National Seismic Hazard Model Research Articles

The 2023 US National Seismic Hazard Model: Subduction ground-motion models

The US Geological Survey National Seismic Hazard Models (NSHMs) are used to calculate earthquake ground-shaking intensities for design and rehabilitation of structures in the United States. The most recent 2014 and 2018 versions of the NSHM for the conterminous United States included major updates to ground-motion models (GMMs) for active and stable crustal tectonic settings; however, the subduction zone GMMs were largely unchanged. With the recent development of the next generation attenuation-subduction (NGA-Sub) GMMs, and recent progress in the utilization of “M9” Cascadia earthquake simulations, we now have access to improved models of ground shaking in the US subduction zones and the Seattle basin. The new NGA-Sub GMMs support multi-period response spectra calculations. They provide global models and regional terms specific to Cascadia and terms that account for deep-basin effects. This article focuses on the updates to subduction GMMs for implementation in the 2023 NSHM and compares them to the GMMs of previous NSHMs. Individual subduction GMMs, their weighted averages, and their impact on the estimated mean hazard relative to the 2018 NSHM are discussed. The updated logic trees include three of the new NGA-Sub GMMs and retain two older models to represent epistemic uncertainty in both the median and standard deviation of ground-shaking intensities at all periods of interest. Epistemic uncertainty is further represented by a three-point logic tree for the NGA-Sub median models. Finally, in the Seattle region, basin amplification factors are adjusted at long periods based on the state-of-the-art M9 Cascadia earthquake simulations. The new models increase the estimated mean hazard values at short periods and short source-to-site distances for interface earthquakes, but decrease them otherwise, relative to the 2018 NSHM. On softer soils, the new models cause decreases to the estimated mean hazard for long periods in the Puget Lowlands basin but increases within the deep Seattle portion of this basin for short periods relative to the 2018 NSHM.

Empirical ground-motion basin response in the California Great Valley, Reno, Nevada, and Portland, Oregon

We assess how well the Next-Generation Attenuation-West 2 (NGA-West2) ground-motion models (GMMs), which are used in the US Geological Survey’s (USGS) National Seismic Hazard Model (NSHM) for crustal faults in the western United States, predict the observed basin response in the Great Valley of California, the Reno basin in Nevada, and Portland and Tualatin basins in Oregon. These GMMs rely on site parameters such as the time-averaged shear-wave velocity ( VS) in the upper 30 m of Earth’s crust ( VS30) and depths to 1.0 and 2.5 km/s shear-wave isosurfaces ( Z1.0 and Z2.5) to capture basin effects and were developed using observations and simulations primarily from the Los Angeles region in southern California. Using ground-motion records from mostly small-to-moderate earthquakes and mixed-effects regression analysis, we find that the GMMs perform well with our local basin-depth models for the California Great Valley. With our local basin-depth models for Reno, the GMMs do not perform as well for this relatively shallow basin and exhibit little sensitivity to the basin parameters used in the NGA-West2 GMMs. We also find good performance for the local Z1.0 model across the Portland region, whereas the local Z2.5 model provides little predictive power except at sites in the deepest part of the Tualatin basin. Additional work could improve the performance of the site and basin terms in the NGA-West2 GMMs for regions with geologic structure different than the deep basins in southern California and the Great Valley. In addition, we find significant discrepancies among the GMMs in how the uncertainty in the ground motion varies with basin depth and pseudospectral period. Our results can help guide seismic hazard analyses on whether to include these local basin-depth models.

