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The 2023 National Seismic Hazard Model (NSHM; Petersen et al., 2023) has two major components – a seismic source characterization (SSC) model and a ground motion characterization (GMC) model. The US Geological Survey (USGS) established separate panels to review and provide input on these two models. Both panels are advisory, meaning that they provide input on technical issues for consideration by the USGS NSHM team, but they do not have decision making authority. Here, we report on the activities and recommendations of the Ground Motion Characterization Panel, made up of the authors of this review. Final modeling decisions are presented in separate USGS documents, including Petersen et al., (2023) and Moschetti et al., (2023). Where modeling decisions depart from our recommendations, the rationale is explained in those publications.

ABSTRACT: A duration ground-motion model for crustal earthquakes based on the normalized Arias intensity (IA) is developed. Two sets of seismological simulations are used to constrain the form and scaling of the duration model. Simulations using a 3D crustal model show that an additive model for the source, path, and site terms captures the physical behavior of duration better than a multiplicative model for the site term. Stochastic finite-fault simulations are used to constrain the saturation of the large-magnitude scaling at short distances. The duration model is developed in two parts: a duration model for the time interval between 5% and 75% of the normalized Arias intensity (D5−75) and a duration model for the ratio of the D5−X/D5−75 duration for X values from 10 to 95. Together, these two models provide a more complete description of the evolution of the seismic energy with time than a single duration metric. A new aspect of the statistical model for duration is the inclusion of a random effect for the path term in addition to random effects for the source and site terms. The source and site random effects are modeled as scale factors on the duration, whereas the path-term random effect is a scale factor on the distance slope. The distribution of the duration residuals has a skewness that is between the skewness of a lognormal distribution and the symmetry of a normal distribution. The final duration aleatory variability is modeled by a power-normal distribution with an exponent of 0.3, which accounts for the amplitude dependence of the aleatory variability of the duration with smaller aleatory variability for large-magnitude events and larger aleatory variability for small-magnitude events as compared to the variability from a lognormal distribution.

Site response estimates from one-dimensional (1D) site response analyses (SRAs) carry inaccuracies due to modeling and parametric errors. Modeling errors are due to the condensation of the three-dimensional (3D) wave propagation phenomenon to the vertical propagation of a horizontally polarized wave through a soil column, and parametric errors are due to the incomplete knowledge of the distributions of soil parameters, leading to the selection of nonoptimal input parameters for a site of interest. While parametric errors are traditionally handled using different soil parameters (e.g. alternative shear-wave velocity profiles), modeling errors are generally neglected. This paper proposes an approach for conducting linear elastic 1D SRAs to improve site response predictions and account for modeling errors. First, ground-motion data from borehole array sites are collected, processed, and screened for appropriateness (e.g. expected shear strains lower than 0.01%, signal-to-noise ratio higher than 3). Second, 1D SRA predictions in terms of transfer functions and amplification factors are compared against observations, and the discrepancies are quantified as residuals. Finally, the residuals are partitioned into a model bias term (Formula presented.), a site term (Formula presented.) with standard deviation (Formula presented.), and a event- and site-specific remaining residual (Formula presented.) with standard deviation (Formula presented.). Values for (Formula presented.) and (Formula presented.) for forward predictions are recommended. The sensitivity of the site response residuals to region, site type (1D- or 3D-like), and the applicability of findings to outcropping applications are discussed, and an example application for a hypothetical project site is presented.

