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1,230 records · Page 6Linked to original sources
USGS2026

A temporal look at the influence of topographic amplification on earthquake-triggered landslides in 3D seismic simulations

Earthquakes are a primary trigger for landslides, often leading to catastrophic consequences. While numerous studies have explored the spatial distribution of earthquake-triggered landslides, understanding the interaction between seismic waves and topography remains a critical challenge. Topographic irregularities can cause seismic wave amplification, altering ground shaking, and can trigger landslides that are challenging for predictive models to anticipate. This study investigates the spatial and temporal evolution of topographically amplified landslides, focusing on coseismic landslides triggered by the Mw 7.5 mainshock of the 2018 Papua New Guinea earthquake and post-seismic landslides associated with its four aftershocks, each exceeding Mw 6.0. We employ low-frequency, three-dimensional numerical ground shaking simulations and data-driven multivariate analyses to examine how landslides evolved from the coseismic to post-seismic periods. Our findings reveal a spatial shift in landslide distribution, in which the mainshock triggered slope failures predominantly on steep hillslopes, and the aftershocks triggered landslides on gentler slopes, often near geologic boundaries. We attribute this transition partly to the earthquake legacy effect of the mainshock, where the mainshock caused weakening of these hillslopes, making them more prone to failure when aftershocks occur. Additionally, the concentration of failures along geologic contacts in the post-seismic phase suggests that site amplification, stemming from contrasts in subsurface materials, exerts a key influence on landslide occurrence. Although not explicitly captured in our current numerical simulations, this mechanism warrants further investigation for more accurate hazard modeling.

JGR Solid Earth↗
USGS2025

Persistent deep long-period seismicity near the Lassen Volcanic Center

Deep long-period (DLP) earthquakes have been observed at many volcanic settings around the world and linked to the magmatic processes that drive volcanic unrest. At the Lassen Volcanic Center (LVC) of the Cascade arc, limited detection of DLP activity hinders classification of anomalous seismic behavior and its relationship to the LVC magmatic system. This study uses a template matching approach with seismic data from temporary nodal and permanent stations to detect and locate DLP earthquakes near the LVC between 2017 and 2024. Within the DLP catalog of 611 events, a transition occurs from scattered (2017–2020) to oscillatory (2021–2024) occurrence rates. During the oscillatory period, regional earthquakes with large amplitude velocity waveforms observed near the LVC are associated with abrupt changes in DLP occurrence rates. Continued monitoring of DLP activity has the potential to better define the processes that drive volcanic unrest at the LVC in the future.

California↗
USGS2025

Three-dimensional seismic velocity model for the Cascadia Subduction Zone with shallow soils and topography, version 1.7

The U.S. Geological Survey’s seismic velocity model for the Cascadia Subduction Zone provides P- and S-wave velocity ( V P and V S , respectively) information from 40.2° to 50.0° N. latitude and −129.0° to −121.0° W. longitude, and is used to support a variety of research topics, including three-dimensional (3D) earthquake simulations and seismic hazard assessment in the Pacific Northwest. This report describes an update to the previous version (v) 1.6 of the 3D seismic velocity model for the Cascadia Subduction Zone. This new model (herein referred to as v1.7) contains more detailed near-surface structure for improved earthquake ground motion modeling. Updated features include the addition of a new shallow soil velocity model in the top few hundred meters and the option of adding user-specified topography. Although v1.6 of the Cascadia seismic velocity model has a minimum V S of 600 meters per second (m/s), the new model (v1.7) has a minimum V S of approximately 40 m/s. Overall, this update will allow for more accurate ground motion estimates from 3D simulations of scenario earthquakes in the Cascadia Subduction Zone region.

