Geology topics

Morgan P. Moschetti

Publications and source records attributed to Morgan P. Moschetti.

At least 37 records · Page 2Linked to original sources

USGS2024

Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models

Model development in the Next Generation Attenuation-East (NGA-East) project included two components developed concurrently and independently: (1) earthquake ground-motion models (GMMs) that predict the median and aleatory variability of various intensity measures conditioned on magnitude and distance, derived for a reference hard-rock site condition with an average shear-wave velocity in the upper 30 m ( V S30 ) = 3000 m/s; and (2) a site amplification model that modifies intensity measures for softer site conditions. We investigate whether these models, when used in tandem, are compatible with ground-motion recordings in central and eastern North America (CENA) using an expanded version of the NGA-East database that includes new events from November 2011 (end date of NGA-East data curation) to April 2022. Following this expansion, the data set has 187 events, 2096 sites, and 16,272 three-component recordings, although the magnitude range remains limited (∼4 to 5.8). We compute residuals using 17 NGA-East GMMs and three data selection criteria that reflect within-CENA regional variations in ground-motion attributes. Mixed-effects regression of the residuals reveals a persistent pattern in which ground motions are overpredicted at short periods (0.01–0.6 s, including peak ground acceleration (PGA)) and underpredicted at longer periods. These misfits are regionally variable, with the Texas–Oklahoma–Kansas region having larger absolute misfits than other parts of CENA. Two factors potentially influencing these misfits are (1) differences in the site amplification models used to adjust the data to the reference condition during NGA-East GMM development relative to CENA amplification models applied since the 2018 National Seismic Hazard Model (NSHM), and (2) potential bias in simulation-based factors used to adjust ground motions from the hard-rock reference condition to a V S30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.

Kansas, Oklahoma, Texas↗

USGS2024

The 2023 US National Seismic Hazard Model: Ground-motion characterization for the conterminous United States

We update the ground-motion characterization for the 2023 National Seismic Hazard Model (NSHM) for the conterminous United States. The update includes the use of new ground-motion models (GMMs) in the Cascadia subduction zone; an adjustment to the central and eastern United States (CEUS) GMMs to reduce misfits with observed data; an updated boundary for the application of GMMs for shallow, crustal earthquakes in active tectonic regions (i.e. western United States (WUS)) and stable continental regions (i.e. CEUS); and the use of improved models for the site response of deep sedimentary basins in the WUS and CEUS. Site response updates include basin models for the California Great Valley and for the Portland and Tualatin basins, Oregon, as well as long-period basin effects from three-dimensional simulations in the Greater Los Angeles region and in the Seattle basin; in the CEUS, we introduce a broadband (0.01- to 10-s period) amplification model for the effects of the passive-margin basins of the Atlantic and Gulf Coastal Plains. In addition, we summarize progress on implementing rupture directivity models into seismic hazard models, although they are not incorporated in the 2023 NSHM. We implement the ground-motion characterization for the 2023 NSHM in the US Geological Survey’s code for probabilistic seismic hazard analysis, nshmp-haz-v2 , and present the sensitivity of hazard to these changes. Hazard calculations indicate widespread effects from adjustments to the CEUS GMMs, from the incorporation of Coastal Plain amplification effects, and from the treatment of shallow-basin and out-of-basin sites in the San Francisco Bay Area and Los Angeles region, as well as locally important changes from subduction-zone GMMs, and from updated and new WUS basins.

conterminous United States↗

USGS2024

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

California↗

USGS2024

Recent applications of the USGS National Crustal Model for Seismic Hazard Studies

The U.S. Geological Survey is developing the National Crustal Model (NCM) for seismic hazard studies to facilitate modeling site, path, and source components of seismic hazard across the conterminous United States. The NCM is composed of a 1km grid of geophysical profiles, extending from the Earth’s surface into the upper mantle. It is constructed from a threedimensional (3D) geologic framework and geophysical rules that use (1) a petrologic and mineral physics database; (2) a 3D temperature model; and (3) a calibrated rock type- and age-dependent porosity model. Parameters needed to estimate site response for existing ground motion models (GMMs), including the time-averaged velocity in the upper 30 meters (VS30), the depths to 1.0 and 2.5 km/s shear-wave velocity (Z1.0 and Z2.5), and sediment thickness, can be computed from the NCM. As GMMs continue to improve in the future, other metrics could also be extracted or derived from the NCM, such as fundamental period, site attenuation (ko), a fully frequency-dependent site response function, or 3D geophysical volumes for wavefield simulations. Application of the NCM may also benefit other aspects of seismic hazard analysis, including better accounting for path-dependent attenuation and geometric spreading, more accurate estimation of earthquake source properties such as hypocentral location and stress drop, and calculation of crustal strength profiles that inform estimates of the base of seismicity.

