground motions; and 4) NGA-East GMMs score well for CEUS tectonic earthquake ground motions. We also use the LLH and MLLH scores to evaluate GMM weights applied in past USGS seismic hazard forecasts and to inform weighting of GMMs in future seismic hazard forecasts.

Bulletin of the Seismological Society of America↗

USGS2018

Ground motions from induced earthquakes in Oklahoma and Kansas

Improved predictions of earthquake ground motions are critical to advancing seismic hazard analyses and earthquake response. The high seismicity rate from 2009 to 2016 in Oklahoma and Kansas provides an extensive data set for examining the ground motions from these events. We evaluate the ability of three suites of ground‐motion prediction equations (GMPEs)—appropriate for modeling tectonic earthquakes in active crustal and stable continental regions—to reproduce the observed ground motions. Mixed‐effects regressions are used to separate the ground‐motion residuals into bias, between‐event, and within‐event terms. Although the residuals depict differing accuracies in the ability of the three GMPE suites to predict the ground motions, some consistent trends emerge in the period, magnitude, and distance dependence. The trends suggest that aspects of the ground motions from these induced earthquakes are not well modeled by current tectonic GMPEs. Most important, we find evidence for relatively poor overall fit to the ground motions, by all of the GMPE suites, at periods less than about 0.2 s and above 3 s, greater‐than‐predicted magnitude scaling for small to moderate‐magnitude events ( ⁠ M ≲ 5 "> M ≲ 5 ⁠ ), higher‐than‐predicted within‐event variability above 3 s, and an apparent geometric attenuation that is stronger than average predictions at close distances ( ⁠ R ≲ 20    km "> R ≲ 20 km ) and short periods ( ⁠ T ≲ 1 s "> T ≲ 1 s ). Our results indicate that regionally appropriate GMPEs for induced earthquakes should be used for predicting ground motions in Oklahoma and Kansas.

Kansas, Oklahoma↗

USGS2018

The case for mean rupture distance in ground‐motion estimation

This article advocates for the use of mean rupture distances that we contend are more physically representative of the distance to an earthquake and are simpler than minimum distances. Many current ground‐motion models (GMMs) rely on numerous modifications of minimum rupture distances to accurately model near‐source ground motions. These modifications, that include additional distance definitions and saturation terms, result in complicated functional forms and are often not easily understood on a seismological basis, such as the magnitude‐dependent near‐fault saturation term. The use of mean distance represents the location of a station in relation to the entire rupture plane and results in a simpler, more physically meaningful GMM that models near‐source ground motion as accurately as other GMMs that have more inputs and more complex functional forms. We demonstrate the use of mean distance by developing a GMM for shallow‐crustal earthquakes with the Next Generation Attenuation‐West2 (NGA‐West2) project database. Specifically, we use the generalized mean distance, also known as the power mean, in which the power varies with frequency. We show that this new GMM fits the NGA‐West2 database as well as the NGA‐West2 GMMs and exhibits similar near‐source amplitude scaling. An additional benefit of mean distance is that it can provide a mechanism to account for spatially variable slip. We prospectively validate this GMM against the 2016 M "> M 7.8 Kaikōura, New Zealand, earthquake, which was not used in model development. To better understand the magnitude dependence of geometrical spreading, we employ a simple conceptual model based on fundamental principles to show that the GMM is consistent with common seismological understanding.

Bulletin of the Seismological Society of America↗

USGS2018

Improving near‐real‐time coseismic landslide models: Lessons learned from the 2016 Kaikōura, New Zealand, earthquake

The U.S. Geological Survey (USGS) is developing near‐real‐time global earthquake‐triggered‐landslide products to augment the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system. The 14 November 2016 M w "> M w Mw 7.8 Kaikōura, New Zealand, earthquake provided a test case for evaluating the performance and near‐real‐time response applicability of three published global seismically induced landslide models. All three models obtain shaking estimates from the USGS ShakeMap, which is updated and sometimes changes significantly in the hours to days after an earthquake. The Kaikōura earthquake is a particularly valuable event that helps us better understand how changes to the ShakeMap affect the landslide models because the ShakeMap evolved significantly over several weeks as multifault rupture and seismic data were incorporated. We used the detailed landslide inventory available for this event for qualitative landslide model evaluation. We found that once a point source was replaced with an approximate rupture extent in ShakeMap, the landslide models were all successful at roughly identifying the area of highest hazard. This is notable, given that the models are relatively simple, coarse in resolution, and are based solely on input proxies that are globally available. However, all of the models dramatically overpredicted the hazard level, which indicates that improvements can be made. Subsequent updates to the ShakeMap resulted in improvements to model performance by some metrics and declining performance by others. In all cases, details of the ShakeMap strongly controlled the spatial pattern, even when those details were erroneous, such as the inclusion of a fault segment that did not rupture. If maps of landslide hazard are to be used effectively for rapid response, then we need to understand and clearly communicate the control that ShakeMap has over the models and how that typically evolves with time and is (or is not) reflected in reported uncertainties.