British Columbia, California, Oregon, Washington↗
USGS2026

Temporal and spatial changes in seismic attenuation associated with inferred fluid migration in the 2016 central Apennines earthquake sequence

Prior work suggests that high‐frequency seismic attenuation acts as a highly sensitive proxy for crustal permeability and fluid mobility in fractured media. We test the hypothesis that the fault system responsible for the 2016–2017 Amatrice–Visso–Norcia–Capitignano sequence acted as an impermeable seal, compartmentalizing pressurized fluids until dynamic rupture triggered widespread fluid diffusion. By tracking across the sequence the spatiotemporal evolution of the S ‐wave anelastic attenuation parameter, we identify large, positive low‐frequency attenuation anomalies emerging within the hanging wall following the Amatrice mainshock and strictly preceding subsequent large ruptures. Conversely, we observe weaker, negative anomalies in the footwall, anticorrelated in time with those of the hanging wall, revealing a massive asymmetry in fluid redistribution and permeability evolution across the fault system. Furthermore, aftershock migration rates reveal distinct linear alignments in a distance‐reduced time space, allowing us to explicitly track and quantify episodes of lateral and upward fluid migration. These physically consistent patterns suggest that stress‐driven fluid diffusion directly weakens adjacent fault patches, dictating the spatiotemporal migration of seismicity. We conclude that near‐real‐time monitoring of seismic attenuation may help detect fluid redistribution in active fault systems and may provide useful information for time‐dependent seismic hazard assessment.

central Apennines↗
USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗
USGS2026

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2025

Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study

We illustrate the systematic difference between moment magnitude and local magnitude caused by underlying earthquake source physics, using seismic moments submitted to the Statewide California Earthquake Center/United States Geological Survey Community Stress Drop Validation Study 2019 Ridgecrest data set. While the relationship between seismic moment and moment magnitude ( M or M w ) of log 10 ( M 0 ) ~ 1.5* M is uniformly valid for all earthquake sizes by definition (Hanks and Kanamori, 1979), the relationship between local magnitude M L and moment is itself magnitude dependent. For moderate events, ~3< M < ~6, M and M L are coincident; for earthquakes smaller than ~3, M L ~ 1.0 log 10 M 0 (Hanks and Boore, 1984). This is a physical consequence of the corner frequency fc becoming larger than the upper frequency of observation and implies that M L and M differ systematically by a factor of 1.5 for these small events. While this idea is not new, we propose a new, continuous relationship between local magnitude and moment, for magnitudes 2 to 6 which extrapolates to smaller and larger magnitudes, applicable to southern California specific to the Ridgecrest region. We make use of the plethora of seismic moments as submitted by many participants of the Community Stress Drop study, compared to the Southern California Seismic Network (SCSN) catalog magnitudes. Overall, the seismic moments in the Community Study recover moment magnitude well, so we use our new M L - M 0 to convert M L to M , refining the SCSN operational M Lr scale. This systematic difference of 50% in slope between local and moment magnitude at small magnitudes has implications for spectral stress drop estimates, earthquake ground motion modeling, as well as other magnitude scales and earthquake occurrence statistics.

California↗
USGS2025

Subduction zone earthquake catalog separation tool: Implementation in the USGS 2025 Puerto Rico and U.S. Virgin Islands National Seismic Hazard Model

The U.S. Geological Survey (USGS) periodically releases updates to National Seismic Hazard Model (NSHM) for the United States and its territories leveraging current scientific knowledge and methodologies to guide public policy, building codes, and risk assessments regarding potential ground shaking due to earthquakes that may result in infrastructure damage. In subduction zones, there is a need to separate the earthquake catalog into tectonic regimes to create specific seismicity models for which the most appropriate ground‐motion models are then applied. Here, we describe newly developed methods and software, called CatSep, that classifies subduction zone events into three primary tectonic regimes: crustal, interface, and intraslab. This method incorporates information about the location of the earthquake relative to the subducting slab, the depth of the Mohorovičić discontinuity, and the earthquake’s moment tensor. Applying this method is a first step in the NSHM workflow for regions covering U.S. subduction zones. Results using this subduction zone earthquake catalog separation tool for the 2025 Puerto Rico and U.S. Virgin Islands NSHM earthquake catalog are presented and analyzed.