Disagreements in Geodetically Inferred Strain Rates in the Western US With Stress Orientations and Geologic Moment Rates

AbstractI employ an elasticity‐based method to invert a geodetically derived surface velocity field in the western US using for present‐day surface strain rate fields with uncertainties. The method uses distributed body forces in a thin elastic sheet and allows for discontinuities in velocity across creeping faults using the solution for dislocations in a thin elastic plate. I compare the strain rate fields with previously published stress orientations and moment rates from geological slip rate data and previous geodetic studies. Geologic and geodetic moment rates are calculated using slip rate and off‐fault strain rates from the 2023 US National Seismic Hazard Model (NSHM) deformation models. I find that computed total geodetic moment rates are higher than NSHM summed moment rates on faults for all regions of the western US except the highest deforming rate regions including the Western Transverse Ranges and the northern and southern San Andreas Fault (SAF) system in California. Computed geodetic moment rates are comparable to the moment rates derived from the geodetically based NSHM deformation models in all regions. I find systematic differences in orientations of maximum horizontal shortening rate and maximum horizontal compressive stress in the Pacific Northwest region and along much of the SAF system. In the Pacific Northwest, the maximum horizontal stress orientations are rotated counterclockwise 40–90° relative to the maximum horizontal strain rate directions. Along the SAF system, the maximum horizontal stresses are rotated systematically 25–40° clockwise (closer to fault normal) relative to the strain rates.

Integration of rupture directivity models for the US National Seismic Hazard Model

Several rupture directivity models (DMs) have been developed in recent years to describe the near-source spatial variations in ground-motion amplitudes related to propagation of rupture along the fault. We recently organized an effort toward incorporating these directivity effects into the US Geological Survey (USGS) National Seismic Hazard Model (NSHM), by first evaluating the community’s work and potential methods to implement directivity adjustments into probabilistic seismic hazard analysis (PSHA). Guided by this evaluation and comparison among the considered DMs, we selected an approach that can be readily implemented into the USGS hazard software, which provides an azimuthally varying adjustment to the median ground motion and its aleatory variability. This method allows assessment of the impact on hazard levels and provides a platform to test the DM amplification predictions using a generalized coordinate system, necessary for consistent calculation of source-to-site distance terms for complex ruptures. We give examples of the directivity-related impact on hazard, progressing from a simple, hypothetical rupture, to more complex fault systems, composed of multiple rupture segments and sources. The directivity adjustments were constrained to strike–slip faulting, where DMs have good agreement. We find that rupture directivity adjustments using a simple median and aleatory adjustment approach can affect hazard both from a site-specific perspective and on a regional scale, increasing ground motions off the end of the fault trace up to 30%–40% and potentially reducing it for sites along strike. Statewide hazard maps of California show that the change in shaking along major faults can be a factor to consider for assessing long-period [Formula: see text] near-source effects within the USGS NSHM going forward, reaching up to 10%–20%. Finally, we suggest consideration of minimum parameter ranges and baseline requirements as future DMs are developed to minimize single approach adaptations to enable more consistent application within both ground motion and hazard studies.

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 ( VS30) = 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 VS30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.

Robust Imaging of Fault Slip Rates in the Walker Lane and Western Great Basin From GPS Data Using a Multi‐Block Model Approach

AbstractThe Walker Lane (WL) in the western Great Basin (GB) is an active plate boundary system accommodating 10%–20% of the relative tectonic motion between the Pacific and North American plates. Its neotectonic framework is structurally complex, having hundreds of faults with various strikes, rakes, and crustal blocks with vertical axis rotation. Faults slip rates are key parameters needed to quantify seismic hazard in such tectonically active plate boundaries but modeling them in complex areas like the WL and GB is challenging. We present a new modeling strategy for estimating fault slip rates in complex zones of active crustal deformation using data from GPS networks. The technique does not rely on prior estimates of slip rates from geologic studies, and only uses data on the surface trace location, dip, and rake. The iterative framework generates large numbers of block models algorithmically from the fault database to obtain many estimates of slip rates for each fault. This reduces bias from subjective choices about how discontinuous faults connect and interact to accommodate strain. Each model iteration differs slightly in block boundary configuration, but all models honor geodetic and fault data, regularization, and are kinematically self‐consistent. The approach provides several advantages over bespoke models, including insensitivity to outlier data, realistic uncertainties, explicit mapping of off‐fault deformation, and slip rates that are more objective and independent of geologic slip rates. Comparisons to the U.S. National Seismic Hazard Model indicate that ∼80% of our geodetic slip rates agree with their geologic slip rates to within uncertainties.

