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Mark D. Petersen

Publications and source records attributed to Mark D. Petersen.

At least 37 records · Page 2Linked to original sources

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

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.

Hawai'i↗

Probabilistic fault displacement hazard assessment (PFDHA) for nuclear installations according to IAEA safety standards

In the last 10 yr, the International Atomic Energy Agency (IAEA) revised its safety standards for site evaluations of nuclear installations in response to emerging fault displacement hazard evaluation practices developed in Member States. New amendments in the revised safety guidance (DS507) explicitly recommend fault displacement hazard assessment, including separate approaches for candidate new sites versus existing sites. If there is insufficient basis to conclusively determine that a fault is not capable of surface displacement at an existing site, then a probabilistic fault displacement hazard analysis (PFDHA) is recommended to better characterize the hazard. This new recommendation has generated the need for the IAEA to provide its Member States with guidance on performing PFDHA, including its formulation and implementation. This article provides an overview of current PFDHA state‐of‐practice for nuclear installations that is consistent with the new IAEA safety standards. We also summarize progress in an ongoing international PFDHA benchmark project that will ultimately provide technical guidance to Member States for conducting site‐specific fault displacement hazard assessments.

Bulletin of the Seismological Society of America↗

The 2018 update of the US National Seismic Hazard Model: Ground motion models in the western US

The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous U.S. NSHM includes significant changes to the underlying ground motion models (GMMs), most of which are necessary to enable the new multi-period response spectra (MPRS) requirements of seismic design regulations that use hazard results for 22 spectral periods and eight site classes. This article focuses on the GMMs used in the western United States (WUS) and is a companion to a recent article on the GMMs used in the central and eastern United States (CEUS). In the WUS, for crustal and subduction earthquakes, two models used in previous versions of the NSHM are excluded to provide consistency over all considered periods and site classes. To more accurately estimate ground motions at long periods in the vicinity of Los Angeles, San Francisco, Salt Lake City, and Seattle, the 2018 NSHM incorporates deep sedimentary basin depth from local seismic velocity models. The subduction GMMs considered lack basin depth terms and are modified to include an additional scale factor to account for this. This article documents the WUS GMMs used in the 2018 NSHM update and provides detail on the changes to GMM medians, aleatory variability, epistemic uncertainty, and site-effect models. It compares each of these components with those considered in prior NSHMs and discusses their total effect on hazard.

Arizona, California, Idaho, Montana, New Mexico, N↗

The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US

The United States Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous US NSHM includes major changes to the underlying ground motion models (GMMs). Most of the changes are motivated by the new multi-period response spectra requirements of seismic design regulations that use hazard results for 22 spectral periods and 8 site classes. In the central and eastern United States (CEUS), the 2018 NSHM incorporates 31 new GMMs for hard-rock site conditions ( V S 30 = 3000 m / s ) "> ( V S 30 = 3000 m / s ) (VS30=3000m/s) , including the Next Generation Attenuation (NGA)-East GMMs. New aleatory variability and site-effect models, both specific to the CEUS, are applied to all median hard-rock GMMs. This article documents the changes to the USGS GMM selection criteria and provides details on the new CEUS GMMs used in the 2018 NSHM update. The median GMMs, their weights, epistemic uncertainty, and aleatory variability are compared with those considered in prior NSHMs. This article further provides implementation details on the CEUS site-effect model, which allows conversion of hard-rock ground motions to other site conditions in the CEUS for the first time in NSHMs. Compared with the 2014 NSHM hard-rock ground motions, the weighted average of median GMMs increases for large magnitude events at middle to large distance range, epistemic uncertainty increases in almost all situations, but aleatory variability is not significantly different. Finally, the total effect on hazard is demonstrated for an assumed earthquake source model in the CEUS, which shows an increased ring of ground motions in the vicinity of the New Madrid seismic zone and decreased ground motions near the East Tennessee seismic zone.