Puerto Rico, U.S. Virgin Islands↗
USGS2025

Special issue "Effects of surface geology on seismic motion (ESG): General state-of-research"

To understand and predict the behaviors of strong ground motions incurred during devastating earthquakes, studies focused on the “effects of surface geology (ESG) on seismic motions” (following tradition, herein contracted as: “ESG”) have progressed steadily in the last three decades. These ESG studies typically involve in situ measurements of the wavefield and commonly apply both analytical and computational approaches. Concurrently, improvements in ESG related research can be readily attributed to the proliferation of openly accessible strong motion data, as well as advances in computational power. Nevertheless, there remain significant shortfalls in our understanding of the epistemic and aleatory uncertainties associated with the ESG as demonstrated by phenomena from recent deadly earthquake-related site effects. Thus, investigations toward addressing these deficiencies should be underscored in future earthquake related disaster mitigation efforts. This special issue of Earth, Planets, and Space (EPS) is dedicated to the ongoing efforts by the International Association of Seismology and Physics of the Earth’s Interior (IASPEI) and the International Association of Earthquake Engineering (IAEE) that champion activities promoting studies related to the ESG.

Earth, Planets and Space↗
USGS2026

Predictable seismic cycles result from structural rupture barriers on oceanic transform faults

Earthquakes of magnitude ( M ) >5.5 on oceanic transform faults (OTFs) repeatedly rupture the same locked patches, sometimes quasiperiodically. These patches are separated by “barriers” that halt earthquake propagation and slip mostly aseismically. However, the physical processes governing this systematic behavior remain unclear. We analyzed two barriers along the Gofar transform fault that have arrested ~15 M 6 earthquakes over the past three decades. Ocean bottom seismometer data indicate that the barriers hosted intense microseismicity before the mainshocks and comprise multistrand faults and transtensional stepovers with 100- to 400-m lateral offset. These characteristics contradict earthquake rupture termination models invoking velocity-strengthening friction or large geometric steps and instead point to damage-enhanced porosity and dilatancy-strengthening mechanisms. By isolating rupture segments, the barriers regulate the quasiperiodic recurrence of OTF earthquakes.

Science↗
USGS2026

Ground-motion aleatory-variability models for Puerto Rico and the U.S. Virgin Islands

I develop independent logic trees for aleatory variability for crustal and subduction-zone (interface and intraslab) earthquakes for seismic hazards analyses in Puerto Rico and the U.S. Virgin Islands (PRVI) from existing suites of ground-motion models (GMMs) and from ground-motion datasets, including a regional PRVI dataset. The aleatory variability models are parameterized using a partially nonergodic partitioning of standard deviation that consists of independently developed between-event ( ), site-to-site ( ), and event-corrected single-station ( ) standard deviation components. The effects of nonlinear site response on aleatory variability are incorporated through additional terms that modify the standard deviation components. Because one goal of this work is to develop independent logic trees for aleatory variability that synthesize the aleatory variability models from GMMs, I make use of the functional forms of the input GMMs. The PRVI dataset contains a limited number of stations with high-quality site metadata and does not contain records from earthquakes with magnitudes greater than 6.1, so I choose not to develop the aleatory variability models from the regional dataset alone. Instead, the standard deviation components from regional ground-motion data are evaluated against the components derived from GMMs and from available global datasets, and regionalized standard deviation components are incorporated where there is evidence that regional effects exhibit substantial differences. The resulting logic trees for aleatory variability consist of models of and that are consistent with semiempirical GMMs for active crustal and subduction-zone regimes, and two alternative models of , including one model that exhibits site-to-site variability informed by PRVI data, with values that exceed global models. The aleatory variability models may be considered in future hazards assessments in PRVI to simplify the hazard calculations, to incorporate regional ground-motion variability effects, and to enable direct logic-tree weighs of aleatory variability.

Puerto Rico, U.S. Virgin Islands↗
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↗
USGS2026

