USGS Science⌕ Search

USGS · 70232685

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

Abstract

The 2021 U.S. National Seismic Hazard Model (NSHM) for the State of Hawaii updates the two-decades-old former model by incorporating new data and modeling techniques to improve the underlying ground shaking forecasts of tectonic-fault, tectonic-flexure, volcanic, and caldera collapse earthquakes. Two earthquake ground shaking hazard models (public policy and research) are produced that differ in how they account for declustered catalogs. The earthquake source model is based on (1) declustered earthquake catalogs smoothed with adaptive smoothing methods, (2) earthquake rate forecasts based on three temporally varying 60-year time periods, (3) maximum magnitude models that extend to larger earthquakes than previously considered, (4) a separate Kīlauea-specific seismogenic caldera collapse model which accounts for clustered event behavior observed during the 2018 eruption, and (5) fault ruptures that consider historic seismicity, GPS-based strain rates, and a new Quaternary fault database. Two new Hawaii-specific ground motion models (GMMs) and five additional global models consistent with Hawaii shaking data are used to forecast ground shaking at 23 spectral periods and peak parameters. Site effects are modeled using western U.S. and Hawaii specific empirical equations and provide shaking forecasts for eight site classes. For most sites the new model results in similar spectral accelerations as those in the 2001 NSHM, with a few exceptions caused mostly by GMM changes. Ground motions are highest in the southern portion of the Island of Hawai‘i due to high rates of forecasted earthquakes on décollement faults. Shaking decays to the northwest where lower earthquake rates result from flexure of the tectonic plate. Large epistemic uncertainties in source characterizations and GMMs lead to an overall high uncertainty (more than a factor of 3) in ground shaking at Honolulu and Hilo. The new shaking model indicates significant chances of slight or greater damaging ground motions across most of the island chain.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 18.917466° to 22.23317° latitude; -160.24961° to -154.809379° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mark D. Petersen, Allison M. Shumway, Peter M. Powers, Morgan P. Moschetti, Andrea L. Llenos, Andrew J. Michael, Charles Mueller, Arthur D. Frankel, Sanaz Rezaeian, Kenneth S. Rukstales, Daniel E. McNamara, P. Okubo, Yuehua Zeng, Kishor S. Jaiswal, Sean Kamran Ahdi, Jason M. Altekruse, Brian Shiro. 2021-12-22. 2021 U.S. National Seismic Hazard Model for the State of Hawaii. https://doi.org/10.1177/87552930211052061

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

KEEP EXPLORING

Related USGS reports

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↗

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↗

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↗