conterminous United States↗

USGS2024

The 2023 U.S. 50-state National Seismic Hazard Model: Changes in 2023 compared to 2018 ground motions

We present the 2023 U.S. National Seismic Hazard Model (NSHM) for all 50 states that applies new smoothed seismicity, fault rupture, and ground motion models. New data and methods are introduced in the 2023 earthquake rupture forecast that include: new earthquake catalogs - excluding induced earthquakes, alternative declustering methods, spatially smoothed seismicity distributions, full-catalog scaled rates to account for aftershocks, updated CEUS-WUS attenuation boundary, new magnitude-scaling equations, new geodetic and geologic deformation models, and alternative fault system solutions accounting for a more complete representation of epistemic uncertainty potential for earthquake generation in Alaska, Hawaii, and the conterminous U.S. Improved ground motion models consider new Next Generation Attenuation NGASubduction, modified NGA-East, and adjustments to account for regional biases in ground shaking observations. Semi-empirical and 3D simulations of ground motion are applied to account for shaking at 21 oscillator periods, 2 peak motions, and 8 site conditions. Site effects models are constructed for western U.S. basins (Seattle, Portland/Tualatin, San Francisco, Central Valley of California, Los Angeles, and Salt Lake City) and for sites with deep sedimentary wedges found across the central and eastern U.S. Gulf Coast and Atlantic coastal plain regions. These models result in substantial changes compared to the older NSHMs and are differentiated for the earthquake rupture forecast and ground motion model changes to display sensitivities and impacts.

Conference Paper↗

USGS2024

Methods to evaluate and improve the modeling of rupture directivity in assessment of seismic hazard

In recent years, there have been several advancements related to the modelling of near-source effects of earthquake rupture on strong ground shaking, leading to an improved characterization of ground motions and resulting seismic hazard. Some of these modifications have stemmed from physics-based numerical modelling of the earthquake rupture process, using physics-based dynamic rupture simulations. These contributions have led to a better understanding of how fault rupture characteristics, geometry, and the style of faulting can interact with the hypocenter-dependence on the path from source to site that may ultimately guide the development of seismic directivity models. Moving forward, the application of modern techniques can be used to incorporate these source characteristics and near-fault ground motion behavior that contribute to the azimuthally varying effects that result in rupture directivity. One example is the application of machine learning methods to support more automated integration of new predictor variables in model development and open more evaluation opportunities to access residuals. Here, we utilize several techniques to take advantage of the plethora of synthetic data and its ability to supplement preexisting trends observed in data. We showcase two examples of how models can be either developed, expanded upon, or constrained using artificial neural network model (ANNs). We evaluate the performance of the ANN with existing methods, comparing misfit, potential limitations, and ability to continue to improve upon these methods in the future. One approach uses a set of simulations with corresponding synthetic ground motions from the Southern California Earthquake Center (SCEC) CyberShake study to develop a ground motion model adapted to incorporate seismic directivity information using an ANN. This large database (TBs) enables us to train the model to capture magnitude, period, and distance variations and how these parameters relate to amplification from hypocenters located along finite-faults. In some cases, there is reduced misfit from better representing source features that aren’t included in base ground motion models that neglect hypocenter location (e.g. azimuthal variation, source-to-site terms). Another ANN method uses a shallow-layered neural network model to better fit a hypocenter-independent model. This method adjusts the median and aleatory variability to account for the averaged impact of various hypocenter distributions to fit the underlying directivity adjustment model. This method serves as a template to apply to other directivity models, improving computational efficiency and more readily enabling integration in hazard codes.

California↗

USGS2023

The 2023 US 50-State National Seismic Hazard Model: Overview and implications

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.