Development of liquefaction-targeted design basis in U.S. seismic provisions

Seismic design criteria for new buildings in the United States have historically focused on life safety performance objectives through minimizing the potential for structural collapse. Development of design criteria to meet this performance objective has evolved over time, leading to the current, risk-targeted maximum considered earthquake (MCE R ) design basis. Corresponding MCE R seismic design loads incorporate the full range of probabilistic ground motion hazard information available from U.S. Geological Survey National Seismic Hazard Models, as well as a representation of the uncertainty in structural collapse capacity. Despite these considerable advances in structural design criteria, guidelines for geotechnical hazards such as liquefaction-induced damage, which continue to be based on uniform ground-shaking hazard (i.e., MCE ground motions), are not well-connected with risk-based, collapse prevention performance objectives. This study, undertaken as part of Building Seismic Safety Council efforts to update recommended seismic provisions through the National Earthquake Hazards Reduction Program, presents probabilistic, liquefaction-targeted design objectives and corresponding ground motion parameters, with a focus on improving consistency in first-level screening criteria for liquefaction hazard assessment. This study identifies a potential maximum acceptable annualized probability of liquefaction triggering ( P L,max ) of 2.5% in 50 years, above which liquefaction consequences and potential mitigation measures would be considered. The P L,max -based design basis is calibrated to effective probabilistic liquefaction hazard levels obtained in practice using current MCE peak ground accelerations, and could be implemented via a new liquefaction-targeted maximum considered earthquake (MCE L ) peak ground acceleration ( PGA L ). The proposed PGA L is derived from probabilistic liquefaction hazard curves and includes uncertainties inherent to liquefaction hazard modeling. The potential design effects of the proposed PGA L are demonstrated via comparison with current MCE PGA levels, effects on first-level liquefaction screening analyses, and improvements in the consistency of P L,max levels across the United States, and for a wide range of site conditions.

conterminous United States↗
USGS2026

Cascadia Subduction Zone science: Call for the next generation community seismic velocity model

The Cascadia subduction zone (CSZ) hosts major seismic and tsunami hazards, yet key questions persist about the relationship between margin structure, fluid distribution, episodic tremor and slip, shallow megathrust behavior, shaking and tsunamigenesis, and the resulting hazard estimates. Addressing these problems requires an empirically grounded, three‐dimensional seismic velocity model to illuminate subsurface structure and properties and to provide a basis for geophysical studies such as earthquake simulations and ground‐motion estimation. In May 2024, the National Science Foundation‐funded Cascadia Region Earthquake Science Center (CRESCENT) community velocity model (CVM) working group, with U.S. Geological Survey and regional partners, convened a workshop to identify priorities for such a model. Participants emphasized the features necessary for addressing key science questions, including implementing findability, accessibility, interoperability, and reusability (FAIR) access, capturing along‐strike and along‐dip structural heterogeneity, resolving shallow offshore–onshore structure, constraining elastic properties and quantifying their uncertainties for numerical wave propagation simulations, their validation benchmarks, and supporting associated accurate earthquake ground‐motion simulations and hazard assessments. This article describes the priorities defined in the workshop, and a description of how, guided by these needs, CRESCENT plans to develop multiple generations of a CVM to advance CSZ science and improve seismic and tsunami hazard modeling across the Pacific Northwest. The CVM will span the CSZ from the surface to ∼100 km depth, offshore and east of the Cascades into Idaho (∼132°–110° W) and the southern and northern tectonic regime transitions (∼36°–52° N) to capture the entire tectonic system as well as its surroundings.

Cascadia Subduction Zone↗
USGS2026

Archean to Mesozoic–Cenozoic seismic crustal structure: Implications for geological and biological evolution

We use >4500 measurements of crustal structure to investigate the seismic structure of continental crust, Archean to Mesozoic–Cenozoic. The mean crustal thickness of continents, including their margins, is 36.5 km. We find that Archean, Paleoproterozoic, and Mesoproterozoic crust have similar mean crustal thickness (41 km), seismic velocities, Vp/Vs ratio, and density. Crusts of these ages span 3 Ga, from 4.0 to 1.0 Ga, and their similarity of physical properties (thickness, density, and seismic velocities) suggests that the process of crustal formation may have been similar during this time period, which covers 66% of Earth's history. Neoproterozoic crustal properties differ significantly from Mesoproterozoic and older crusts. The mean thickness of Neoproterozoic crust is 32 km, some 9 km thinner than the mean thickness of Archean, Paleoproterozoic, and Mesoproterozoic crust. A lithospheric root with a thickness of 150–200 km underlies Archean, Paleoproterozoic, and Mesoproterozoic crusts, and this root resists lithospheric rifting and crustal extension and thinning. Based on these observations, particularly the lithospheric thickness, we conclude that Archean, Paleoproterozoic, and Mesoproterozoic lithosphere are unique and together form the stable cratonic nuclei, defined as the thick (150–250 km), long-lived cores of continents. Higher mantle temperatures during the Archean, Paleoproterozoic, and Mesoproterozoic may have played a key role in the formation of the thick lithospheric roots. The second key finding is that the similarities of mean seismic properties indicate that the process of crustal formation operating in the Archean continued during the Paleoproterozoic and Mesoproterozoic. The thin (mean value < 135 km) lithospheric root beneath Neoproterozoic and younger crust may be related to the steady decrease in mantle temperature through time. Neoproterozoic and Paleozoic crust have similar physical properties, and these eras are characterized by pronounced biodiversification, including the renowned Garden of Ediacara, the Cambrian Explosion, and the Great Ordovician Biodiversification. Mesozoic–Cenozoic crust is the most diverse and reflects the current tectonic and magmatic processes of crustal formation.

