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Morgan T. Page

Publications and source records attributed to Morgan T. Page.

At least 37 records · Page 2Linked to original sources
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↗
USGS2020

Apparent earthquake rupture predictability

To what extent can the future evolution of an ongoing earthquake rupture be predicted? This question of fundamental scientific and practical importance has recently been addressed by studies of teleseismic source time functions (STFs) but reaching contrasting conclusions. One study concludes that the initial portion of STFs is the same regardless of magnitude. Another study concludes that the rate at which earthquakes grow increases systematically and strongly with final event magnitudes. Here we show that the latter reported trend is caused by a selection bias towards events with unusually long durations, and by estimates of STF growth made when the STF is already decaying. If these invalid estimates are left out, the trend is no longer present, except during the first few seconds of the smallest events in the dataset, Mw5–6.5, for which the reliability of the STF amplitudes is questionable. Simple synthetic tests show that the observations are consistent with statistically indistinguishable growth of smaller and larger earthquakes. A much weaker trend is apparent among events of comparable duration, but we argue that its significance is not resolvable by the current data. Finally, we propose a nomenclature to facilitate further discussions of earthquake rupture predictability and determinism.

Geophysical Journal International↗
USGS2020

The normal faulting 2020 Mw5.8 Lone Pine, Eastern California earthquake sequence

The 2020 M w "> M w 5.8 Lone Pine earthquake, the largest earthquake on the Owens Valley fault zone, eastern California, since the nineteenth century, ruptured an extensional stepover in that fault. Owens Valley separates two normal‐faulting regimes, the western margin of the Great basin and the eastern margin of the Sierra Nevada, forming a complex seismotectonic zone, and a possible nascent plate boundary. Foreshocks began on 22 June 2020; the largest M w "> M w 4.7 foreshock occurred at ∼ 6    km "> ∼6 km depth, with primarily normal faulting, followed ∼ 40    hr "> ∼ 40 hr later on 24 June 2020 by an M w "> M w 5.8 mainshock at ∼ 7    km "> ∼ 7 km depth. The sequence caused overlapping ruptures across a ∼ 0.25    km 2 "> ∼0.25 km 2 area, extended to ∼ 4    km 2 "> ∼ 4 km 2 , and culminated in an ∼ 25    km 2 "> ∼25 km 2 aftershock area. The mainshock was predominantly normal faulting, with a strike of 330° (north‐northwest), dipping 60°–65° to the east‐northeast. Comparison of background seismicity and 2020 Ridgecrest aftershock rates showed that this earthquake was not an aftershock of the Ridgecrest mainshock. The M w "> M w M w – m B "> – m B relationship and distribution of ground motions suggest typical rupture speeds. The aftershocks form a north‐northwest‐trending, north‐northeast‐dipping, 5 km long distribution, consistent with the rupture length estimated from analysis of regional waveform data. No surface rupture was reported along the 1872 scarps from the 2020 M w "> M w 5.8 mainshock, although, the dipping rupture zone of the M w "> M w 5.8 mainshock projects to the surface in the general area. The mainshock seismic energy triggered rockfalls at high elevations ( ⁠ > 3.0    km "> > 3.0 km ⁠ ) in the Sierra Nevada, at distances of 8–20 km, and liquefaction along the western edge of Owens Lake. Because there were ∼ 30 % "> ∼ 30 % fewer aftershocks than for an average southern California sequence, the aftershock forecast probabilities were lower than expected. ShakeAlert, the earthquake early warning system, provided first warning within 9.9 s, as well as subsequent updates.

California↗
USGS2020

Revisiting California’s past great earthquakes and long-term earthquake rate

In this study, we revisit the three largest historical earthquakes in California—the 1857 Fort Tejon, 1872 Owens Valley, and 1906 San Francisco earthquakes—to review their published moment magnitudes, and compare their estimated shaking distributions with predictions using modern ground‐motion models (GMMs) and ground‐motion intensity conversion equations. Currently accepted moment magnitude estimates for the three earthquakes are 7.9, 7.6, and 7.8, respectively. We first consider the extent to which the intensity distributions of all three earthquakes are consistent with a moment magnitude toward the upper end of the estimated range. We then apply a GMM‐based method to estimate the magnitudes of large historical earthquakes. The intensity distribution of the 1857 earthquake is too sparse to provide a strong constraint on magnitude. For the 1872 earthquake, consideration of all available constraints suggests that it was a high stress‐drop event, with a magnitude on the higher end of the range implied by scaling relationships, that is, higher than moment magnitude 7.6. For the 1906 earthquake, based on our analysis of regional intensities and the detailed intensity distribution in San Francisco, along with other available constraints, we estimate a preferred moment magnitude of 7.9, consistent with the published estimate based on geodetic and instrumental seismic data. These results suggest that, although there can be a tendency for historical earthquake magnitudes to be overestimated, the accepted catalog magnitudes of California’s largest historical earthquakes could be too low. Given the uncertainties of the magnitude estimates, the seismic moment release rate between 1850 and 2019 could have been either higher or lower than the average over millennial time scales. It is further not possible to reject the hypothesis that California seismicity is described by an untruncated Gutenberg–Richter distribution with a b "> b ‐value of 1.0 for moment magnitudes up to 8.0.