Earthquake Spectra↗

The 2018 update of the US National Seismic Hazard Model: Where, why, and how much probabilistic ground motion maps changed

The 2018 US Geological Survey National Seismic Hazard Model (NSHM) incorporates new data and updated science to improve the underlying earthquake and ground motion forecasts for the conterminous United States. The NSHM considers many new data and component input models: (1) new earthquakes between 2013 and 2017 and updated earthquake magnitudes for some earlier earthquakes; (2) two updated smoothed seismicity models to forecast earthquake rates; (3) two suites of new central and eastern US (CEUS) ground motion models (GMMs) to translate ground shaking for various earthquake sizes and source-to-site distances considered in the model; (4) two CEUS GMMs for aleatory variability; (5) two CEUS site-effect models that modify ground shaking based on alternative shallow site conditions; (6) more advanced western US (WUS) lithologic and structural information to assess basin site effects for selected urban regions; and (7) a more comprehensive range of outputs (22 periods and 8 site classes) than in previous versions of the NSHMs. Each of these new datasets and models produces changes in the probabilistic ground shaking levels that are spatially and statistically analyzed. Recent earthquakes or changes to some older earthquake magnitudes and locations mostly result in probabilistic ground shaking levels that are similar to previous models, but local changes can reach up to +80% and −60% compared to the 2014 model. Newly developed CEUS models for GMMs, aleatory variability, and site effects cause overall changes up to ±64%. The addition of the WUS basin amplifications causes changes of up to +60% at longer periods for sites overlying deep soft soils. Across the conterminous United States, the hazard changes in the model are mainly caused by new GMMs in the CEUS, by sedimentary basin effects for long periods (≥1 s) in the WUS, and by seismicity changes for short (0.2 s) and long (1 s) periods for both areas.

Earthquake Spectra↗

The 2018 update of the US National Seismic Hazard Model: Additional period and site class data

As part of the update of the 2018 National Seismic Hazard Model (NSHM) for the conterminous United States (CONUS), new ground motion and site effect models for the central and eastern United States were incorporated, as well as basin depths from local seismic velocity models in four western US (WUS) urban areas. These additions allow us, for the first time, to calculate probabilistic seismic hazard curves for an expanded set of spectral periods (0.01 to 10 s) and site classes (V S30 = 150 to 1500 m/s) for the CONUS, as well as account for amplification of long-period ground motions in deep sedimentary basins in the Los Angeles, San Francisco Bay, Seattle, and Salt Lake City areas. Two sets of 2018 NSHM hazard data (hazard curves and uniform-hazard ground motions) are available: (1) 0.05°-latitude-by-0.05°-longitude gridded data for the CONUS and (2) higher resolution 0.01°-latitude-by-0.01°-longitude gridded data for the four WUS basins. Both sets of data contain basin effects in the WUS deep sedimentary basins. Uniform-hazard ground motion data are interpolated for 2, 5, and 10% probability of exceedance in 50 years from the hazard curves. The gridded data for the hazard curves and uniform-hazard ground motions, for all periods and site classes, are available for download at the U.S. Geological Survey ScienceBase Catalog ( https://doi.org/10.5066/P9RQMREV ). The design ground motions derived from the hazard curves have been accepted by the Building Seismic Safety Council for adoption in the 2020 National Earthquake Hazard Reduction Program Recommended Seismic Provisions.

California, Utah, Washington↗

Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard forecasts: Hawaii tectonic earthquakes and volcanic eruptions

The selection and weighting of ground‐motion models (GMMs) introduces a significant source of uncertainty in U.S. Geological Survey (USGS) National Seismic Hazard Modeling Project (NSHMP) forecasts. In this study, we evaluate 18 candidate GMMs using instrumental ground‐motion observations of horizontal peak ground acceleration (PGA) and 5%‐damped pseudospectral acceleration (0.02–10 s) for tectonic earthquakes and volcanic eruptions, to inform logic‐tree weights for the update of the USGS seismic hazard model for Hawaii. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function (PDF), mean and standard deviations σ "> σ ⁠ , of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Hawaii seismic hazard model logic trees. The total residual PDF approach provides additional information by preserving GMM over‐ and underprediction across a broad spectrum of periods that is not available from a single value LLH score. We apply these GMM evaluation methods to two different data sets: (1) a database of instrumental ground motions from historic earthquakes in Hawaii from 1973 to 2007 ( ⁠ M w "> M w 4–7.3) and (2) available ground motions from recent earthquakes ( ⁠ M w "> M w 4–6.9) associated with 2018 Kilauea eruptions. The 2018 Kilauea sequence contains both volcanic eruptions and tectonic earthquakes allowing for statistically significant GMM comparisons of the two event classes. The Kilauea ground observations provide an independent data set allowing us to evaluate the predictive power of GMMs implemented in the new USGS nshmp‐haz software system. We evaluate GMM performance as a function of earthquake depth and we demonstrate that short‐period volcanic eruption ground motions are not well predicted by any candidate GMMs. Nine of the initial 18 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the update of the Hawaii seismic hazard model. A weighted mean of four top performing GMMs in this study (NGAsubslab, NGAsubinter, ASK14, A10) is 50% lower for PGA than for GMMS used in the previous USGS seismic hazard model for Hawaii.

