The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard (both increases and decreases compared to previous NSHMs) are substantial because the new model considers more data and updated earthquake rupture forecasts and ground-motion components. In developing the 2023 model, we tried to apply best available or applicable science based on advice of co-authors, more than 50 reviewers, and hundreds of hazard scientists and end-users, who attended public workshops and provided technical inputs. The hazard assessment incorporates new catalogs, declustering algorithms, gridded seismicity models, magnitude-scaling equations, fault-based structural and deformation models, multi-fault earthquake rupture forecast models, semi-empirical and simulation-based ground-motion models, and site amplification models conditioned on shear-wave velocities of the upper 30 m of soil and deeper sedimentary basin structures. Seismic hazard calculations yield hazard curves at hundreds of thousands of sites, ground-motion maps, uniform-hazard response spectra, and disaggregations developed for pseudo-spectral accelerations at 21 oscillator periods and two peak parameters, Modified Mercalli Intensity, and 8 site classes required by building codes and other public policy applications. Tests show the new model is consistent with past ShakeMap intensity observations. Sensitivity and uncertainty assessments ensure resulting ground motions are compatible with known hazard information and highlight the range and causes of variability in ground motions. We produce several impact products including building seismic design criteria, intensity maps, planning scenarios, and engineering risk assessments showing the potential physical and social impacts. These applications provide a basis for assessing, planning, and mitigating the effects of future earthquakes.

Research Article| January 25, 2023 Introduction to the SRL Focus Section on the Hunga Tonga‐Hunga Ha’apai Eruption Margaret Hellweg; Margaret Hellweg * 1Berkeley Seismology Laboratory, University of California Berkeley, Berkeley, California, U.S.A. *Corresponding author: peggy@seismo.berkeley.edu Search for other works by this author on: GSW Google Scholar Stephen Arrowsmith; Stephen Arrowsmith 2Southern Methodist University, Dallas, Texas, U.S.A. https://orcid.org/0000-0002-9150-0363 Search for other works by this author on: GSW Google Scholar Hugo Delgado; Hugo Delgado 3Departamento de Vulcanologia, Instituto de Geofisica, Coyoacan, Mexico https://orcid.org/0000-0001-5263-7968 Search for other works by this author on: GSW Google Scholar James Gridley; James Gridley 4National Tsunami Warning Center, Palmer, Alaska, U.S.A. Search for other works by this author on: GSW Google Scholar Ronan Joseph Le Bras; Ronan Joseph Le Bras 5Comprehensive Test Ban Treaty Organization, Wien, Austria https://orcid.org/0000-0003-2439-6938 Search for other works by this author on: GSW Google Scholar Daniel McNamara; Daniel McNamara 6Ann Arbor, Michigan, U.S.A. Search for other works by this author on: GSW Google Scholar Steven Sherburn Steven Sherburn 7Data Science and Geohazards Monitoring Department, GNS Science, Taupo, New Zealand Search for other works by this author on: GSW Google Scholar Author and Article Information Margaret Hellweg * 1Berkeley Seismology Laboratory, University of California Berkeley, Berkeley, California, U.S.A. Stephen Arrowsmith https://orcid.org/0000-0002-9150-0363 2Southern Methodist University, Dallas, Texas, U.S.A. Hugo Delgado https://orcid.org/0000-0001-5263-7968 3Departamento de Vulcanologia, Instituto de Geofisica, Coyoacan, Mexico James Gridley 4National Tsunami Warning Center, Palmer, Alaska, U.S.A. Ronan Joseph Le Bras https://orcid.org/0000-0003-2439-6938 5Comprehensive Test Ban Treaty Organization, Wien, Austria Daniel McNamara 6Ann Arbor, Michigan, U.S.A. Steven Sherburn 7Data Science and Geohazards Monitoring Department, GNS Science, Taupo, New Zealand *Corresponding author: peggy@seismo.berkeley.edu Publisher: Seismological Society of America First Online: 25 Jan 2023 Online ISSN: 1938-2057 Print ISSN: 0895-0695 © Seismological Society of America Seismological Research Letters (2023) 94 (2A): 564–566. https://doi.org/10.1785/0220230001 Article history First Online: 25 Jan 2023 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Margaret Hellweg, Stephen Arrowsmith, Hugo Delgado, James Gridley, Ronan Joseph Le Bras, Daniel McNamara, Steven Sherburn; Introduction to the SRL Focus Section on the Hunga Tonga‐Hunga Ha’apai Eruption. Seismological Research Letters 2023;; 94 (2A): 564–566. doi: https://doi.org/10.1785/0220230001 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search Similar to the Roman god Janus, natural events often have two faces. For the people in their environment, they can be disasters, sometimes with truly terrible effects. For scientists, often geophysicists who observe the interactions on the planet, they may bring exciting new measurements and insights. The Hunga Tonga‐Hunga Ha’apai (HTHH) eruption was just such an event. It was the largest underwater eruption since 1883, when the Indonesian volcano Krakatoa produced a tsunami that killed more than 20,000 people, and the pressure wave that was heard (or measured) around the world. Similar to Krakatoa, the HTHH eruption was tremendous, with... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