Inverting Geodetic Strain Rates for Slip Deficit Rate in Complex Deforming Zones: An Application to the New Zealand Plate Boundary

AbstractThe potential for future earthquakes on faults is often inferred from inversions of geodetically derived surface velocities for locking on faults using kinematic models such as block models. This can be challenging in complex deforming zones with many closely spaced faults or where deformation is not readily described with block motions. Furthermore, surface strain rates are more directly related to coupling on faults than surface velocities. We present a methodology for estimating slip deficit rate directly from strain rate and apply it to New Zealand for the purpose of incorporating geodetic data in the 2022 revision of the New Zealand National Seismic Hazard Model. The strain rate inversions imply slightly higher slip deficit rates than the preferred geologic slip rates on sections of the major strike‐slip systems including the Alpine Fault, the Marlborough Fault System and the northern part of the North Island Fault System. Slip deficit rates are significantly lower than even the lowest geologic estimates on some strike‐slip faults in the southern North Island Fault System near Wellington. Over the entire plate boundary, geodetic slip deficit rates are systematically higher than geologic slip rates for faults slipping less than one mm/yr but lower on average for faults with slip rates between about 5 and 25 mm/yr. We show that 70%–80% of the total strain rate field can be attributed to elastic strain due to fault coupling. The remaining 20%–30% shows systematic spatial patterns of strain rate style that is often consistent with local geologic style of faulting.

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.

New Zealand specific consequence functions for seismic loss assessment

Quantitative seismic loss assessment has become an increasingly popular tool for evaluating the seismic performance of structures. The growth in popularity is largely in response to a desire to look beyond the traditional life safety performance objective and instead consider also economic losses and downtime due to earthquakes. A key step in the loss assessment calculation process is relating damage in both structural and nonstructural components to appropriate repair strategies and subsequently repair costs and repair times. This is achieved through the use of so-called consequence functions, which in this paper are derived specifically for the New Zealand context. Furthermore, a framework is established for other researchers and professional engineers to continue to build on and improve the initial dataset. It is shown that using New Zealand specific consequence functions can have a noticeable effect on estimates of expected annual loss when compared to a benchmark case using consequence functions from FEMA P-58. The opportunity is also taken to evaluate the impact of recent updates to the New Zealand National Seismic Hazard Model, with the results for a case-study building in Wellington indicating that the change in hazard has a far more significant effect on estimates of loss when compared to the choice of different consequence functions.

PSHA: Does It Deal with What It Is or What We Want It to Be?

Abstract In a recent opinion piece Albarello and Paolucci (2023; hereafter, AP23) provide their view as members of the past Seismic Group of the Commissione Grandi Rischi (CGR-SRS) in Italy, which represents the main scientific consultant for Italian Civil Protection, about the difficulty using probabilistic seismic hazard analysis (PSHA) models for building code purposes. Here, we refer to this specific kind of PSHA modeling as National Seismic Hazard Model (NSHM). We agree with AP23 that the topic is of great and general importance, and here we aim at contributing to this discussion by offering our perspective on two points that are at the heart of the matter, concluding that AP23 is misguided in how to deal with them. First, we assert that the credibility of an NSHM has to be rooted only in the use of the best available science, which includes a rigorous testing phase with observations, independent from the consequences in terms of risk. (PSHA deals with what it is.) Second, we claim that the difficulties in accepting a new NSHM with some major changes with respect to the previous model are mostly due to too rigid building code procedures that do not account for the epistemic uncertainty in the hazard estimates.

The United States Has an Updated Map of Earthquake Hazards

The new National Seismic Hazard Model shows where damaging earthquakes are likely to occur, informing public safety and infrastructure policies.

