Search USGS⌕ Search
Home/Archive/USGS

USGS · 70283712

Revisions to the 2023 U.S. 50-state National Seismic Hazard Model

Peter M. Powers·Mark D. Petersen·Allison M. Shumway·Jason M. Altekruse·Kevin Ross Milner·Edward H. Field·Morgan P. Moschetti·Andrea L. Llenos·Julie A. Herrick·Nicole Martha Pember·Kenneth S. Rukstales·Sanaz Rezaeian·Andrew James Makdisi·Kishor S. Jaiswal·Nico Luco
View original source ↗Export metadata ↓

Abstract

We present an update to the 2023 U.S. 50-state National Seismic Hazard Model, based on questions and comments received from a range of users, as well as additional internal and building code reviews since its initial release. For the conterminous United States, the update includes (1) revised weighting of ground motion models in the Intermountain West, (2) revised weighting of seismicity models across the stable crust of the central and eastern United States, (3) corrections to fault rupture input files and hazard codes, and (4) adjustments to stable crust nonlinear site amplification terms at soft soil sites. The model also updates the implementation of moment magnitude 7–8 subduction interface earthquake ruptures for Alaska and includes an alternate, full-catalog rate model for Hawaii. The revised model is available through the U.S. Geological Survey online tools and is accompanied by a data release of high-resolution hazard datasets for eight site conditions (from soft soil to hard rock with a time-averaged shear-wave velocity, V S30 , ranging from 150 to 1500 m/s) in terms of peak horizontal ground acceleration, peak ground velocity, and 5% damped pseudo-spectral accelerations at 21 spectral periods. It has been approved as the basis for updated design provisions and is being considered for inclusion in other hazard and risk assessment products.

Explore related subjects

Earthquake SpectraArticle
90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 18.771115062337024° to 71.35706654962706° latitude; -178.2421875° to -66.796875° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Peter M. Powers, Mark D. Petersen, Allison M. Shumway, Jason M. Altekruse, Kevin Ross Milner, Edward H. Field, Morgan P. Moschetti, Andrea L. Llenos, Julie A. Herrick, Nicole Martha Pember, Kenneth S. Rukstales, Sanaz Rezaeian, Andrew James Makdisi, Kishor S. Jaiswal, Nico Luco. 2026-10-11. Revisions to the 2023 U.S. 50-state National Seismic Hazard Model. https://doi.org/10.1002/esp4.70126

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

An examination of the reasons for, and variability of, the differences between response spectra and pseudo response spectra

For many decades, it has been common practice to overlook the differences between response spectra and pseudo response spectra. This practice stems from analyses indicating that the average difference between response spectra and pseudo response spectra is negligible for a viscous damping ratio of 5%, which is near-universally adopted. As others have shown, the differences depend strongly on the damping ratio, earthquake magnitude, and oscillator period, with larger differences for larger damping, smaller magnitudes, and longer periods. To quantify the full statistical distribution of the ratio of the absolute acceleration response spectrum (SA) to the pseudo absolute acceleration response spectrum (PSA), we fit empirical ratios with the generalized gamma distribution. Data for magnitudes from 4.0 to 5.5 give 95% prediction intervals for the ratio of 1.00–1.02 at 1 s and 1.01–2.24 at 10 s for 5% damping. For 30% damping, these intervals increase to 1.14–2.01 at 1 s and 1.62–11.8 at 10 s, respectively. Further, we demonstrate how the shape of the ground-motion Fourier amplitude spectrum interacts with the natural period of the oscillator to control the differences in the response spectra type. Routinely treating the two measures of acceleration response spectra as interchangeable may lead to unacceptable inconsistencies when the response spectra of individual records are important or when larger damping ratios are used, such as in direct displacement-based design. If one must convert between them, the uncertainty of the conversion should be accounted for during analysis.

Earthquake Spectra↗
USGS2026

Accounting for biases in the analysis of building damage data for the 2023 M7.8 Türkiye/Syria earthquake sequence

In the aftermath of a large earthquake, several practical constraints affect the systematic collection of data for assessing building damage. The available data are therefore typically incomplete, frequently missing key information such as the type of construction, age and geographic location. Moreover, the observations often favour certain locations and damage grades. In the absence of robust methods, using such data directly for characterising the building stock or conducting fragility assessments can introduce systematic bias. Using the 2023 M7.8 Türkiye/Syria earthquake sequence as a case study, we propose a statistical model that enables joint inference over the inventory and fragility of the building stock while explicitly accounting for sources of data error and missing information. The results show higher-than-expected vulnerability amongst several building types, particularly mid- and high-rise reinforced concrete buildings, which performed extremely poorly during the 2023 earthquake sequence. The proposed Bayesian framework provides rigorous uncertainty quantification that can be propagated to future applications.

Earthquake Spectra↗
USGS2026

Suite of regional seismic velocity models for the U.S. Atlantic and Gulf Coastal Plains (CPVMv2.0): Incorporating epistemic uncertainty in velocity models

The U.S. Atlantic and Gulf Coastal Plain (CP) sediments are kilometers-thick, low-velocity deposits underlain by high-velocity bedrock that create regional patterns of amplification and attenuation of ground motions. Capturing these effects is challenging because of the limited subsurface information available, particularly the shear wave velocity ( V S ) structure down to bedrock (or assumed reference rock condition) and the associated uncertainties. This paper introduces a new suite of regional velocity models for the CPs, called CPVMv2.0, which builds upon previous efforts integrating geology, V S measurements, and sediment thickness in the region. CPVMv2.0 uses 750 measured V S profiles and identifies nine surficial-geologic-age-based and geography-based groups (with alternative physiographic-province-based subgroupings) to create surface-based median V S profiles. This suite of new models also includes six subsurface-based median profiles developed using geologic age boundaries from depth-dependent stratigraphic sequences extracted from the U.S. Geological Survey National Crustal Model. In addition to quantifying aleatory variability in sediment velocity, weathered-rock velocity, bedrock velocity, and the depth to the top of weathered rock and bedrock, CPVMv2.0 provides alternative profile models that allow for the characterization of the epistemic uncertainty. This is a unique and relevant feature of CPVMv2.0. Our suite of models was validated using measured and estimated fundamental resonant frequencies as well as other V S models in the region. CPVMv2.0 enables the incorporation of crustal velocities (and their associated variability and uncertainty) into physics-based ground-motion simulations in the eastern United States and into the development of new ground-motion models aiming to characterize systematic site effects via V S30 , depths to V S isosurfaces, and/or sediment thickness in the region.

U.S. Atlantic and Gulf Coastal Plains↗