The 2021 US National Seismic Hazard Model (NSHM) for the State of Hawaii updates the previous two-decade-old assessment by incorporating new data and modeling techniques to improve the underlying ground shaking forecasts of tectonic-fault, tectonic-flexure, volcanic, and caldera collapse earthquakes. Two earthquake ground shaking hazard forecasts (public policy and research) are produced that differ in how they account for declustered catalogs. The earthquake source model is based on (1) declustered earthquake catalogs smoothed with adaptive methods, (2) earthquake rate forecasts based on three temporally varying 60-year time periods, (3) maximum magnitude criteria that extend to larger earthquakes than previously considered, (4) a separate Kīlauea-specific seismogenic caldera collapse model that accounts for clustered event behavior observed during the 2018 eruption, and (5) fault ruptures that consider historical seismicity, GPS-based strain rates, and a new Quaternary fault database. Two new Hawaii-specific ground motion models (GMMs) and five additional global models consistent with Hawaii shaking data are used to forecast ground shaking at 23 spectral periods and peak parameters. Site effects are calculated using western US and Hawaii specific empirical equations and provide shaking forecasts for 8 site classes. For most sites the new analysis results in similar spectral accelerations as those in the 2001 NSHM, with a few exceptions caused mostly by GMM changes. Ground motions are the highest in the southern portion of the Island of Hawai’i due to high rates of forecasted earthquakes on décollement faults. Shaking decays to the northwest where lower earthquake rates result from flexure of the tectonic plate. Large epistemic uncertainties in source characterizations and GMMs lead to an overall high uncertainty (more than a factor of 3) in ground shaking at Honolulu and Hilo. The new shaking model indicates significant chances of slight or greater damaging ground motions across most of the island chain.

Seismic attenuation is generally greater in the western United States (WUS) than the central and eastern United States (CEUS), but the nature of this transition or location of this boundary is poorly constrained. We conduct crustal seismic (Lg) attenuation tomography across a region that stretches from the CEUS across the Rocky Mountains to the Basin and Range using a total of 115,870 amplitude measurements from 106 earthquakes recorded on 544 stations across five frequency bands spanning 0.5–16 Hz. Similar to previous studies, we find higher attenuation in the WUS ( Q 0 ∼ 190) than the nominally CEUS ( Q 0 ∼ 250) and comparatively high attenuation on the Gulf Coast ( Q 0 ∼ 175). Our models defy simple east versus west regionalization, however. Heterogeneity within the Rocky Mountain region—low attenuation in the Colorado Plateau interior and Wyoming Craton ( Q 0 ∼ 230) compared to high attenuation in the southern Rockies ( Q 0 ∼ 110)—exceeds the gross differences between the CEUS and western United States. These province‐scale patterns are readily interpreted in terms of intrinsic attenuation. The boundary between the Colorado Plateau and Basin and Range hosts the highest attenuation imaged in the study area ( Q 0 ∼ 90), consistent with localized scattering across contrasting crustal structure. Focused high attenuation in the southern Rockies may represent the effects of represent in situ partial crustal melt. Within the CEUS, second‐order bands of comparatively high attenuation align with the Proterozoic Yavapai‐Mazatzal suture zone and Midcontinent Rift. This complex attenuation structure defies broad regionalization and suggests a need for path‐specific models near these boundaries and for critical infrastructure.