Earthquake Spectra↗

USGS2023

Sediment thickness map of United States Atlantic and Gulf Coastal Plain Strata, and their influence on earthquake ground motions

With the recent successful accounting of basin depth ground-motion adjustments in seismic hazard analyses for select areas of the western United States, we move toward implementing similar adjustments in the Atlantic and Gulf Coastal Plains by constructing a sediment thickness model and evaluating multiple relevant site amplification models for central and eastern United States seismic hazard analyses. We digitize and combine existing sediment thickness data sets into a composite surface that delineates the base of Cretaceous sediments under the Atlantic Coastal Plain and the base of Mesozoic sediments under the Gulf Coastal Plain. Amplification models dependent on sediment thickness, site natural period, and source-to-site path length are compared with data sets of observed ground motions to evaluate the ability of the new models to improve ground motion estimates. We find that the amplification models can account for observed trends in sediment-thickness and period-dependent residuals, but some tuning is required. For example, the model of Chapman and Guo requires a reference V S 30 , the time-averaged shear-wave velocity within 30 m of the Earth’s surface, for non-Coastal Plain sites, which we estimate to be between about 1 and 2 km/s. Along with our sediment thickness model, we estimate a velocity profile for application to the Harmon et al. site-natural-period-based model in order to best match the Chapman and Guo period dependence for a broad range of sediment thicknesses. The Next Generation of Attenuation models for the eastern United States Gulf Coast path-based adjustment models can also account for seismic attenuation in the Coastal Plain sediments and reduce the standard deviation of total residuals. If enacted in the U.S. Geological Survey National Seismic Hazard Model, these amplification models will reduce predicted short-period (<1 s) and increase predicted long-period (>1 s) ground motions in the Coastal Plains appreciably.

Earthquake Spectra↗

USGS2023

Ground‐motion variability from kinematic rupture models and the implications for nonergodic probabilistic seismic hazard analysis

The variability of earthquake ground motions has a strong control on probabilistic seismic hazard analysis (PSHA), particularly for the low frequencies of exceedance used for critical facilities. We use a crossed mixed‐effects model to partition the variance components from simulated ground motions of M w "> M w 7 earthquakes on the Salt Lake City segment of the Wasatch fault zone. Total variability of simulated ground motions is approximately equivalent to empirical models. The high contribution from rupture speed suggests an avenue to reducing variability through research on the causes and predictions of rupture speed on specific faults. Simulations show a strong spatial heterogeneity in the variability that manifests from directivity effects. We illustrate the impact of this spatial heterogeneity on hazard using a partially nonergodic PSHA framework. The results highlight the benefit of accounting for directivity effects in nonergodic PSHA, in which models that account for additional processes controlling ground motions are paired with reductions in the modeled ground‐motion variability.

Salt Lake City segment of the Wasatch fault zone↗

USGS2023

Investigations of ambient noise velocity variations in a region of induced seismicity near Greeley, Colorado

Wastewater injection has induced earthquakes in Northeastern Colorado since 2014. We apply ambient noise correlation techniques to determine temporal changes in seismic velocities in the region. We find no clear correlation between seismic velocity fluctuations and either injection volumes or seismicity patterns. We do observe apparent annual variations in velocity that may be associated with hydrologic loading or thermoelastic strain. In addition, we model uniform and vertically localized velocity perturbations, and measure the velocity change with 1D synthetic seismograms. Our results indicate that our methods underestimate the known velocity change, especially at shorter station distances and when variations are restricted to a horizontal layer. If injection does cause measurable velocity changes, its effect is likely diluted in cross correlations due to its localized spatial extent around injection wells.

Colorado↗

USGS2023

Magnitude conversion and earthquake recurrence rate models for the central and eastern United States