Earthquake Rupture Forecast Model Construction for the 2023 U.S. 50-State National Seismic Hazard Model Update: Central and Eastern U.S. Fault-Based Source Model

Abstract As part of the U.S. Geological Survey’s 2023 50-State National Seismic Hazard Model (NSHM), we make modest revisions and additions to the central and eastern U.S. (CEUS) fault-based seismic source model that result in locally substantial hazard changes. The CEUS fault-based source model was last updated as part of the 2014 NSHM and considered new information from the Seismic Source Characterization for Nuclear Facilities (CEUS-SSCn) Project. Since then, new geologic investigations have led to revised fault and fault-zone inputs, and the release of databases of fault-based sources in the CEUS. We have reviewed these databases and made minor revisions to six of the current fault-based sources in the NSHM, as well as added five new fault-based sources. Implementation of these sources follows the current NSHM methodology for CEUS fault-based sources, as well as the incorporation of a new magnitude–area relationship and updated maximum magnitude and recurrence rate estimates following the methods used by the CEUS-SSCn Project. Seismic hazard sensitivity calculations show some substantial local changes in hazard (−0.4g to 1.1g) due to some of these revisions and additions, especially from the addition of the central Virginia, Joiner ridge, and Saline River sources and revisions made to the Meers and New Madrid sources.

The 1886 Charleston, South Carolina, Earthquake: Intensities and Ground Motions

ABSTRACT The 1 September 1886 Charleston, South Carolina, earthquake was one of the largest preinstrumental earthquakes in eastern North America for which extensive contemporaneous observations were documented. The distribution of shaking was mapped shortly after the earthquake, and reconsidered by several authors in the late twentieth century, but has not been reconsidered with a modern appreciation for issues associated with macroseismic data interpretation. Detailed contemporary accounts have also never been used to map the distribution of numerical shaking intensities in the near field. In this study we reconsider macroseismic data from far-field accounts as well as detailed accounts of damage in the near field, estimating modified Mercalli intensity values at 1297 locations including over 200 definite “not felt” reports that delineate the overall felt extent. We compare the results to the suite of ground-motion models for eastern North America selected by the National Seismic Hazard Model, using a recently proposed mainshock rupture model and an average site condition for the locations at which intensities are estimated. The comparison supports the moment magnitude estimate, 7.3, from a recently proposed rupture model (Bilham and Hough, 2023). A ShakeMap constrained by model predictions and estimated intensities further illustrates this consistency, which we show is insensitive to rupture model details. Given the uncertainty of calibration relations for magnitudes close to 7, the overall intensity distribution provides a good characterization of shaking but cannot improve the independent moment magnitude estimate. We also identify a previously unrecognized early large aftershock that occurred 9–10 min after the mainshock, for which we estimate magnitude ∼5.6.

Review of Geodetic and Geologic Deformation Models for 2023 U.S. National Seismic Hazard Model

ABSTRACT We review five deformation models generated for the 2023 update to the U.S. National Seismic Hazard Model (NSHM), which provide input fault-slip rates that drive the rate of earthquake moment release. Four of the deformation models use the Global Positioning System-derived surface velocity field and geologic slip-rate data to derive slip-rate estimates (Evans, Pollitz, Shen-Bird, and Zeng), and one model uses geologic data (the “geologic model”). The correlation between the geologic model preferred slip rates and geodetically derived slip rates is high for the Pollitz, Zeng, and Shen-Bird models, and the median of all slip-rate models has correlation coefficient of 0.88. The median geodetic model slip rates are systematically lower than the preferred geologic model rates for faults with slip rates exceeding 10 mm/yr and systematically higher on faults with slip rates less than 0.1 mm/yr. Geodetically derived slip rates tend to the low end of the geologic model range along sections of the San Andreas fault and the Garlock fault, whereas they tend to be higher across north coast California faults. The total on-fault moment rates agree well across models with all rates within 18% of the median. Estimated off-fault strain rate orientations and styles vary considerably across models and off-fault moment rates vary more than on-fault moment rates. Path integrals across the western U.S. accounting for fault-slip rate and off-fault deformation are generally consistent with Pacific-North America plate motion with the median deformation rates recovering about 98% of the plate motion with about 20% of the total plate motion accommodated by off-fault strain rate. The geologic model, which has no off-fault deformation, accounts for about 82% of plate motion with fault slip. Finally, we make a recommendation for relative weighting of the models for the NSHM as well as several recommendations for future NSHM deformation model development.