Hawaii↗

Probabilistic seismic hazard analysis at regional and national scale: State of the art and future challenges

Seismic hazard modelling is a multi-disciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such models consist of a probabilistic framework that quantifies uncertainty across a complex system; typically, this includes at least two model components developed from Earth science: seismic-source and ground-motion models. Although there is no scientific prescription for the forecast length, the most common probabilistic seismic hazard analyses consider forecasting windows of 30 to 50 years, which are typically an engineering demand for building code purposes. These types of analyses are the topic of this review paper. Although the core methods and assumptions of seismic hazard modelling have largely remained unchanged for more than 50 years, we review the most recent initiatives which face the difficult task of meeting both the increasingly sophisticated demands of society and keeping pace with advances in scientific understanding. A need for more accurate and spatially precise hazard forecasting must be balanced with increased quantification of uncertainty and new challenges such as moving from time-independent hazard to forecasts that are time-dependent and specific to the time-period of interest. Meeting these challenges requires the development of science-driven models which integrate all information available, the adoption of proper mathematical frameworks to quantify the different types of uncertainties in the hazard model, and the development of a proper testing phase of the model to quantify its consistency and skill. We review the state-of-the-art of the national seismic hazard modeling, and how the most innovative approaches try to address future challenges.

Reviews of Geophysics↗

2018 and 2023 U. S. National Seismic Hazard Models

During 2017-2018, the National Seismic Hazard Model (NSHM) was updated by incorporating (1) new median ground motion models, new estimates of their epistemic uncertainties and aleatory variabilities, and new soil amplification factors for the central and eastern U.S., (2) amplification of long-period ground motions in deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas, (3) an updated seismicity catalog, which includes new earthquakes that occurred between 2012 and 2017, and (4) improved computer code and implementation details. Results show significantly increased ground shaking in many (but not all) locations across the central and eastern U.S., and increased ground shaking in the four urban areas (listed above) that overlie deep sedimentary basins in the western U.S. During 2019-2023, the NSHM will consider additional updates for the 2023 NSHM including: 3D simulations in urban areas of Los Angeles and Seattle, additional soil amplification models for other urban areas (e.g., eastern and southern coastal plains of the U.S., Reno, and Las Vegas), non-ergodic ground motion models that reconsider epistemic and aleatory uncertainty, topographic amplification, and new geological and geodetic models for faults. These maps will be considered by the Building Seismic Safety Council, American Society of Civil Engineers, and International Building Code committees for inclusion in upcoming building codes. Due to population growth, more people live and work in areas of moderate or high seismic hazard than ever before, leading to higher risk of undesirable consequences from future ground shaking.

conterminous United States↗

Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence

Instrumental ground‐motion recordings from the 2018 Anchorage, Alaska ( ⁠ M w "> M w 7.1), earthquake sequence provide an independent data set allowing us to evaluate the predictive power of ground‐motion models (GMMs) for intraslab earthquakes associated with the Alaska subduction zone. In this study, we evaluate 15 candidate GMMs using instrumental ground‐motion observations of peak ground acceleration and 5% damped pseudospectral acceleration (0.02–10 s) to inform logic‐tree weights for the update of the U.S. Geological Survey seismic hazard model for Alaska. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function, mean, and standard deviations σ "> σ of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Alaska seismic hazard model logic trees. To test logic branches in previous seismic hazard models, we evaluate GMM performance as a function of depth and we demonstrate that some GMMs show improved performance for earthquakes with focal depths greater than 50 km. Ten of the initial 15 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the next update of the Alaska seismic hazard model.

