Geology topics

Kevin R. Milner

Publications and source records attributed to Kevin R. Milner.

At least 19 recordsLinked to original sources

USGS2024

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Earthquake Spectra↗

USGS2024

Using open-science workflow tools to produce SCEC CyberShake physics-based probabilistic seismic hazard models

The Statewide (formerly Southern) California Earthquake Center (SCEC) conducts multidisciplinary earthquake system science research that aims to develop predictive models of earthquake processes, and to produce accurate seismic hazard information that can improve societal preparedness and resiliency to earthquake hazards. As part of this program, SCEC has developed the CyberShake platform, which calculates physics-based probabilistic seismic hazard analysis (PSHA) models for regions with high-quality seismic velocity and fault models. The CyberShake platform implements a sophisticated computational workflow that includes over 15 individual codes written by 6 developers. These codes are heterogeneous, ranging from short-running high-throughput serial CPU codes to large, long-running, parallel GPU codes. Additionally, CyberShake simulation campaigns are computationally extensive, typically producing tens of terabytes of meaningful scientific data and metadata over several months of around-the-clock execution on leadership-class supercomputers. To meet the needs of the CyberShake platform, we have developed an extreme-scale workflow stack, including the Pegasus Workflow Management System, HTCondor, Globus, and custom tools. We present this workflow software stack and identify how the CyberShake platform and supporting tools enable us to meet a variety of challenges that come with large-scale simulations, such as automated remote job submission, data management, and verification and validation. This platform enabled us to perform our most recent simulation campaign, CyberShake Study 22.12, from December 2022 to April 2023. During this time, our workflow tools executed approximately 32,000 jobs, and used up to 73% of the Summit system at Oak Ridge Leadership Computing Facility. Our workflow tools managed about 2.5 PB of total temporary and output data, and automatically staged 19 million output files totaling 74 TB back to archival storage on the University of Southern California's Center for Advanced Research Computing systems, including file-based relational data and large binary files to efficiently store millions of simulated seismograms. CyberShake extreme-scale workflows have generated simulation-based probabilistic seismic hazard models that are being used by seismological, engineering, and governmental communities.

Frontiers Earth Science Journal↗

USGS2024

Forecasting the long-term spatial distribution of earthquakes for the 2023 US National Seismic Hazard Model using gridded seismicity

Probabilistic seismic hazard analyses such as the U.S. National Seismic Hazard Model (NSHM) typically rely on declustering and spatially smoothing an earthquake catalog to estimate a long‐term time‐independent (background) seismicity rate to forecast future seismicity. In support of the U.S. Geological Survey’s (USGS) 2023 update to the NSHM, we update the methods used to develop this background or gridded seismicity model component of the NSHM. As in 2018, we use a combination of fixed and adaptive kernel Gaussian smoothing. However, we implement two additional declustering methods to account for the fact that declustering is a nonunique process. These new declustering methods result in different forecasts for the locations of future seismicity, as represented by spatial probability density functions that are later combined with a rate model to produce a full gridded earthquake rate forecast. The method updates, particularly in the separation of the spatial and rate models as well as revised regional boundaries, in some places cause substantive changes to the seismic hazard forecast compared to the previous 2018 NSHM. Additional updates to catalog processing and induced seismicity zones also contribute to changes in the gridded seismicity hazard since 2018. However, these changes are well understood and reflect improvements in our modeling of gridded seismicity hazard.

Continental United States↗

USGS2023

The 2023 US 50-State National Seismic Hazard Model: Overview and implications

The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard (both increases and decreases compared to previous NSHMs) are substantial because the new model considers more data and updated earthquake rupture forecasts and ground-motion components. In developing the 2023 model, we tried to apply best available or applicable science based on advice of co-authors, more than 50 reviewers, and hundreds of hazard scientists and end-users, who attended public workshops and provided technical inputs. The hazard assessment incorporates new catalogs, declustering algorithms, gridded seismicity models, magnitude-scaling equations, fault-based structural and deformation models, multi-fault earthquake rupture forecast models, semi-empirical and simulation-based ground-motion models, and site amplification models conditioned on shear-wave velocities of the upper 30 m of soil and deeper sedimentary basin structures. Seismic hazard calculations yield hazard curves at hundreds of thousands of sites, ground-motion maps, uniform-hazard response spectra, and disaggregations developed for pseudo-spectral accelerations at 21 oscillator periods and two peak parameters, Modified Mercalli Intensity, and 8 site classes required by building codes and other public policy applications. Tests show the new model is consistent with past ShakeMap intensity observations. Sensitivity and uncertainty assessments ensure resulting ground motions are compatible with known hazard information and highlight the range and causes of variability in ground motions. We produce several impact products including building seismic design criteria, intensity maps, planning scenarios, and engineering risk assessments showing the potential physical and social impacts. These applications provide a basis for assessing, planning, and mitigating the effects of future earthquakes.