One-dimensional site response analysis (1D SRA) remains the state of practice to estimate site-specific seismic response, despite the ample evidence of discrepancies between observations and 1D SRA-based predictions. These discrepancies are due to errors in the input parameters, intrinsic limitations in the predicting capabilities of 1D SRAs even for sites relatively compliant with the 1D SRA assumptions, and the inability of 1D SRAs to model three-dimensional (3D) wave propagation phenomena. This article aims at reducing 1D SRA mispredictions using small-strain damping profiles factored by a damping multiplier (Dmul) and randomized shear-wave velocity (VS) profiles. An approach for conducting 1D SRAs for site-specific site response assessment is developed to reduce the 1D SRA errors in magnitude and variability. First, sites from a database of 534 downhole sites are classified as 1D- or 3D-like, depending on the substructure conditions inferred from observed transfer functions. Second, data from the 1D-like sites are compared against predictions from 1D SRAs conducted using various trials of Dmul and VS standard deviations (Formula presented.) for VS randomization. Third, Dmul and (Formula presented.) are selected based on their combined ability to reduce the root mean square error (RMSE) in SRA predictions. Results indicate that 1D SRAs conducted with Dmul = 3 and (Formula presented.) lead to an overall minimum RMSE and thus provide more accurate site response estimates. The use of these parameters in forward SRA predictions is discussed in a companion paper.

ABSTRACT: The horizontal-to-vertical spectral ratios from microtremor (mHVSR) data obtained at 196 seismic stations in California are used to evaluate three alternative microtremor-based proxies for site amplification for use in ground-motion models (GMMs): the site fundamental period (f0), the period-dependent amplitude of the mHVSR(T), and the normalized amplitude of the mHVSR(T). The alternative parameters are evaluated for the sites with and without measurements of VS30. If a VS30 measurement is not available for a site, then f0 has the highest correlation with the site amplification for short periods (T

One-dimensional site response analyses (1D SRAs) with shear-wave velocity (VS) randomization are commonly performed to estimate median site-specific amplification factors (AFs) under the implicit assumption that this approach yields a realistic response. In this work, an investigation is conducted to determine the appropriate amount of VS randomization (σlnVs) needed to capture a median response that accounts for 2D VS spatial variability effects. Results from 2D SRAs and 1D SRAs with VS randomization show that the median 2D seismic responses are generally higher than 1D responses at the site’s fundamental frequency, and that higher VS variability has a mild impact on the median 2D seismic response amplitude at the fundamental frequency, whereas it significantly reduces the median 1D response. Findings indicate that the 84th percentile AFs based on 1D SRAs conducted with VS randomization using σlnVs = 0.25, approximate well with the more realistic median 2D SRA-based AFs around the fundamental frequency, while the 70th to 60th percentiles might be more appropriate at higher frequencies. The benefit of using percentiles of the 1D SRA-based AFs higher than the median is shown for different site conditions and supported by comparisons against empirical data from four downhole sites.

This paper summarizes a ground-motion database developed for the NGA-Sub Project. The database consists of two- and three-component ground-motion recordings from selected earthquakes in subduction zones. The database also includes the supporting data such as source, path, and site metadata. The earthquakes are located in Japan, Taiwan, the Pacific Northwest region of North America, Alaska, Mexico, Central and South America, and New Zealand. The events in the database are classified as interface, intraslab, or outer-rise, and have magnitudes ranging from 4 to 9. The database includes more than 71,000 three-component recordings, most of which are from digital accelerograms. The database includes PGA, PGV, pseudo-spectral acceleration for eleven damping values between 0.5% and 30%, Fourier amplitude spectra for frequencies from 0.1 to 100 Hz, and significant-shaking durations based on Arias Intensity. These data are analyzed in the project to model various ground-motion properties.

Computational simulations have become central to the seismic analysis and design of major infrastructure over the past several decades. Most major structures are now “proof tested” virtually through representative simulations of earthquake-induced response. More recently, with the advancement of high-performance computing (HPC) platforms and the associated massively parallel computational ecosystems, simulation is beginning to play a role in increased understanding and prediction of ground motions for earthquake hazard assessments. However, the computational requirements for regional-scale geophysics-based ground motion simulations are extreme, which has restricted the frequency resolution of direct simulations and limited the ability to perform the large number of simulations required to numerically explore the problem parametric space. In this article, recent developments toward an integrated, multidisciplinary earth science-engineering computational framework for the regional-scale simulation of both ground motions and resulting structural response are described with a particular emphasis on advancing simulations to frequencies relevant to engineered systems. This multidisciplinary computational development is being carried out as part of the US Department of Energy (DOE) Exascale Computing Project with the goal of achieving a computational framework poised to exploit emerging DOE exaflop computer platforms scheduled for the 2022–2023 timeframe.