Alaska↗

The 2018 update of the US National Seismic Hazard Model: Overview of model and implications

During 2017–2018, the National Seismic Hazard Model for the conterminous United States was updated as follows: (1) an updated seismicity catalog was incorporated, which includes new earthquakes that occurred from 2013 to 2017; (2) in the central and eastern United States (CEUS), new ground motion models were updated that incorporate updated median estimates, modified assessments of the associated epistemic uncertainties and aleatory variabilities, and new soil amplification factors; (3) in the western United States (WUS), amplified shaking estimates of long-period ground motions at sites overlying deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas were incorporated; and (4) in the conterminous United States, seismic hazard is calculated for 22 periods (from 0.01 to 10 s) and 8 uniform V S30 maps (ranging from 1500 to 150 m/s). We also include a description of updated computer codes and modeling details. Results show increased ground shaking in many (but not all) locations across the CEUS (up to ~30%), as well as near the four urban areas overlying deep sedimentary basins in the WUS (up to ~50%). Due to population growth and these increased hazard estimates, more people live or work in areas of high or moderate seismic hazard than ever before, leading to higher risk of undesirable consequences from forecasted future ground shaking.

Earthquake Spectra↗

Improved implementation of rupture location uncertainty in fault displacement hazard assessment

This short note proposes an improvement to the implementation of uncertainty associated with rupture location from future earthquakes in probabilistic fault displacement hazard analysis. Location uncertainty leads to nonzero primary fault displacement near a mapped fault. With the improved implementation of location uncertainty, estimated fault displacement hazard at a given site is affected strongly by the dimension of the area considered (or the footprint size of the structure). A larger area near a mapped fault has greater potential of exhibiting primary fault displacement than does a smaller area at the same location. In addition, fault displacement hazard is affected by fault‐map quality and fault‐trace complexity. For a more accurately mapped fault with simpler geometry, larger fault displacement is expected directly over and in close proximity of the mapped fault. If fault location is highly uncertain and fault traces are complex, expected displacement is spread out in a wider zone along the mapped fault.

Bulletin of the Seismological Society of America↗

Evaluation of ground motion models for USGS seismic hazard forecasts: Induced and tectonic earthquakes in the Central and Eastern U.S.

Ground motion model (GMM) selection and weighting introduces a significant source of uncertainty in United States Geological Survey (USGS) seismic hazard models. The increase in moderate moment magnitude induced earthquakes (Mw 4 to 5.8) in Oklahoma and Kansas since 2009, due to increased wastewater injection related to oil and gas production (Keranen et al., 2013; 2014; Weingarten et al., 2015; McNamara et al., 2015a), provides useful near-source (< 40 km) instrumental ground-motion observations for comparisons between central and eastern US (CEUS) induced (Rennolet et al., 2017) and tectonic (Goulet et al., 2014) earthquakes. In this study, we evaluate over 50 GMMs using two well-established probabilistic scoring methods: log likelihood (LLH) (Scherbaum et al., 2004; 2009) and multivariate LLH (MLLH) (Mak et al., 2017). The LLH approach compares the mean and standard deviation (σ) of the observed and modeled ground motions. The MLLH approach advances the LLH method by considering the variability (φ,τ) of multiple correlated variables namely intra- (within) and inter- (between) event residuals. For the probabilistic scoring GMM evaluation methods (LLH, MLLH), we compute horizontal component peak ground acceleration (PGA) and 1s period pseudo spectral acceleration (PSA1.0) total residuals using GMM software (nshmp-haz) recently implemented by the USGS National Seismic Hazard Model Project (NSHMP). We observe from LLH and MLLH scores that: 1) newer GMMs with lower standard deviations (σ,φ,τ) score better than older GMMs with higher published uncertainty; 2) 2014 CEUS GMMs score better for CEUS tectonic earthquakes than induced earthquakes; 3) NGA-West2, G17 and A15 GMMs score well for CEUS induced earthquake ground motions; and 4) NGA-East GMMs score well for CEUS tectonic earthquake ground motions. We also use the LLH and MLLH scores to evaluate GMM weights applied in past USGS seismic hazard forecasts and to inform weighting of GMMs in future seismic hazard forecasts.

Bulletin of the Seismological Society of America↗

Additional period and site class maps for the 2014 National Seismic Hazard Model for the conterminous United States