Development of Seismic Source Characterization (SSC) models, which is an essential part of Probabilistic Seismic Hazard Analyses (PSHA), can help forecast the temporal and spatial distribution of future damaging earthquakes (𝑀 w ≥ 5) in seismically active regions. Because it is impossible to associate all earthquakes with known faults, seismic source models for PSHA often include sources of diffuse seismicity in which future earthquake scenarios are not localized on mapped faults. These sources of diffuse seismicity are referred to as area source zones, distributed seismicity zones, or just source zones. During the early years of PSHA studies, it was assumed that earthquakes in seismotectonic zones have (1) uniform spatial distribution, (2) Poisson temporal distribution, and (3) exponential magnitude distribution (NRC, 2012). In seismically active regions (e.g., the Western United States), where active faults are readily identified, models of the spatial distribution of earthquakes include both the fault source geometries and the distributed seismicity (background) source zones. Source characterization of active faults is complemented by paleoseismic studies with estimates of earthquake magnitudes, dates of occurrences, and slip rates, which provide important information for PSHA studies. In the Central and Eastern United States (CEUS) very few Quaternary-active faults have the requisite information for use in PSHA (i.e., fault geometry and dimensions, event rates or slip rates, etc.), and we lack knowledge about the causative faults for most observed seismicity in the region. As a result, area source zones are frequently used in site-specific PSHA in the CEUS to represent diffuse seismicity that cannot be associated with faults. However, there are examples of active fault sources in the CEUS, such as the Meers fault, the Cheraw fault, and New Madrid region, where individual faults can be characterized. The source characterization models for background seismicity are based, to a large extent, on an assumption that spatial distribution of historical and recorded seismicity will not change substantially for time periods of interest for PSHA (approximately the next 50-100 years for engineered structures). Furthermore, studies such as those by Kafka (2007, 2009) found a correlation between the locations of small- to moderate-magnitude earthquakes and the locations of large-magnitude earthquakes, indicating that we can, with some level of confidence, use the spatial pattern of smaller earthquakes to forecast the future pattern of damaging earthquakes. Within background seismicity zones, the earthquake rate forecast is developed using spatial smoothing of the small to moderate magnitude events in earthquake catalogs. Different methodologies are used for this purpose and can predict varying distributions of seismicity rates. This in turn affects the results of a seismic hazard analysis. The U.S. Geological Survey (USGS) and Nuclear Regulatory Commission (NRC) use different methods for computing spatially smoothed seismicity rates in the CEUS; the USGS uses kernel-based spatial smoothing methods in developing the National Seismic Hazard Model (NSHM), and the method adopted in the Central and Eastern United States Seismic Source Characterization (CEUS-SSC) project is used when evaluating seismic hazard for nuclear power plant siting. These methods are described and the impact on seismic hazard are evaluated in this Research Information Letter (RIL). Another important input to estimating the rate of distributed seismicity is event magnitudes listed in earthquake catalogs. A substantial source of uncertainty in catalogs is the magnitude assigned to a given earthquake. Numerous different magnitude types exist, with each magnitude type computed in a different way. Therefore, for the sake of consistency, both the CEUS-SSC and the USGS NSHM have attempted to assemble a complete catalog with a uniform magnitude determination. To this end, moment magnitude, 𝑀 w , which is a physics-based measurement, has been adopted as the standard. However, 𝑀 w was not computed routinely until the past few decades. To address this issue, the CEUS-SSC conducted extensive analyses to determine conversion equations from which to take a routinely computed network (e.g., 𝑀 L or 𝑚 bLg ) and convert it into 𝑀 w . Another issue with using 𝑀 w is that it becomes increasingly difficult to compute for earthquakes with 𝑀 less than ~4. This study investigates the effects of moment magnitude estimation and spatial smoothing methods on estimation of the earthquake rate forecast and on seismic hazard. We investigate the validity of the magnitude conversion equations and their associated uncertainties by applying them to a case study for induced earthquakes in southern Kansas and northern Oklahoma, and summarize the use of the decay of the seismic coda to estimate 𝑀 w for small earthquakes (𝑀 w < 4. Furthermore, the study documents a comparison and assessment of background seismicity smoothing methods implemented by the USGS for the NSHM and used by the CEUS-SSC for siting nuclear facilities based on probabilistic seismic hazard estimates from multiple source zones in the CEUS and for multiple sites.