Earthquake Spectra↗

USGS2023

The USGS 2023 Conterminous U.S. time‐independent earthquake rupture forecast

We present the 2023 U.S. Geological Survey time‐independent earthquake rupture forecast for the conterminous United States, which gives authoritative estimates of the magnitude, location, and time‐averaged frequency of potentially damaging earthquakes throughout the region. In addition to updating virtually all model components, a major focus has been to provide a better representation of epistemic uncertainties. For example, we have improved the representation of multifault ruptures, both in terms of allowing more and less fault connectivity than in the previous models, and in sweeping over a broader range of viable models. An unprecedented level of diagnostic information has been provided for assessing the model, and the development was overseen by a 19‐member participatory review panel. Although we believe the new model embodies significant improvements and represents the best available science, we also discuss potential model limitations, including the applicability of logic tree branch weights with respect different types of hazard and risk metrics. Future improvements are also discussed, with deformation model enhancements being particularly worthy of pursuit, as well as better representation of sampling errors in the gridded seismicity components. We also plan to add time‐dependent components, and assess implications with a wider range of hazard and risk metrics.

Bulletin of the Seismological Society of America↗

USGS2023

A comprehensive fault system inversion approach: Methods and application to NSHM23

We present updated inversion‐based fault‐system solutions for the 2023 update to the National Seismic Hazard Model (NSHM23), standardizing earthquake rate model calculations on crustal faults across the western United States. We build upon the inversion methodology used in the Third Uniform California Earthquake Rupture Forecast (UCERF3) to solve for time‐independent rates of earthquakes in an interconnected fault system. The updated model explicitly maps out a wide range of fault recurrence and segmentation behavior (epistemic uncertainty), more completely exploring the solution space of viable models beyond those of UCERF3. We also improve the simulated annealing implementation, greatly increasing computational efficiency (and thus inversion convergence), and introduce an adaptive constraint weight calculation algorithm that helps to mediate between competing constraints. Hazard calculations show that ingredient changes (especially fault and deformation models) are the primary driver of hazard changes between NSHM23 and UCERF3. Updates to the inversion methodology are also consequential near faults in which the slip rate in UCERF3 was poorly fit or was satisfied primarily using large multifault ruptures that are now restricted by explicit b ‐value and segmentation constraints.

Bulletin of the Seismological Society of America↗

USGS2023

Comparison of nonergodic ground-motion components from CyberShake and NGA-West2 datasets in California

In this study, we compare the Southern California Earthquake Center CyberShake platform against the Next Generation Attenuation‐West2 empirical datasets. Because the CyberShake and empirical datasets cover very different magnitude ranges and site conditions, we develop ground‐motion models (GMMs) for CyberShake datasets to compare trends with empirical GMMs and decompose the residuals for further analysis. We apply mixed effects regression to four CyberShake datasets in southern, central, and northern California at 2, 3, 5, and 10 s periods, and compare the results with the empirical datasets using the same approach. CyberShake captures the total variability of ground motions in the empirical datasets but tends to predict larger median ground motions relative to the empirical GMMs. We then calculate and compare the repeatable source‐specific location, site, and path effects between CyberShake and empirical datasets. We find that the correlations of site effects between the CyberShake and empirical datasets are generally satisfactory, but the variability of site effects is slightly smaller for CyberShake datasets. There is no apparent correlation of source‐specific location effects between the CyberShake and empirical datasets. Comparison of path effects shows a wide range of correlation coefficients. Finally, we investigate the source of observed differences between the CyberShake and empirical datasets. We attribute the larger median ground‐motion levels in CyberShake to a combination of the homogeneous slip patterns of the earthquake ruptures, the low resolution of near‐surface materials in the velocity models, and strong reflections at high‐contrast boundaries in the velocity models. These factors also impact the correlations of site and path effects between the CyberShake and empirical datasets. Moreover, the leakage from location effects into site and path terms further weakens the correlations. In summary, we find that CyberShake could be improved, but it is still very useful to supplement empirical datasets for ground‐motion studies, especially to inform their nonergodic components.