The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous U.S. NSHM includes significant changes to the underlying ground motion models (GMMs), most of which are necessary to enable the new multi-period response spectra (MPRS) requirements of seismic design regulations that use hazard results for 22 spectral periods and eight site classes. This article focuses on the GMMs used in the western United States (WUS) and is a companion to a recent article on the GMMs used in the central and eastern United States (CEUS). In the WUS, for crustal and subduction earthquakes, two models used in previous versions of the NSHM are excluded to provide consistency over all considered periods and site classes. To more accurately estimate ground motions at long periods in the vicinity of Los Angeles, San Francisco, Salt Lake City, and Seattle, the 2018 NSHM incorporates deep sedimentary basin depth from local seismic velocity models. The subduction GMMs considered lack basin depth terms and are modified to include an additional scale factor to account for this. This article documents the WUS GMMs used in the 2018 NSHM update and provides detail on the changes to GMM medians, aleatory variability, epistemic uncertainty, and site-effect models. It compares each of these components with those considered in prior NSHMs and discusses their total effect on hazard.

The 2018 US Geological Survey National Seismic Hazard Model (NSHM) incorporates new data and updated science to improve the underlying earthquake and ground motion forecasts for the conterminous United States. The NSHM considers many new data and component input models: (1) new earthquakes between 2013 and 2017 and updated earthquake magnitudes for some earlier earthquakes; (2) two updated smoothed seismicity models to forecast earthquake rates; (3) two suites of new central and eastern US (CEUS) ground motion models (GMMs) to translate ground shaking for various earthquake sizes and source-to-site distances considered in the model; (4) two CEUS GMMs for aleatory variability; (5) two CEUS site-effect models that modify ground shaking based on alternative shallow site conditions; (6) more advanced western US (WUS) lithologic and structural information to assess basin site effects for selected urban regions; and (7) a more comprehensive range of outputs (22 periods and 8 site classes) than in previous versions of the NSHMs. Each of these new datasets and models produces changes in the probabilistic ground shaking levels that are spatially and statistically analyzed. Recent earthquakes or changes to some older earthquake magnitudes and locations mostly result in probabilistic ground shaking levels that are similar to previous models, but local changes can reach up to +80% and −60% compared to the 2014 model. Newly developed CEUS models for GMMs, aleatory variability, and site effects cause overall changes up to ±64%. The addition of the WUS basin amplifications causes changes of up to +60% at longer periods for sites overlying deep soft soils. Across the conterminous United States, the hazard changes in the model are mainly caused by new GMMs in the CEUS, by sedimentary basin effects for long periods (≥1 s) in the WUS, and by seismicity changes for short (0.2 s) and long (1 s) periods for both areas.