The existing observational database of the regional-scale distribution of strong ground motions and measured building response for major earthquakes continues to be quite sparse. As a result, details of the regional variability and spatial distribution of ground motions, and the corresponding distribution of risk to buildings and other infrastructure, are not comprehensively understood. Utilizing high-performance computing platforms, emerging high-resolution, physics-based ground motion simulations can now resolve frequencies of engineering interest and provide detailed synthetic ground motions at high spatial density. This provides an opportunity for new insight into the distribution of infrastructure seismic demands and risk. In the work presented herein, the EQSIM fault-to-structure computational framework described in a companion paper, McCallen et al., is employed to investigate the regional-scale response of buildings to large earthquakes. A representative M = 7.0 strike-slip event is used to explore the distribution and amplitude of building demand, and comparisons are made between building response computed with fault-to-structure simulations and building response computed with existing measured near-fault earthquake records. New information on the distribution and variability of building response from high-performance parallel simulations is described and analyzed, and favorable first comparisons between building response predicted with both fault-to-structure simulations and real ground motions records are presented.

Ground-motion simulations generated from physics-based wave propagation models are gaining increasing interest in the engineering community for their potential to inform the performance-based design and assessment of infrastructure residing in active seismic areas. A key prerequisite before the ground-motion simulations can be used with confidence for application in engineering domains is their comprehensive and rigorous investigation and validation. This article provides a four-step methodology and acceptance criteria to assess the reliability of simulated ground motions of not historical events, which includes (1) the selection of a population of real records consistent with the simulated scenarios, (2) the comparison of the distribution of Intensity Measures (IMs) from the simulated records, real records, and Ground-Motion Prediction Equations (GMPEs), (3) the comparison of the distribution of simple proxies for building response, and (4) the comparison of the distribution of Engineering Demand Parameters (EDPs) for a realistic model of a structure. Specific focus is laid on near-field ground motions (

We report on high-performance computing (HPC) fully deterministic simulation of ground motions for a moment magnitude (Mw) 7.0 scenario earthquake on the Hayward fault resolved to 5 Hz using the SW4 finite-difference code. We computed motions obeying physics-based 3D wave propagation at a regional scale with an Mw 7.0 kinematic rupture model generated following Graves and Pitarka (2016). Both plane-layered (1D) and 3D Earth models were considered, with 3D subsurface material properties and topography interpolated from a model of the U.S. Geological Survey (USGS). The resulting ground-motion intensities cover a broader frequency range than typically considered in regional-scale simulations, including higher frequencies relevant for engineering analysis of structures. Median intensities for sites across the domain are within the reported between-event uncertainties (τ) of ground-motion models (GMMs) across spectral periods 0.2-10 s (frequencies 0.1-5 Hz). The within-event standard deviation ϕ of ground-motion intensity measurement residuals range 0.2-0.5 natural log units with values consistently larger for the 3D model. Source-normalized ratios of intensities (3D/ 1D) reveal patterns of path and site effects that are correlated with known geologic structure. These results demonstrate that earthquake simulations with fully deterministic wave propagation in 3D Earth models on HPC platforms produce broadband ground motions with median and within-event aleatory variability consistent with empirical models. Systematic intensity variations for the 3D model caused by path and site effects suggest that these epistemic effects can be estimated and removed to reduce variation in site-specific hazard estimates. This study motivates future work to evaluate the validity of the USGS 3D model and investigate the development of path and site corrections by running more scenarios.