California↗

USGS2022

What to expect when you are expecting earthquake early warning

We present a strategy for earthquake early warning (EEW) alerting that focuses on providing users with a target level of performance for their shaking level of interest (for example, ensuring that users receive warnings for at least 95 per cent of the occurrences of that shaking level). We explore the factors that can affect the accuracy of EEW shaking forecasts including site conditions (which can make shaking more or less varied), the share of earthquake hazard that comes from outlier events, and even the metric of shaking being forecast (with modified Mercalli intensity being the most uncertain quantity to forecast). To provide different locations with the same level of EEW performance, the alert issuance criteria will need to change based on these factors. Finally, we present a hierarchy of information approach with which to communicate EEW system design and performance to the public and other stakeholders, including how frequently alerts will be issued and how accurate those alerts will be.

Geophysical Journal International↗

USGS2022

Enumerating plausible multifault ruptures in complex fault systems with physical constraints

We propose a new model for determining the set of plausible multifault ruptures in an interconnected fault system. We improve upon the rules used in the Third Uniform California Earthquake Rupture Forecast (UCERF3) to increase connectivity and the physical consistency of ruptures. We replace UCERF3’s simple azimuth change rules with new Coulomb favorability metrics and increase the maximum jump distance to 15 km. Although the UCERF3 rules were appropriate for faults with similar rakes, the Coulomb calculations used here inherently encode preferred orientations between faults with different rakes. Our new rules are designed to be insensitive to discretization details and are generally more permissive than their UCERF3 counterparts; they allow more than twice the connectivity compared to UCERF3, yet heavily penalize long ruptures that take multiple improbable jumps. The set of all possible multifault ruptures in the California fault system is near-infinite, but our model produces a tractable set of 326,707 ruptures (a modest 29% increase over UCERF3, despite the greatly increased connectivity). Inclusion in the rupture set does not dictate that a rupture receives a significant rate in the final model; rupture rates are subsequently determined by data constraints used in an inversion. We describe the rupture building algorithm and its components in detail and provide comparisons with ruptures generated by a physics-based multicycle earthquake simulator. We find that greater than twice as many ruptures generated by the simulator violate the UCERF3 rules than violate our proposed model.

California↗

USGS2021

The seismic hazard implications of declustering and poisson assumptions inferred from a fully time‐dependent model

We use the Third Uniform California Earthquake Rupture Forecast (UCERF3) epidemic‐type aftershock sequence (ETAS) model (UCERF3‐ETAS) to evaluate the effects of declustering and Poisson assumptions on seismic hazard estimates. Although declustering is necessary to infer the long‐term spatial distribution of earthquake rates, the question is whether it is also necessary to honor the Poisson assumption in classic probabilistic seismic hazard assessment. We use 500,000 yr, M ≥ 2.5 synthetic catalogs to address this question, for which UCERF3‐ETAS exhibits realistic spatiotemporal clustering effects (e.g., aftershocks). We find that Gardner and Knopoff (1974) declustering, used in the U.S. Geological Survey seismic hazard models, lowers 2% in 50 yr and risk‐targeted ground‐motion hazard metrics by about 4% on average (compared with the full time‐dependent [TD] model), with the reduction being 5% at 40% in 50 yr ground motions. Keeping all earthquakes and treating them as a Poisson process increases these same hazard metrics by about 3%–12%, on average, due to the removal of relatively quiet time periods in the full TD model. In the interest of model simplification, bias minimization, and consideration of the probabilities of multiple exceedances, we agree with others ( Marzocchi and Taroni, 2014 ) that we are better off keeping aftershocks and treating them as a Poisson process rather than removing them from hazard consideration via declustering. Honoring the true time dependence, however, will likely be important for other hazard and risk metrics, and this study further exemplifies how this can now be evaluated more extensively.