The 2014 update of the U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) for the conterminous United States (2014 NSHM; Petersen and others, 2014, 2015) included probabilistic ground motion maps for 2 percent and 10 percent probabilities of exceedance in 50 years, derived from seismic hazard curves for peak ground acceleration (PGA) and 0.2 and 1.0 second spectral accelerations (SAs) with 5 percent damping for the National Earthquake Hazards Reduction Program (NEHRP) site class boundary B/C (time-averaged shear wave velocity in the upper 30 meters [V S30 ]=760 meters per second [m/s]). We now provide uniform NEHRP site class maps for 2, 5, and 10 percent probabilities of exceedance in 50 years derived from hazard curves for additional spectral periods. For the central and eastern United States (CEUS) and western United States (WUS), hazard curves and maps for PGA, 0.1, 0.2, 0.3, 0.5, 1.0, and 2.0 second SAs are now available. The WUS additionally includes hazard curves and maps for 0.75, 3.0, 4.0, and 5.0 second SAs. The use of region-specific suites of weighted ground motion models (GMMs) in the 2014 NSHM precluded the calculation of ground motions for a uniform set of periods and site classes for the conterminous United States. At the time of the development of the 2014 NSHM, there was no consensus in the CEUS on an appropriate site-amplification model to use; therefore, we calculated hazard curves and maps for NEHRP site class A, for which most stable continental GMMs were originally developed, based on simulations for hard rock site conditions (V S30 =2,000 m/s). In the WUS, however, the active crustal Next Generation Attenuation Relationships for the WUS (NGA-West2 GMMs) and subduction GMMs allow amplification of ground motions based on site class (defined by V S30 ); so we calculated hazard curves and maps for NEHRP site classes B (V S30 =1,080 m/s), C (V S30 =530 m/s), D (V S30 =260 m/s), and E (V S30 =150 m/s) and site class boundaries A/B (V S30 =1,500 m/s), B/C (V S30 =760 m/s), C/D (V S30 =365 m/s), and D/E (V S30 =185 m/s). The 2014 NSHM introduced a set of criteria for selecting GMMs for use in the NSHMs. When calculating additional period and site class maps, we verified whether the 2014 NSHM original suites of GMMs satisfied these ground motion selection criteria at all additional periods and site classes using GMM magnitude-distance scaling relation plots. Results of our analysis show that certain GMMs give unrealistic results at longer periods, distances, and softer soils in the WUS. In these rare instances, the GMM was removed from the original suite of GMMs (for all periods and site classes) and the weights of the remaining GMMs in the suite were renormalized. Ratio maps show these updated suites of weighted GMMs result in probabilistic ground motion changes of less than 10 percent in the WUS at PGA, as well as 0.2 and 1.0 second SAs, except in the Pacific Northwest, where differences as much as 20 percent are seen. Hazard curves and uniform hazard response spectra at test sites across the conterminous United States were produced to verify that results were reasonable. The additional period and site class maps, and the hazard curves from which they were derived, are available for download from the USGS ScienceBase Catalog.

Open-File Report↗

2018 one‐year seismic hazard forecast for the central and eastern United States from induced and natural earthquakes

This article describes the U.S. Geological Survey (USGS) 2018 one‐year probabilistic seismic hazard forecast for the central and eastern United States from induced and natural earthquakes. For consistency, the updated 2018 forecast is developed using the same probabilistic seismicity‐based methodology as applied in the two previous forecasts. Rates of earthquakes across the United States M &#x2265; 3.0 "> M ≥ 3.0 grew rapidly between 2008 and 2015 but have steadily declined over the past 3 years, especially in areas of Oklahoma and southern Kansas where fluid injection has decreased. The seismicity pattern in 2017 was complex with earthquakes more spatially dispersed than in the previous years. Some areas of west‐central Oklahoma experienced increased activity rates where industrial activity increased. Earthquake rates in Oklahoma (429 earthquakes of M &#x2265; 3 "> M ≥ 3 and 4 M &#x2265; 4 "> M ≥ 4 ), Raton basin (Colorado/New Mexico border, six earthquakes M &#x2265; 3 "> M ≥ 3 ), and the New Madrid seismic zone (11 earthquakes M &#x2265; 3 "> M ≥ 3 ) continue to be higher than historical levels. Almost all of these earthquakes occurred within the highest hazard regions of the 2017 forecast. Even though rates declined over the past 3 years, the short‐term hazard for damaging ground shaking across much of Oklahoma remains at high levels due to continuing high rates of smaller earthquakes that are still hundreds of times higher than at any time in the state’s history. Fine details and variability between the 2016–2018 forecasts are obscured by significant uncertainties in the input model. These short‐term hazard levels are similar to active regions in California. During 2017, M &#x2265; 3 "> M ≥ 3 earthquakes also occurred in or near Ohio, West Virginia, Missouri, Kentucky, Tennessee, Arkansas, Illinois, Oklahoma, Kansas, Colorado, New Mexico, Utah, and Wyoming.