Book chapter↗
USGS2026

Ground-motion characterization for the 2025 U.S. National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands

We develop the ground-motion characterization (GMC) for the 2025 U.S. National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands (NSHM-PRVI) for earthquakes in active crustal, subduction interface, and subduction intraslab regimes. Using ground-motion models (GMMs) from the Next-Generation Attenuation (NGA)-West2 and NGA-Subduction projects, the GMC is parameterized by scaled-backbone models for median ground motions and by independent logic trees of aleatory variability. We introduce several novel GMC features into the U.S. NSHM: (1) use of regional ground-motion data for modeling median ground motions; (2) development of scaled-backbone models for median ground motions; and (3) development of independent logic trees of aleatory variability from variance components of GMMs and computed from multiple ground-motion datasets, and incorporating regional ground-motion data effects on variability. We compute probabilistic seismic hazard curves and maps to evaluate the contributions from the GMC components and for comparison with the 2003 GMC. Contributions of the GMC to epistemic uncertainty in seismic hazard are evaluated through spatial variations in epistemic uncertainty in hazard maps, comparisons between mean hazard curves and fractiles, as well as investigations of the contributions of logic-tree branches to hazard maps and curves. Comparisons between seismic hazard from the 2025 and 2003 GMCs allow examination of the changes in hazard curves and mapped values with 2% and 10% probabilities of exceedance in 50 years. The 2025 GMC exhibits modest changes in median predictions, relative to the 2003 GMC; overall, values of aleatory variability are higher, except at long periods ( ), resulting in changes to probabilistic ground motions at low probabilities of exceedance (<10% probability of exceedance in 50 years). Changes in hazard at 2% and 10% probabilities of exceedance in 50 years are also relatively modest (within 20%) at most sites, with the impacts from the 2025 GMC exhibiting minor reductions and increases at 0.2 and 1.0 s periods, respectively, relative to the 2003 GMC.

Puerto Rico, U.S. Virgin Islands↗
USGS2026

Evaluating the U.S. Geological Survey’s earthquake shaking hazard forecasts and their implications on seismic risk

We analyze the last six update cycles of the long-term probabilistic earthquake shaking hazard forecast from the U.S. Geological Survey (USGS) and discuss the changes in hazard estimates from the 1996 to the latest 2023 update of the National Seismic Hazard Model (NSHM) for the conterminous U.S. We summarize how our understanding of earthquake hazards has evolved over the last two decades and quantify the implications of changing hazards on people, buildings, and lifeline infrastructure. The net effect of changes in hazard estimates, with reference to the mean hazard from the 2023 NSHM update that has 2% probability of exceedance in 50 years, suggests an overall increase in total geographic areas facing very strong shaking levels (modified Mercalli Intensity (MMI) of VII or more) when compared with any of the previous cycles. This increase puts ~159.2 million people (an increase from 111.8 million when using the 2018 NSHM), ~47.3 million residential buildings (an increase from 32.5 million with the 2018 NSHM), and ~$25.6 trillion of economic exposure of all buildings (an increase from $17.4 trillion when using the 2018 NSHM) at risk from earthquakes. We demonstrate that small changes in hazard estimates do not necessarily imply small changes in risk estimates. Therefore, changes in risk estimates can be used to highlight key USGS NSHM updates for improving risk mitigation efforts.

Earthquake Spectra Journal↗