California↗

USGS2021

Improvements to the Third Uniform California Earthquake Rupture Forecast ETAS Model (UCERF3‐ETAS)

We describe recent improvements to the Third Uniform California Earthquake Rupture Forecast ETAS Model (UCERF3‐ETAS), which continues to represent our most advanced and complete earthquake forecast in terms of relaxing segmentation assumptions and representing multifault ruptures, elastic‐rebound effects, and spatiotemporal clustering (the latter to represent aftershocks and otherwise triggered events). The two main improvements include adding aleatory variability in aftershock productivity and the option to represent off‐fault events with finite‐rupture surfaces. We also summarize the studies that led to these modifications, and reflect on how past and future uses of the model can improve our understanding of earthquake processes and the hazards and risks they pose.

California↗

USGS2021

Toward physics-based nonergodic PSHA: A prototype fully-deterministic seismic hazard model for southern California

We present a nonergodic framework for probabilistic seismic‐hazard analysis (PSHA) that is constructed entirely of deterministic, physical models. The use of deterministic ground‐motion simulations in PSHA calculations is not new (e.g., CyberShake), but prior studies relied on kinematic rupture generators to extend empirical earthquake rupture forecasts. Fully dynamic models, which simulate rupture nucleation and propagation of static and dynamic stresses, are still computationally intractable for the large simulation domains and many seismic cycles required to perform PSHA. Instead, we employ the Rate‐State earthquake simulator (RSQSim) to efficiently simulate hundreds of thousands of years of M ≥ 6.5 earthquake sequences on the California fault system. RSQSim produces full slip‐time histories for each rupture, which, unlike kinematic models, emerge from frictional properties, fault geometry, and stress transfer; all intrinsic variability is deterministic. We use these slip‐time histories directly as input to a 3D wave‐propagation code within the CyberShake platform to obtain simulated F max = 0.5 Hz ground motions. The resulting 3 s spectral acceleration ground motions closely match empirical ground‐motion model (GMM) estimates of median and variability of shaking. When computed over a range of sources and sites, the variability is similar to that of ergodic GMMs. Variability is reduced for individual pairs of sources and sites that repeatedly sample a single path, which is expected for a nonergodic model. This results in increased exceedance probabilities for certain characteristic ground motions for a source–site pair, while decreasing probabilities at the extreme tails of the ergodic GMM predictions. We present these comparisons and preliminary fully deterministic physics‐based RSQSim–CyberShake hazard curves, as well as a new technique for estimating within‐ and between‐event variability through simulation.

California↗

USGS2020

Generalizing the inversion‐based PSHA source model for an interconnected fault system

This article represents a step toward generalizing and simplifying the procedure for constructing an inversion‐based seismic hazard source model for an interconnected fault system, including the specification of adjustable segmentation constraints. A very simple example is used to maximize understandability and to counter the notion that an inversion approach is only applicable when an abundance of data is available. Also exemplified is how to construct a range of models to adequately represent epistemic uncertainties (which should be a high priority in any hazard assessment). Opportunity is also taken to address common concerns and misunderstandings associated with the third Uniform California Earthquake Rupture Forecast, including the seemingly disproportionate number of large‐magnitude events, and how well hazard is resolved given the overall problem is very underdetermined. However, the main aim of this article is to provide a general protocol for constructing such models.

Bulletin of the Seismological Society of America↗

USGS2020

Shaking is almost always a surprise: The earthquakes that produce significant ground motion

Although small earthquakes are expected to produce weak shaking, ground motion is highly variable and there are outlier earthquakes that generate more shaking than expected—sometimes significantly more. We explore datasets of M 0.5–8.3 earthquakes to determine the relative impact of frequent, smaller-magnitude earthquakes that rarely produce strong ground motion, to rare, large earthquakes that always cause strong shaking. We find that the natural variability of ground motion, combined with the Gutenberg–Richter magnitude–frequency relationship, ensures that most occurrences of any ground motion come from earthquakes of smaller magnitude than expected, often > 2 magnitude units smaller. This holds even for very strong shaking ( > 20% g ), suggesting that M < 7 earthquakes could be a significant source of damage.