Seismological Research Letters↗

Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model

For more than 20 yrs, damage patterns and instrumental recordings have highlighted the influence of the local 3D geologic structure on earthquake ground motions (e.g., M "> M M 6.7 Northridge, California, Gao et al. , 1996 ; M "> M M 6.9 Kobe, Japan, Kawase, 1996 ; M "> M M 6.8 Nisqually, Washington, Frankel, Carver, and Williams, 2002 ). Although this and other local‐scale features are critical to improving seismic hazard forecasts, historically they have not been explicitly incorporated into the U.S. National Seismic Hazard Model (NSHM, national model and maps), primarily because the necessary basin maps and methodologies were not available at the national scale. Instead, the U.S. Geological Survey (USGS), its partners, and external groups developed urban seismic hazard maps (urban models and maps) that consider detailed site effects in local areas (e.g., Wong et al. , 2002 ; Cramer et al. , 2006 ; Frankel et al. , 2007 ; Graves et al. , 2011 ). The disconnect between the urban and national hazard models, however, means that the national models, which underlie U.S. building codes and other applications, do not make use of all of the scientific results informing earthquake ground‐shaking hazards. We recommend that future U.S. national seismic hazard assessment make use of all available regional information, including that in urban models. In this column, we describe the roles of and differences between the urban and national models, and discuss the obstacles to and benefits of integrating the urban models with the national model. Future progress on this issue will require further coordination and implementation efforts between the USGS and external partners.

Seismological Research Letters↗

Earthquake potential in California-Nevada implied by correlation of strain rate and seismicity

Rock mechanics studies and dynamic earthquake simulations show that patterns of seismicity evolve with time through (1) accumulation phase, (2) localization phase, and (3) rupture phase. We observe a similar pattern of changes in seismicity during the past century across California and Nevada. To quantify these changes, we correlate GPS strain rates with seismicity. Earthquakes of M > 6.5 are collocated with regions of highest strain rates. By contrast, smaller magnitude earthquakes of M ≥ 4 show clear spatiotemporal changes. From 1933 to the late 1980s, earthquakes of M ≥ 4 were more diffused and broadly distributed in both high and low strain rate regions (accumulation phase). From the late 1980s to 2016, earthquakes were more concentrated within the high strain rate areas focused on the major fault strands (localization phase). In the same time period, the rate of M > 6.5 events also increased significantly in the high strain rate areas. The strong correlation between current strain rate and the later period of seismicity indicates that seismicity is closely related to the strain rate. The spatial patterns suggest that before the late 1980s, the strain rate field was also broadly distributed because of the stress shadows from previous large earthquakes. As the deformation field evolved out of the shadow in the late 1980s, strain has refocused on the major fault systems and we are entering a period of increased risk for large earthquakes in California.

Geophysical Research Letters↗

Seismic hazard, risk, and design for South America

We calculate seismic hazard, risk, and design criteria across South America using the latest data, models, and methods to support public officials, scientists, and engineers in earthquake risk mitigation efforts. Updated continental scale seismic hazard models are based on a new seismicity catalog, seismicity rate models, evaluation of earthquake sizes, fault geometry and rate parameters, and ground‐motion models. Resulting probabilistic seismic hazard maps show peak ground acceleration, modified Mercalli intensity, and spectral accelerations at 0.2 and 1 s periods for 2%, 10%, and 50% probabilities of exceedance in 50 yrs. Ground shaking soil amplification at each site is calculated by considering uniform soil that is applied in modern building codes or by applying site‐specific factors based on V S 30 "> V S 30 shear‐wave velocities determined through a simple topographic proxy technique. We use these hazard models in conjunction with the Prompt Assessment of Global Earthquakes for Response (PAGER) model to calculate economic and casualty risk. Risk is computed by incorporating the new hazard values amplified by soil, PAGER fragility/vulnerability equations, and LandScan 2012 estimates of population exposure. We also calculate building design values using the guidelines established in the building code provisions. Resulting hazard and associated risk is high along the northern and western coasts of South America, reaching damaging levels of ground shaking in Chile, western Argentina, western Bolivia, Peru, Ecuador, Colombia, Venezuela, and in localized areas distributed across the rest of the continent where historical earthquakes have occurred. Constructing buildings and other structures to account for strong shaking in these regions of high hazard and risk should mitigate losses and reduce casualties from effects of future earthquake strong ground shaking. National models should be developed by scientists and engineers in each country using the best available science.

Bulletin of the Seismological Society of America↗