FIGURE 1. Schematic of ocean-based geophysical instrumentation and data communications installation. A wave glider and a Deep-Ocean Assessment and Reporting of Tsunamis (DART) tsunameter communicate with a satellite. An autonomous underwater vehicle (AUV) collects data from the water column for later transmission via the satellite. Other instrumentation includes a recoverable geodetic transponder, a trawl-resistant and current-protected seismometer, and a self-calibrating pressure gauge. The 2004 magnitude (M) 9.1 Sumatra-Andaman Islands earthquake in the Indian Ocean triggered the deadliest tsunami ever, killing more than 230,000 people. In response, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) established three additional Intergovernmental Coordination Groups (ICGs) for the Tsunami and Other Coastal Hazards Early Warning System: for the Caribbean and Adjacent Regions (ICG/CARIBE-EWS), for the Indian Ocean, and for the Northeastern Atlantic, Mediterranean, and Connected Seas. Along with the ICG for the Pacific Ocean, which was established in 1965, one of the goals of the new ICGs was to improve earthquake and tsunami monitoring and early warning. This need was further demonstrated by the 2011 Great East Japan (Tōhoku-oki) earthquake and tsunami, which killed more than 20,000 people, and other destructive tsunamis that occurred in the Solomon Islands, Samoa, Tonga, Chile, Indonesia, and Peru. In response to the call to action by the UN Decade of Ocean Science for Sustainable Development (2021– 2030), as well as the desired safe ocean outcome (von Hillebrandt-Andrade et al., 2021), the Intergovernmental Oceanographic Commission (IOC) of UNESCO approved the Ocean Decade Tsunami Programme in June 2021. One of its goals is to develop the capability to issue actionable alerts for tsunamis from all sources with minimum uncertainty within 10 minutes (Angove et al., 2019). While laudable, this goal presents complexities. Currently, warning depends on quick detection as well as the location and initial magnitude estimates of an earthquake that may generate a tsunami. Other factors that affect tsunamis, such as the faulting mechanism (how the faults slide past each other) and areal extent of the earthquake, currently take at least 20–30 minutes to forecast and are still subject to large uncertainties. Hence, agencies charged with tsunami early warning need to broadcast public alerts within minutes after an earthquake occurs but may struggle to meet this 10-minute goal without further technological advances, some of which are outlined in this article. To reduce loss of life through adequate tsunami warning requires global ocean-based seismic, sea level, and geodetic initiatives to detect high-impact earthquakes and tsunamis, combined with sufficient communication and education so that people know how to respond when they receive alerts and warnings. The United Nations

ABSTRACTThis article assesses the ability of regionally specific, frequency-dependent crustal attenuation (1/Q) to reduce mean magnitude discrepancies between seismic stations in the northern Appalachian and Grenville provinces (NAP and GP) of Canada. LgQ(f) is an important parameter in ground-motion models used in probabilistic seismic hazard analysis. Discrepancies in regional magnitude estimates have long been noted to exist between stations in the two provinces for common event origins. Such discrepancies could arise from systematic site condition variations between the geologic provinces or from varying crustal attenuative properties. To evaluate the effect of frequency-dependent anelastic attenuation, LgQ(f) on estimated magnitudes, we analyze Lg amplitudes from >6000 waveforms recorded by Grenville and northern Appalachian receivers from 420 natural earthquakes of MN magnitude 3–5.6. Waveform analysis is strictly limited to analyst-reviewed, vertical-component waveforms in which Lg is clearly identified, ensuring that the datasets exhibit dominant, high-frequency energy in the Lg velocity window. LgQ(f) is found to be higher in the GP than in the northern Appalachians. In the Grenville, Q(f)=761(±145)f0.25(±0.014), and in the northern Appalachians, attenuation is higher: Q(f)=506(±172)f0.33(±0.310). Earthquake magnitude determined using the peak amplitude of the Lg phase (mbLg) for eastern Canada is corrected to incorporate the frequency-dependent, regionally specific LgQ(f) determined in this study. Using the new LgQ(f) values diminishes and nearly resolves magnitude discrepancies between the provinces. Correcting regional magnitude discrepancies between provinces is critical for reliable regional seismic hazard estimates because magnitude error in a particular region could lead to increased uncertainty in seismic hazard models.

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.

Rapid seismic deployments following large earthquakes capture ephemeral near-field recordings of aftershocks and ambient noise that can provide valuable data for seismological studies. The U.S. Geological Survey installed 19 temporary seismic stations following the 4 July 2019 M w 6.4 and 6 July 2019 (UTC) M w 7.1 earthquakes near the city of Ridgecrest, California. The stations record the aftershock sequence beginning two days after the mainshock and are expected to remain in the field through approximately January 2020. The deployment augments the permanent seismic network in the area to improve azimuthal coverage and provide additional near-field observations. This article summarizes the motivation and goals of the deployment; details of station installation, instrumentation, and configurations; and initial data quality and observations from the network. We expect these data to be useful for a range of studies including detailing near-field variability in strong ground motions, determining stress drops and rupture directivity of small events, imaging the fault zone, documenting the evolution of crustal properties within and outside of the fault zone, and others.