Accounting for the Variability of Earthquake Rates within Low-Seismicity Regions: Application to the 2022 Aotearoa New Zealand National Seismic Hazard Model

ABSTRACT The distribution of earthquakes in time and space is seldom stationary, which could hinder a robust statistical analysis, particularly in low-seismicity regions with limited data. This work investigates the performance of stationary Poisson and spatially precise forecasts, such as smoothed seismicity models (SSMs), in terms of the available training data. Catalog bootstrap experiments are conducted to: (1) identify the number of training data necessary for SSMs to perform spatially better than the least-informative Uniform Rate Zone (URZ) models; and (2) describe the rate temporal variability accounting for the overdispersion and nonstationarity of seismicity. Formally, the strict-stationarity assumption used in traditional forecasts is relaxed into local and incremental stationarity (i.e., a catalog is only stationary in the vicinity of a given time point t) along with self-similar behavior described by a power law. The results reveal rate dispersion up to 10 times higher than predicted by Poisson models and highlight the impact of nonstationarity in assuming a constant mean rate within training-forecast intervals. The temporal rate variability is translated into a reduction of spatial precision by means of URZ models. First, counting processes are devised to capture rate distributions, considering the rate as a random variable. Second, we devise a data-driven method based on geodetic strain rate to spatially delimit the precision of URZs, assuming that strain/stress rate is related to the timescales of earthquake interactions. Finally, rate distributions are inferred from the available data within each URZ. We provide forecasts for the New Zealand National Seismic Hazard Model update, which can exhibit rates up to ten times higher in low-seismicity regions compared with SSMs. This study highlights the need to consider nonstationarity in seismicity models and underscores the importance of appropriate statistical descriptions of rate variability in probabilistic seismic hazard analysis.

Implementing Non-Poissonian Forecasts of Distributed Seismicity into the 2022 Aotearoa New Zealand National Seismic Hazard Model

ABSTRACT Seismicity usually exhibits a non-Poisson spatiotemporal distribution and could undergo nonstationary processes. However, the Poisson assumption is still deeply rooted in current probabilistic seismic hazard analysis models, especially when input catalogs must be declustered to obtain a Poisson background rate. In addition, nonstationary behavior and scarce earthquake records in regions of low seismicity can bias hazard estimates that use stationary or spatially precise forecasts. In this work, we implement hazard formulations using forecasts that trade-off spatial precision to account for overdispersion and nonstationarity of seismicity in the form of uniform rate zones (URZs), which describe rate variability using non-Poisson probabilistic distributions of earthquake numbers. The impact of these forecasts in the hazard space is investigated by implementing a negative-binomial formulation in the OpenQuake hazard software suite, which is adopted by the 2022 Aotearoa New Zealand National Seismic Hazard Model. For a 10% exceedance probability of peak ground acceleration (PGA) in 50 yr, forecasts that only reduce the spatial precision, that is, stationary Poisson URZ models, cause up to a twofold increase in hazard for low-seismicity regions compared to spatially precise forecasts. Furthermore, the inclusion of non-Poisson temporal processes in URZ models increases the expected PGA by up to three times in low-seismicity regions, whereas the effect on high-seismicity is minimal (∼5%). The hazard estimates presented here highlight the relevance, as well as the feasibility, of incorporating analytical formulations of seismicity that go beyond the inadequate stationary Poisson description of seismicity.