central and eastern United States↗

USGS2023

Ground motion and seismic hazard in the central and eastern United States

This report describes work carried out under the U.S. Nuclear Regulatory Commission (NRC) Interagency Agreement to the U.S. Geological Survey (USGS) “Research to Support NRC’s Seismic Hazard Analyses” for Task 3, “Seismic Hazard and Ground Motion Models.” The focus of this work has been on evaluation of the Next Generation Attenuation (NGA)-East groundmotion models (GMMs) with available ground-motion data and evaluation of alternative methods for characterizing epistemic uncertainty for probabilistic seismic hazard analysis (PSHA). When the Interagency Agreement commenced, the USGS’s National Seismic Hazard Model (NSHM) was being updated, and a significant part of the update for the 2018 NSHM included the introduction of new GMMs for the central and eastern United States (CEUS) (Petersen et al., 2020). In addition to the implementation of the then-recently developed NGA-East GMMs (Goulet et al., 2018), the ground-motion characterization for the CEUS in the 2018 NSHM also included a logic-tree branch with weights applied to the updated “adjusted seed” models that were developed as part of the NGA-East process and in updates by the GMM developers. The Statement of Work for Task 3 of the NRC Interagency Agreement to the USGS included the following parts: (1) Describe technically acceptable approaches in combining GMMs for use in PSHA calculations; (2) Evaluate the effect of using different sets of GMMs (NGA-East SSHAC versus NGA-East USGS) on PSHA calculations; (3) Describe the results of the GMM testing against recorded data, and provide a recommendation on the GMMs application for use in the PSHA; (4) Evaluate the impacts of recently updated individual GMMs on the published NGAEast models; and (5) Submit a final Technical Letter Report documenting results of this task. We present results from this work in two sections: (Chapter 1) Updated Central and Eastern United States Ground Motions and Ground-Motion Analyses; and (Chapter 2) Approaches to Combining Ground-Motion Models for Probabilistic Seismic Hazard Analysis in the Central and Eastern United States.

central and eastern United States↗

USGS2022

U.S. Geological Survey coastal plain amplification virtual workshop

In early October of 2020, the U.S. Geological Survey (USGS) held a virtual workshop to discuss Gulf and Atlantic Coastal Plains site-response models. Earthquake researchers came together to assess (1) research related to proposed Coastal Plains amplification models and (2) USGS plans for implementing these models. Presentations spanned a broad range of topics from Atlantic and Gulf Coastal Plains geophysical properties including seismic velocity and attenuation, to ground motion amplification models and their impacts on seismic hazard. Interspersed with these presentations were discussions regarding the definition and extent of the Atlantic and Gulf Coastal Plains, potential complexities of wave propagation in the Atlantic and Gulf Coastal Plains, and problems that need to be overcome to implement various proposed site-response models. Based on feedback from this workshop, the USGS working group on Coastal Plain Amplification is considering applying published models that depend on sediment thickness. The working group is also exploring potential application of models that depend on the length of path traversed across the Coastal Plain, including the Gulf Coastal Plain ground-motion model adjustments from the Next Generation Attenuation Relationships for the Eastern United States.

Gulf and Atlantic Coast Plains↗

USGS2022

Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada

We present a framework to evaluate the inclusion of candidate basin depth models in the U.S. Geological Survey National Seismic Hazard Model. We compute intensity measures (peak and spectral amplitudes) from uniformly processed earthquake ground motions in and around the basin of interest and compare these to ground-motion model (GMM) estimates over a range of oscillator periods. The GMMs use depth to specific shear-wave velocity isosurfaces (Z x ) as a proxy for basin depth. We quantify whether the GMM estimates using Z x from the candidate basin depth model outperform the default estimates based on V S30 (the time-averaged shear wave velocity in the upper 30 m). We partition GMM residuals into event and site terms and compare site terms for stations within the basin to non-basin sites. We apply this framework to the greater Reno, Nevada, region, which has shallow basin depths (less than 450 m) and empirical amplifications of up to a factor of 2.2 at 1.0 s. There are no strong trends in site terms with basin depth, and the use of Z x values from the new candidate basin model shows marginal improvement of GMM total residuals compared to the default V S30 -based model (the condition of no relative basin amplification).