We investigate the nonergodic behavior of ground motions from subduction zone earthquakes and crustal earthquakes in Japan using the National Research Institute for Earth Science and Disaster Resilience strong-motion flatfile together with various reference ergodic ground-motion models (GMMs). For the nonergodic path effects, our nonergodic GMM has two path effects terms: a cell-specific linear-distance scaling, denoted as δP2PQ, that mimics the effects of a 3D Q structure, and a source- and site-specific term related to the effects of the 3D velocity structure, denoted δP2PV. The resulting model provides spatially varying nonergodic source, site, and path terms. The GMM smoothly interpolates and extrapolates the nonergodic terms in space so that the GMM can be applied to any combination of source and site locations in the region. In regions where data are sparse, the median nonergodic terms will approach zero but with large epistemic uncertainty. Over the period range of 0-10 s, the ranges of the standard deviations of the nonergodic source, path, and site terms are 0.2-0.65, 0.25-0.40, and 0.15-0.40 natural log units, respectively. The fully nonergodic models lead to a 40%-55% decrease in the aleatory standard deviation compared to the reference ergodic GMMs. This large reduction in the aleatory standard deviation combined with the change in the median given by the nonergodic terms can exert a significant impact on the computed seismic hazard for the Japan region. [ABSTRACT FROM AUTHOR]

A duration ground-motion model for crustal earthquakes based on the normalized Arias intensity (IA) is developed. Two sets of seismological simulations are used to constrain the form and scaling of the duration model. Simulations using a 3D crustal model show that an additive model for the source, path, and site terms captures the physical behavior of duration better than a multiplicative model for the site term. Stochastic finite-fault simulations are used to constrain the saturation of the large-magnitude scaling at short distances. The duration model is developed in two parts: a duration model for the time interval between 5% and 75% of the normalized Arias intensity (D5-75) and a duration model for the ratio of the D5-X/D5-75 duration for X values from 10 to 95. Together, these two models provide a more complete description of the evolution of the seismic energy with time than a single duration metric. A new aspect of the statistical model for duration is the inclusion of a random effect for the path term in addition to random effects for the source and site terms. The source and site random effects are modeled as scale factors on the duration, whereas the path-term random effect is a scale factor on the distance slope. The distribution of the duration residuals has a skewness that is between the skewness of a lognormal distribution and the symmetry of a normal distribution. The final duration aleatory variability is modeled by a power-normal distribution with an exponent of 0.3, which accounts for the amplitude dependence of the aleatory variability of the duration with smaller aleatory variability for large-magnitude events and larger aleatory variability for small-magnitude events as compared to the variability from a lognormal distribution. [ABSTRACT FROM AUTHOR]

Ground-motion prediction equations (GMPEs) relate a ground-motion parameter (e.g. peak ground acceleration) to a set of explanatory variables describing the source, wave propagation path and site conditions. In the past five decades many hundreds of GMPEs for the prediction of PGA and linear elastic response spectral ordinates have been published. An accompanying paper discusses the pre-selection of GMPEs undertaken within the framework of the Global Earthquake Model (GEM) Global GMPEs project, coordinated by the Pacific Earthquake Engineering Research Center (PEER). Here, we discuss the following step undertaken to reduce the long list of pre-selected models down to a more manageable number for global hazard assessments. The procedure followed, consisting of an examination of themulti-dimensional (e.g. magnitude, distance and structural period) predicted ground-motion space in various ways and published quantitative tests of the GMPEs against observational data not used for their derivation, is discussed and illustrated for subduction zones.

Earthquake ground motions exhibit spatial variability manifest as random variations of Fourier amplitude and phase. These variations increase with frequency and distance between observations points (d), and introduce demands for lifeline systems and foundations. Spatially variable ground motions (SVGM) are quantified by: (1) apparent horizontal wave velocity (Vapp), which controls wave passage effects that shift Fourier phase; (2) lagged coherency, representing random phase variations; and (3) standard deviation terms representing Fourier amplitude variability. We examine empirical relations for the three SVGM sources through analysis of data from the Borrego Valley Differential Array (BVDA) in California and re-analysis of data from the LSST array in Taiwan, both having a number of stations at d < 120 m. We show that Vapp from the two arrays have medians of 2.1 and 2.6 km/s and natural log standard deviations of about 0.5. We show that previous models for lagged coherency and standard deviation from amplitude variability have bias, and propose revisions. We show that amplitude and coherency residuals from the baseline model are uncorrelated, although frequency-to-frequency residuals for both quantities are weakly correlated for small frequency offsets.

