Calibration of the U.S. Geological Survey National Crustal Model
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- Document: Report (6.30 MB pdf)
- Data Releases:
- USGS data release - Calibration Coefficients for the U.S. Geological Survey National Crustal Model and Depth to Water Table
- USGS data release - GeoPhys
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Abstract
The U.S. Geological Survey National Crustal Model (NCM) is being developed to include spatially varying estimates of site response in seismic hazard assessments. Primary outputs of the NCM are continuous velocity and density profiles from the Earth’s surface to the mantle transition zone at 410-kilometer (km) depth for each location on a 1-km grid across the conterminous United States. Datasets used to produce the NCM may have a resolution of better than 1 km near the Earth’s surface in some regions, but, with increasing depth, NCM resolution decreases to tens to hundreds of kilometers in the mantle. Basic subsurface information is provided by the NCM geologic framework, thermal model, and petrologic and mineral physics database. In this report, the velocities and densities that can be extracted from the NCM are calibrated through the development of a porosity model based on Biot-Gassmann theory and more than 2,000 compressional- and (or) shear-wave velocity profiles less than 10 km deep from across the conterminous United States and southwestern Canada.
Sediment and rock porosities are derived from shear-wave velocity and are found to depend on effective pressure, rock type, and age (for sedimentary and extrusive volcanic deposits). Porosity-effective pressure functions are then estimated for each rock type (and age for sedimentary and extrusive volcanic deposits). Unconsolidated sediments are found to have higher porosities than consolidated units, which have higher porosities than unweathered igneous units; young sedimentary units (for example, Quaternary age units) tend to have higher porosities than older sedimentary units (for example, pre-Cenozoic age units); porosity decreases with increasing effective pressure; and porosities can decrease quickly through the weathered layer of intrusive rocks.
Comparing two Los Angeles area velocity models and the U.S. Geological Survey Bay Area velocity model with the NCM, the NCM does a better job on average of reproducing observed shear-wave velocities below 1 km per second because it has less bias and uncertainty. Approaching and above 1 km per second, the NCM tends to underpredict observed shear-wave velocity. Whereas several factors could contribute to this, the primary factor is probably bias in the NCM geologic framework. For example, the NCM will predict lower velocities in places where the depth to bedrock and basement appear shallower in the measured velocity profiles than specified in the NCM geologic framework. With regard to observed compressional-wave velocity and density, the NCM has significantly less bias than California models for the former, especially below 2 km per second, and all models tend to overpredict density for densities less than about 2,200 kilograms per cubic meter.
Suggested Citation
Boyd, O.S., 2020, Calibration of the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2020–1052, 23 p., https://doi.org/10.3133/ofr20201052.
ISSN: 2331-1258 (online)
Study Area
Table of Contents
- Acknowledgments
- Abstract
- Introduction
- Biot-Gassmann Theory
- Subsurface Porosity
- Comparisons with Observed Velocities
- Water Table
- Velocity Variability
- Comparison with Existing Geophysical Models
- Discussion
- Conclusions
- References Cited
Publication type | Report |
---|---|
Publication Subtype | USGS Numbered Series |
Title | Calibration of the U.S. Geological Survey National Crustal Model |
Series title | Open-File Report |
Series number | 2020-1052 |
DOI | 10.3133/ofr20201052 |
Year Published | 2020 |
Language | English |
Publisher | U.S. Geological Survey |
Publisher location | Reston, VA |
Contributing office(s) | Geologic Hazards Science Center |
Description | Report: vi, 23 p.; Data Release |
Country | United States |
Online Only (Y/N) | Y |
Google Analytic Metrics | Metrics page |