ABSTRACTWe evaluated the performance of 12 ground-motion models (GMMs) for earthquakes in the tectonically active shallow crustal region of southern California using instrumental ground-motion observations from the 2019 Ridgecrest, California, earthquake sequence (Mw 4.0–7.1). The sequence was well recorded by the Southern California Seismic Network and rapid response portable aftershock monitoring stations. Ground-motion recordings of this size and proximity are rare, valuable, and independent of GMM development, allowing us to evaluate the predictive powers of GMMs. We first compute total residuals and compare the probability density functions, means, and standard deviations of the observed and predicted ground motions. Next we use the total residuals as inputs to the probabilistic scoring method (log-likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) logic trees. We also explore GMM performance for a range of earthquake magnitudes, wave propagation distances, and site characteristics. We find that the Next Generation Attenuation West-2 (NGAW2) active crust GMMs perform well for the 2019 Ridgecrest, California, earthquake sequence and thus validate their use in the 2018 USGS NSHM. However, significant ground-motion residual scatter remains unmodeled by NGAW2 GMMs due to complexities such as local site amplification and source directivity. Results from this study will inform logic-tree weights for updates to the USGS National NSHM. Results from this study support the use of nonergodic GMMs that can account for regional attenuation and site variations to minimize epistemic uncertainty in USGS NSHMs.

ABSTRACTThe 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, 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 (Mw 4–7.3) and (2) available ground motions from recent earthquakes (Mw 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.

Instrumental ground-motion recordings from the 2018 Anchorage, Alaska (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 sigma 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.

We measure pseudospectral and peak ground motions from 44 intermediate-depth M-w >= 4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 M-w 7.1 earthquake near Anchorage, to identify regional amplification features (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.

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 less than or similar to 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 less than or similar to 20 km) and short periods (T less than or similar to 1s). Our results indicate that regionally appropriate GMPEs for induced earthquakes should be used for predicting ground motions in Oklahoma and Kansas.

ABSTRACTAdvances in seismic instrumentation have enabled data to be recorded at increasing sample rates. This has in turn created a need to establish higher frequency baselines for assessing data quality, as the widely used new high-noise model (NHNM) and new low-noise model (NLNM) of Peterson (1993) do not extend to frequencies above 10 Hz. To provide a baseline for higher frequencies (10–100 Hz), we examine power spectral density probability density functions (PSDPDFs) for high-sample rate stations available from the Incorporated Research Institutions for Seismology Data Services Modular Utility for STAtistical kNowledge Gathering (IRIS MUSTANG) quality control system. We compute high-frequency high- and low-noise baselines by matching the appropriate composite PSDPDF percentile points to NHNM and NLNM power levels at overlapping frequencies (1–10 Hz) and then extending to higher frequencies (10–100 Hz) with piecewise linear fits to the matching PSDPDF percentile.We find that the Peterson NLNM remains an accurate representation of the lower bound of global ambient Earth noise because it is lower than 99.9% of Global Seismographic Network power spectral densities. We present high-frequency high- and low-noise baselines intended primarily for use by temporary networks targeting high-frequency signals (e.g., monitoring of aftershocks or induced seismicity) based on statistics of PSDPDFs from all publicly available high-sample rate data.Most publicly available high-sample rate data are recorded by temporary deployments, and the experiment design and scientific targets of these deployments strongly influence the observed statistical distribution of high-frequency noise. We anticipate that the noise baselines presented here will be useful in automated quality control of high-sample rate seismic data. However, we note that establishing a low-noise model that accurately represents the lowest possible ambient Earth noise at frequencies up to 100 Hz will require additional continuous high-sample rate data from high-quality permanent stations in low-noise environments.