A model for horizontal peak ground strain (PGS) is developed in consideration of three fundamental contributions to spatially variable ground motion (SVGM): (1) spatial incoherence effects, which contribute to phase variability in a stochastic sense; (2) wave passage effects, which contribute to phase variability in a deterministic sense; and (3) amplitude variability. Previous models for each of these effects are reviewed and compared to array data from Borrego Valley, California. Published empirical models for coherency and amplitude variability are found to represent reasonably well the Borrego data. We extend previous work by considering correlations of amplitude and phase variability (generally found to be small) and characterizing the coherency-dependent probabilistic distribution of phase variability. Using the aforementioned amplitude and phase variability models, a procedure is developed to generate simulated acceleration records from a seed record. The procedure is applied to a suite of Northridge earthquake recordings to predict ground strains, which are found to be strongly dependent on the peak ground velocity (PGV) of the seed motion and the separation distance between the seed and simulated motions. The dependence of PGS on PGV saturates for large PGV (> 50 cm/sec).

A new approach is developed to incorporate the anisotropic path effects in ground motions due to the 3D velocity structure into nonergodic ground-motion models (GMMs) using the varying coefficient model (VCM) in a two-step process. The first step uses the VCM to estimate the spatially varying path term for each site separately with the spatial correlation based on the separation between earthquakes. The model for the correlation length varies as a function of rupture distance to reflect that, for a given separation between events, the path effects are more similar for longer path lengths. The second step uses the step-1 VCM results as the input to estimate path terms for a specific source location for any site location. The final model is a smooth spatially varying nonergodic path term that can be applied to any source-site pair. An example application of the proposed method using a subset of 600 scenarios of the v15.4 CyberShake simulation for T = 3 s response spectral values shows that nonergodic path terms can be significant, ranging from -0.8 to 0.8 ln units, which corresponds to factors of 0.45-2.23 in the median ground motion compared to the ergodic approach. With nonergodic path terms, the single-path aleatory variability for the nonergodic GMM is reduced to 0.34 ln units as compared to 0.52 ln units for single-station sigma without systematic path effects. A comparison of probabilistic hazards shows that the proposed approach leads to a nonergodic GMM that can capture the path effects seen in the CyberShake simulations in terms of both the median and the aleatory standard deviation. The resulting nonergodic GMM extends the applicability of the 3D simulation results to site-source pairs in the region and not limited to the locations of the simulations, making the simulation results more practical to use in seismic hazard studies. [ABSTRACT FROM AUTHOR]

One-dimensional site response analysis (1D SRA) remains the state of practice to estimate site-specific seismic response, despite the ample evidence of discrepancies between observations and 1D SRA-based predictions. These discrepancies are due to errors in the input parameters, intrinsic limitations in the predicting capabilities of 1D SRAs even for sites relatively compliant with the 1D SRA assumptions, and the inability of 1D SRAs to model three-dimensional (3D) wave propagation phenomena. This article aims at reducing 1D SRA mispredictions using small-strain damping profiles factored by a damping multiplier (D mul) and randomized shear-wave velocity (VS) profiles. An approach for conducting 1D SRAs for site-specific site response assessment is developed to reduce the 1D SRA errors in magnitude and variability. First, sites from a database of 534 downhole sites are classified as 1D- or 3D-like, depending on the substructure conditions inferred from observed transfer functions. Second, data from the 1D-like sites are compared against predictions from 1D SRAs conducted using various trials of D mul and VS standard deviations (σ ln V S ) for VS randomization. Third, D mul and σ ln V S are selected based on their combined ability to reduce the root mean square error (RMSE) in SRA predictions. Results indicate that 1D SRAs conducted with D mul = 3 and σ ln V S = 0. 25 lead to an overall minimum RMSE and thus provide more accurate site response estimates. The use of these parameters in forward SRA predictions is discussed in a companion paper. [ABSTRACT FROM AUTHOR]