Bulletin of the Seismological Society of America↗

USGS2018

Spatial and spectral interpolation of ground-motion intensity measure observations

Following a significant earthquake, ground‐motion observations are available for a limited set of locations and intensity measures (IMs). Typically, however, it is desirable to know the ground motions for additional IMs and at locations where observations are unavailable. Various interpolation methods are available, but because IMs or their logarithms are normally distributed, spatially correlated, and correlated with each other at a given location, it is possible to apply the conditional multivariate normal (MVN) distribution to the problem of estimating unobserved IMs. In this article, we review the MVN and its application to general estimation problems, and then apply the MVN to the specific problem of ground‐motion IM interpolation. In particular, we present (1) a formulation of the MVN for the simultaneous interpolation of IMs across space and IM type (most commonly, spectral response at different oscillator periods) and (2) the inclusion of uncertain observation data in the MVN formulation. These techniques, in combination with modern empirical ground‐motion models and correlation functions, provide a flexible framework for estimating a variety of IMs at arbitrary locations.

Bulletin of the Seismological Society of America↗

USGS2018

A flatfile of ground motion intensity measurements from induced earthquakes in Oklahoma and Kansas

We have produced a uniformly processed database of orientation-independent (RotD50, RotD100) ground motion intensity measurements containing peak horizontal ground motions (accelerations and velocities) and 5-percent-damped pseudospectral accelerations (0.1–10 s) from more than 3,800 M ≥ 3 earthquakes in Oklahoma and Kansas that occurred between January 2009 and December 2016. Ground motion time series were collected from regional, national, and temporary seismic arrays out to 500 km. We relocated the majority of the earthquake hypocenters using a multiple-event relocation algorithm to produce a set of near-uniformly processed hypocentral locations. Ground motion processing followed standard methods, with the primary objective of reducing the effects of noise on the measurements. Regional wave-propagation features and the high seismicity rate required careful selection of signal windows to ensure that we captured the entire ground motion record and that contaminating signals from extraneous earthquakes did not contribute to the database. Processing was carried out with an automated scheme and resulted in a database comprising more than 174,000 records ( https://dx.doi.org/10.5066/F73B5X8N ). We anticipate that these results will be useful for improved understanding of earthquake ground motions and for seismic hazard applications.

Kansas, Oklahoma↗

USGS2018

Preliminary 2018 national seismic hazard model for the conterminous United States

The 2014 U.S. Geological Survey national seismic hazard model for the conterminous U.S. will be updated in 2018 and 2020 to coincide with the Building Seismic Safety Council’s Project 17 timeline for development of new building code design criteria. The two closely timed updates are planned to allow more time for the Provisions Update Committee to analyze the consequences of the hazard model changes in the design criteria. To prepare the 2018 update we held a workshop (March 7-8, 2018) with scientists and engineers to solicit feedback on the model. The 2018 model will be available for public comment during the summer of 2018. The purpose of this paper is to solicit feedback on the modeling choices and results. The 2018 NSHM considers an updated seismicity catalog and certain key changes in the way ground motions are calculated. First, we implemented new Next Generation Attenuation Relationships for the Central and Eastern North America Region and other published models that allow for the calculation of ground motions at additional periods and site classes in the central and eastern U.S. (CEUS). Second, basin depth terms were implemented in the ground motion models in select regions of the western U.S. (WUS) to account for enhanced long-period ground motions at softer soil sites overlying sedimentary basins. Preliminary results indicate higher ground motions for all periods in parts of the CEUS and for long-periods and soft soils in urban areas overlying sedimentary basins in the WUS.

Conference Paper↗

USGS2017

An open repository of earthquake-triggered ground-failure inventories

Earthquake-triggered ground failure, such as landsliding and liquefaction, can contribute significantly to losses, but our current ability to accurately include them in earthquake-hazard analyses is limited. The development of robust and widely applicable models requires access to numerous inventories of ground failures triggered by earthquakes that span a broad range of terrains, shaking characteristics, and climates. We present an openly accessible, centralized earthquake-triggered groundfailure inventory repository in the form of a ScienceBase Community to provide open access to these data with the goal of accelerating research progress. The ScienceBase Community hosts digital inventories created by both U.S. Geological Survey (USGS) and non-USGS authors. We present the original digital inventory files (when available) as well as an integrated database with uniform attributes. We also summarize the mapping methodology and level of completeness as reported by the original author(s) for each inventory. This document describes the steps taken to collect, process, and compile the inventories and the process for adding additional ground-failure inventories to the ScienceBase Community in the future.

Data Series↗

USGS2017

Estimating rupture distances without a rupture

Most ground motion prediction equations (GMPEs) require distances that are defined relative to a rupture model, such as the distance to the surface projection of the rupture (RJB) or the closest distance to the rupture plane (RRUP). There are a number of situations in which GMPEs are used where it is either necessary or advantageous to derive rupture distances from point-source distance metrics, such as hypocentral (RHYP) or epicentral (REPI) distance. For ShakeMap, it is necessary to provide an estimate of the shaking levels for events without rupture models, and before rupture models are available for events that eventually do have rupture models. In probabilistic seismic hazard analysis, it is often convenient to use point-source distances for gridded seismicity sources, particularly if a preferred orientation is unknown. This avoids the computationally cumbersome task of computing rupture-based distances for virtual rupture planes across all strikes and dips for each source. We derive average rupture distances conditioned on REPI, magnitude, and (optionally) back azimuth, for a variety of assumed seismological constraints. Additionally, we derive adjustment factors for GMPE standard deviations that reflect the added uncertainty in the ground motion estimation when point-source distances are used to estimate rupture distances.

Bulletin of the Seismological Society of America↗