Nevada↗

USGS2022

Sediment thickness and ground motion site amplification along the United States Atlantic and Gulf Coastal Plains

Past and present research on earthquake ground motions along the Atlantic and Gulf Coastal Plains and Mississippi Embayment show significant period-dependent site response that is not presently accounted for in ground motion models. These deviations are strongly correlated with the thickness of Mesozoic and younger syn- and post-rift sediments. With the recent incorporation of deep basin depth measurements in the U.S. Geological Survey National Seismic Hazard Model for select regions in the western United States, we move toward a similar analysis in the greater Coastal Plains region by constructing a sediment thickness model and considering three new site response models conditioned on sediment thickness. As of the preparation of this conference paper, we have performed a preliminary evaluation of the Chapman and Guo model and find that the predicted ratio between pseudo-spectral accelerations for the Coastal Plains relative to the continental interior are broadly consistent with our independent dataset.

Atlantic and Gulf Coastal Plains↗

USGS2021

2021 U.S. National Seismic Hazard Model for the State of Hawaii

The 2021 U.S. National Seismic Hazard Model (NSHM) for the State of Hawaii updates the two-decades-old former model 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 models (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 smoothing methods, (2) earthquake rate forecasts based on three temporally varying 60-year time periods, (3) maximum magnitude models that extend to larger earthquakes than previously considered, (4) a separate Kīlauea-specific seismogenic caldera collapse model which accounts for clustered event behavior observed during the 2018 eruption, and (5) fault ruptures that consider historic 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 modeled using western U.S. and Hawaii specific empirical equations and provide shaking forecasts for eight site classes. For most sites the new model results in similar spectral accelerations as those in the 2001 NSHM, with a few exceptions caused mostly by GMM changes. Ground motions are 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.

Hawai'i↗

USGS2021

Automated detection of clipping in broadband earthquake records

Because the amount of available ground‐motion data has increased over the last decades, the need for automated processing algorithms has also increased. One difficulty with automated processing is to screen clipped records. Clipping occurs when the ground‐motion amplitude exceeds the dynamic range of the linear response of the instrument. Clipped records in which the amplitude exceeds the dynamic range are relatively easy to identify visually yet challenging for automated algorithms. In this article, we seek to identify a reliable and fully automated clipping detection algorithm tailored to near‐real‐time earthquake response needs. We consider multiple alternative algorithms, including (1) an algorithm based on the percentage difference in adjacent data points, (2) the standard deviation of the data within a moving window, (3) the shape of the histogram of the recorded amplitudes, (4) the second derivative of the data, and (5) the amplitude of the data. To quantitatively compare these algorithms, we construct development and holdout datasets from earthquakes across a range of geographic regions, tectonic environments, and instrument types. We manually classify each record for the presence of clipping and use the classified records. We then develop an artificial neural network model that combines all the individual algorithms. Testing on the holdout dataset, the standard deviation and histogram approaches are the most accurate individual algorithms, with an overall accuracy of about 93%. The combined artificial neural network method yields an overall accuracy of 95%, and the choice of classification threshold can balance precision and recall.

Seismological Research Letters↗

USGS2021

A big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma

Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude ( ⁠ M w "> M w Mw ⁠ ) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally M w < 4 "> M w < 4 Mw<4 ⁠ ) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this, magnitudes of small earthquakes and statistics derived from them can be biased. Furthermore, because small earthquakes are much more numerous than large ones, many applications, such as seismic hazard modeling, depend critically on analysis of events characterized by magnitudes other than M w "> M w Mw ⁠ . To assess this problem, we apply coda envelope analysis to reliably determine moment magnitudes for a case study of small earthquakes from northern Oklahoma and southern Kansas. Not surprisingly, we find significant differences among M L "> M L ML ⁠ , m b L g "> m b L g mbLg ⁠ , and M w "> M w Mw for M ∼2–4 earthquakes examined here. More troublingly, we find that relations designed to convert other magnitudes to M w "> M w Mw ⁠ , which are relied upon for important applications such as seismic hazard analysis, often increase rather than decrease this bias for our dataset. In our case study, we find that converted magnitudes can result in a systematic bias sometimes exceeding 0.5 magnitude units, a difference that typically corresponds to a factor of ∼3 in seismicity rate. Moreover, we find a correspondingly large bias in Gutenberg–Richter b ‐values, controlled primarily by inaccurate magnitude scaling in the conversion relationships. Although this study focuses on a relatively small geographic area, we can expect that similar issues exist with varying severity in other regions. Therefore, magnitudes of small earthquakes and their associated statistics, including seismicity rates and b ‐values, should be treated with caution.

Kansas, Oklahoma↗