The 2023 New Zealand Ground-Motion Database

ABSTRACT This article summarizes the development of the 2023 New Zealand ground-motion database (NZGMDB). A preceding version was formally used as the central ground-motion database in the ground-motion characterization modeling for the 2022 New Zealand (NZ) National Seismic Hazard Model (NSHM) revision. The database contains ground motions for events with a moment magnitude greater than ∼3.0 from the years 2000 to the end of 2022. Several challenges associated with NZ earthquake source metadata are explained, including determination of earthquake location, magnitude, tectonic classification, and finite-fault geometry, among others. The site table leverages the site database developed as a part of the 2022 NZ NSHM revision, and several definitions of source-to-site distance are computed for the propagation path table. The ground-motion quality classification was initially assessed using a neural network. Subsequent waveform quality verification was conducted and additional quality criteria were enforced to ensure a sufficiently high-quality database. Standard processing techniques were applied to the ground motions before intensity measure (IM) calculation. IMs in the database include peak ground acceleration, 5%-damped pseudoacceleration response spectra, smoothed Fourier amplitude spectra, and other cumulative and duration-related metrics. The NZGMDB is publicly available and routinely updated as new and higher quality data become available.

The Seismicity Rate Model for the 2022 Aotearoa New Zealand National Seismic Hazard Model

ABSTRACT A seismicity rate model (SRM) has been developed as part of the 2022 Aotearoa New Zealand National Seismic Hazard Model revision. The SRM consists of many component models, each of which falls into one of two classes: (1) inversion fault model (IFM); or (2) distributed seismicity model (DSM). Here we provide an overview of the SRM and a brief description of each of the component models. The upper plate IFM forecasts the occurrence rate for hundreds of thousands of potential ruptures derived from the New Zealand Community Fault Model version 1.0 and utilizing either geologic- or geodetic-based fault-slip rates. These ruptures are typically less than a couple of hundred kilometers long, but can exceed 1500 km and extend along most of the length of the country (albeit with very low probabilities of exceedance [PoE]). We have also applied the IFM method to the two subduction zones of New Zealand and forecast earthquake magnitudes of up to ∼Mw 9.4, again with very low PoE. The DSM combines a hybrid model developed using multiple datasets with a non-Poisson uniform rate zone model for lower seismicity regions of New Zealand. Forecasts for 100 yr are derived that account for overdispersion of the rate variability when compared with Poisson. Finally, the epistemic uncertainty has been modeled via the range of models and parameters implemented in an SRM logic tree. Results are presented, which indicate the sensitivity of hazard results to the logic tree branches and that were used to reduce the overall complexity of the logic tree.

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.

Capturing Directivity in Probabilistic Seismic Hazard Analysis for New Zealand: Challenges, Implications, and a Machine Learning Approach for Implementation

ABSTRACT The proximity of fast-slipping crustal faults to urban areas may result in pulse-like ground motions from rupture directivity, which can contribute to increased levels of damage even for engineered structures. Systematic modeling of directivity within probabilistic seismic hazard analysis (PSHA) remains challenging to implement at the regional scale, despite the availability of directivity models in the literature. In the process of developing the 2022 National Seismic Hazard Model for New Zealand (2022 NSHM), we explored the feasibility and impact of modeling directivity for PSHA at a national scale using the previous generation 2010 NSHM. The results of this analysis allowed us to quantify the impact of directivity on the resulting seismic hazard maps for New Zealand and gain insights into the factors that contribute to the expected increases (and decreases) in ground-motion level. For the 2022 NSHM, the earthquake rupture forecast (ERF) seismogenic source models introduced enormous challenges for directivity modeling due to the abundance of large multisegment or multifault ruptures with complex geometries. To overcome these challenges, we applied a machine learning-based strategy to “overfit” an artificial neural network to capture the distributions of directivity amplification and its variability for each unique rupture in the earthquake rupture forecast. This produces a compact representation of the spatial fields of amplification that are computationally efficient to generate within a complete PSHA calculation for the 2022 NSHM. This flexible and reproducible framework facilitates the implementation of directivity in PSHA at a regional scale for complex ERF source models and opens up the possibility of more complex characterization of epistemic uncertainties for near-source ground motion in practice.