Seismicity in the central United States has dramatically increased since 2008, due in large part to the injection of waste-water produced by oil and gas extraction. In response to this phenomenon, the U.S. Geological Survey (USGS) created a one-year probabilistic hazard model and map for 2016 to portray the increased hazard posed to the central and eastern United States. Using the intensity of shaking reported to the "Did You Feel It?" (DYFI) system during 2016, we assessed the performance of this model using a metric that compared the fraction of sites at which the maximum shaking exceeded the mapped value to the fraction that had been expected. These fractions are similar for both the central and eastern United States as a whole, as well as for the region within this area with the highest amount of seismicity - Oklahoma and its surrounding area. We observe the greatest mismatch in northern Texas, with hazard overstated, presumably because lower oil and gas prices and regulatory action reduced the water injection volume relative to that of the previous year. We also assessed the model using a misfit metric that compares the spatial patterns of predicted and maximum observed shaking. This hazard map performs better by both metrics than other hazard maps we have studied. These results imply that such hazard maps can be valuable tools for policy makers and regulators in attempts to manage the seismic risks associated with unconventional oil and gas production.

Oklahoma experienced three earthquakes of M(w)5.0 or greater in 2016: the 13-Feb. Fairview earthquake (M(w)5.1), the 03-Sep. Pawnee earthquake (M(w)5.8), and the 07-Nov. Cushing earthquake (M(w)5.0). These events are the first earthquakes in the state exceeding M(w)5.0 since the 2011 M(w)5.7 Prague earthquake and likely result from wide scale deep fluid-injection. We use interferometric synthetic aperture radar (InSAR) observations to quantify the magnitude and location of surface deformation associated with these three events, determine the depth ranges of fault slip, and assess the spatial relationship between fault slip and well-calibrated mainshock and aftershock locations. We also include newly reported, calibrated event locations for the Cushing earthquake. We find that the Pawnee earthquake ruptured within the crystalline basement with the shallowest slip occurring at depths of 3.1-4.3 km. We find a similar, though shallower, crystalline basement source for the Cushing earthquake with a minimum depth to slip of 1.6-2.3 km. Despite the smaller magnitude of the Cushing earthquake, it generated anomalously high ground motions and damage compared to the larger Pawnee and Fairview earthquakes. We postulate that the shallow source of the Cushing earthquakes provides one explanation for the higher than expected ground motions. The Fairview earthquake generated no detectable co-seismic displacements, which is consistent with a relatively deep earthquake source (similar to 8.5 km). We do, however, identify a 16 km stretch of floodplain where widespread liquefaction occurred in response to the Fairview earthquake, and where 30 gas production wells were exposed to surface displacements exceeding 5 cm. Consequently, the depth to crystalline basement, which limits the depth of injection-induced earthquakes in Oklahoma, and the potential for liquefaction are important factors in assessing shaking risk in the central United States.

This article describes the U.S. Geological Survey (USGS) 2018 one-year probabilistic seismic hazard forecast for the central and eastern United States from induced and natural earthquakes. For consistency, the updated 2018 forecast is developed using the same probabilistic seismicity-based methodology as applied in the two previous forecasts. Rates of earthquakes across the United States M >= 3.0 grew rapidly between 2008 and 2015 but have steadily declined over the past 3 years, especially in areas of Oklahoma and southern Kansas where fluid injection has decreased. The seismicity pattern in 2017 was complex with earthquakes more spatially dispersed than in the previous years. Some areas of west-central Oklahoma experienced increased activity rates where industrial activity increased. Earthquake rates in Oklahoma (429 earthquakes of M >= 3 and 4 M >= 4), Raton basin (Colorado/New Mexico border, six earthquakes M >= 3), and the New Madrid seismic zone (11 earthquakes M >= 3) continue to be higher than historical levels. Almost all of these earthquakes occurred within the highest hazard regions of the 2017 forecast. Even though rates declined over the past 3 years, the short-term hazard for damaging ground shaking across much of Oklahoma remains at high levels due to continuing high rates of smaller earthquakes that are still hundreds of times higher than at any time in the state's history. Fine details and variability between the 2016-2018 forecasts are obscured by significant uncertainties in the inputmodel. These short-term hazard levels are similar to active regions in California. During 2017, M >= 3 earthquakes also occurred in or near Ohio, West Virginia, Missouri, Kentucky, Tennessee, Arkansas, Illinois, Oklahoma, Kansas, Colorado, New Mexico, Utah, and Wyoming.