Seismological Research Letters↗

USGS2020

Pseudo-prospective evaluation of UCERF3-ETAS forecasts during the 2019 Ridgecrest sequence

The 2019 Ridgecrest sequence provides the first opportunity to evaluate Uniform California Earthquake Rupture Forecast v.3 with epidemic‐type aftershock sequences (UCERF3‐ETAS) in a pseudoprospective sense. For comparison, we include a version of the model without explicit faults more closely mimicking traditional ETAS models (UCERF3‐NoFaults). We evaluate the forecasts with new metrics developed within the Collaboratory for the Study of Earthquake Predictability (CSEP). The metrics consider synthetic catalogs simulated by the models rather than synoptic probability maps, thereby relaxing the Poisson assumption of previous CSEP tests. Our approach compares statistics from the synthetic catalogs directly against observations, providing a flexible approach that can account for dependencies and uncertainties encoded in the models. We find that, to the first order, both UCERF3‐ETAS and UCERF3‐NoFaults approximately capture the spatiotemporal evolution of the Ridgecrest sequence, adding to the growing body of evidence that ETAS models can be informative forecasting tools. However, we also find that both models mildly overpredict the seismicity rate, on average, aggregated over the evaluation period. More severe testing indicates the overpredictions occur too often for observations to be statistically indistinguishable from the model. Magnitude tests indicate that the models do not include enough variability in forecasted magnitude‐number distributions to match the data. Spatial tests highlight discrepancies between the forecasts and observations, but the greatest differences between the two models appear when aftershocks occur on modeled UCERF3‐ETAS faults. Therefore, any predictability associated with embedding earthquake triggering on the (modeled) fault network may only crystalize during the presumably rare sequences with aftershocks on these faults. Accounting for uncertainty in the model parameters could improve test results during future experiments.

California↗

USGS2020

Assessing the value of removing earthquake-hazard-related epistemic uncertainties, exemplified using average annual loss in California

To aid in setting scientific research priorities, we assess the potential value of removing each of the epistemic uncertainties currently represented in the US Geological Survey California seismic-hazard model, using average annual loss (AAL) as the risk metric of interest. Given all the uncertainties, represented with logic-tree branches, we find a mean AAL of $3.94 billion. The modal value is 17.5% lower than the mean, and there is a 78% chance that the true AAL value is more than 10% away from the mean, and a 5% chance that it is a factor 2.1 greater or lower than the mean. We quantify the extent to which resolving each uncertainty improves the AAL estimate. The most influential branch is one that adds additional epistemic uncertainty to ground motion models, but others are found to be influential as well, such as the rate of M ≥ 5 events throughout the region. We discuss the broader implications of our findings, and note that the time dependence caused by spatiotemporal clustering can be much more influential on AAL than the epistemic uncertainties explored here.

California↗

USGS2020

Operational earthquake forecasting during the 2019 Ridgecrest, California, earthquake sequence with the UCERF3-ETAS model

The first Uniform California Earthquake Rupture Forecast, Version 3–epidemic‐type aftershock sequence (UCERF3‐ETAS) aftershock simulations were running on a high‐performance computing cluster within 33 min of the 4 July 2019 M 6.4 Searles Valley earthquake. UCERF3‐ETAS, an extension of the third Uniform California Earthquake Rupture Forecast (UCERF3), is the first comprehensive, fault‐based, epidemic‐type aftershock sequence (ETAS) model. It produces ensembles of synthetic aftershock sequences both on and off explicitly modeled UCERF3 faults to answer a key question repeatedly asked during the Ridgecrest sequence: What are the chances that the earthquake that just occurred will turn out to be the foreshock of an even bigger event?

California↗

USGS2019

The limits of earthquake early warning accuracy and best alerting strategy

We explore how accurate earthquake early warning (EEW) can be, given our limited ability to forecast expected shaking even if the earthquake source is known. Because of the strong variability of ground motion metrics, such as peak ground acceleration (PGA) and peak ground velocity (PGV), we find that correct alerts (i.e., alerts that accurately predict the observed ground motion above a predetermined damage threshold) are not expected to be the most common EEW outcome even when the earthquake magnitude and location are accurately determined. Infrequently, ground motion variability results in a user receiving a false alert because the ground motion turned out to be significantly smaller than the damage threshold. More commonly, users will experience missed alerts when the system does not issue an alert but the user experiences potentially damaging shaking. Despite these inherit limitations, EEW can significantly mitigate earthquake losses for false-alert-arm-tolerant users who choose to receive alerts for expected ground motions much smaller than the level that could cause damage. Although this results in many false alerts for earthquakes that do not produce damaging ground shaking, it minimizes the number of missed alerts and produces overall optimal performance.

California↗