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

More fault connectivity Is needed in seismic hazard analysis

Did the third Uniform California Earthquake Rupture Forecast (UCERF3) go overboard with multifault ruptures? Schwartz (2018) argues that there are too many long ruptures in the model. Here, I address his concern and show that the UCERF3 rupture‐length distribution matches empirical data. I also present evidence that, if anything, the UCERF3 model could be improved by adding more connectivity to the fault system. Adding more connectivity would improve model misfits with data, particularly with paleoseismic data on the southern San Andreas fault; make the model less characteristic on the faults; potentially improve aftershock forecasts; and reduce model sensitivity to inadequacies and unknowns in the modeled fault system.

Bulletin of the Seismological Society of America↗
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

#EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm

Communicating probabilities of natural hazards to varied audiences is a notoriously difficult task. Many of these challenges were encountered during the 2016 Bombay Beach, California, swarm of ~100 2≤M≤4.3 earthquakes, which began on 26 September 2016 and lasted for several days. The swarm’s proximity to the southern end of the San Andreas fault caused concern that a larger earthquake could be triggered. Within 1–2 days, different forecast models were used to evaluate the likelihood of a larger event with two agencies (the U.S. Geological Survey [USGS] and the California Governor’s Office of Emergency Services) releasing probabilities and forecasts for larger earthquakes. Our research explores communication and news media efforts, as well as how people on a microblogging social media site (Twitter) responded to these forecasts. Our findings suggest that news media used a combination of information sources, basing their articles on what they learned from social media, as well as using information provided by government agencies. As the swarm slowed down, there is evidence of the continued interplay between news media and social media, with the USGS issuing revised probability reports and scientists from the USGS and other institutions participating in media interviews. In reporting on the swarm, news media often used language more generally than the scientists; terms such as probability, likelihood, chance, and possibility were used interchangeably. Knowledge of how news media used scientific information from the 2016 Bombay Beach forecasts can assist local, state, and federal agencies in developing effective communication strategies to respond to future earthquakes.

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↗
USGS2019

Peak ground displacement saturates exactly when expected: Implications for earthquake early warning

The scaling of rupture properties with magnitude is of critical importance to earthquake early warning (EEW) systems that rely on source characterization using limited snapshots of waveform data. ShakeAlert, a prototype EEW system that is being developed for the western United States, provides real-time estimates of earthquake magnitude based on P-wave peak ground displacements measured at stations triggered by the event. The algorithms used in ShakeAlert assume that the displacement measurements at each station are statistically independent and that there exists a linear and time-independent relation between log peak ground displacement and earthquake magnitude. Here we challenge this basic assumption using a comprehensive database of more than 130,000 vertical component waveforms from M4.5-M9 earthquakes occurring near Japan from 1997 through 2017 and recorded by the K-NET and KiK-net strong-motion networks. By analyzing the time-evolution of P-wave peak ground displacements for these earthquakes, we show that there is a break, or saturation, in the magnitude-displacement scaling that depends on the length of the measurement time window. We demonstrate that the magnitude at which this saturation occurs is well-explained by a simple and non-deterministic model of earthquake rupture growth. We then use the predictions of this saturation model to develop a Bayesian framework for estimating posterior uncertainties in real-time magnitude estimates which incorporates the expected time-dependence of the peak displacement measurements.

Journal of Geophysical Research B: Solid Earth↗
USGS2018

Updated California aftershock parameters

Reasenberg and Jones (1989) introduced a statistical model for aftershock rate following a mainshock along with estimates of “generic” California parameter values based on past aftershock sequences. The Reasenberg and Jones (1989) model has been used for decades to issue aftershock forecasts following M ≥ 5 "> M ≥ 5 mainshocks in California. Here, we update the “generic” parameters for California through a fit to the aftershock sequences of M ≥ 5 "> M ≥ 5 mainshocks occurring since 1980. We find aftershock productivity values that are lower on average than the generic productivity reported by Reasenberg and Jones (1989) , likely because low‐productivity sequences were omitted from their analysis and possibly because of a trade‐off between productivity and b "> b ‐value. We confirm the observation of Llenos and Michael (2017) that southern California sequences are more productive on average than northern California sequences. The Mendocino area is much less productive; the hydrothermal areas in Long Valley, Coso, and the Salton Sea, in contrast, are much more productive. We also quantify the variability of the Reasenberg and Jones (1989) productivity parameter a "> a a between sequences with a normal distribution. This distribution of a "> a ‐values can be used to compute aftershock forecasts that include epistemic uncertainty and can be used as the prior for Bayesian updating of the a "> a a ‐value as a sequence progresses.

California↗
USGS2018

Turing-style tests for UCERF3 synthetic catalogs

Epidemic-Type Aftershock Sequence (ETAS) catalogs generated from the 3rd Uniform California Earthquake Rupture Forecast (UCERF3) model are unique in that they are the first to combine a complex, fault-based long-term forecast with short-term earthquake clustering statistics. We present Turing-style tests to examine whether these synthetic catalogs can successfully imitate observed earthquake behavior in California. We find that UCERF3-ETAS is more spatially diffuse than the observed historic catalog in California and that it is lacking quiet periods that are present in the real catalog. While mean aftershock productivity of the observed catalog is matched closely by UCERF3-ETAS, the real catalog has more inter-sequence productivity variability and small mainshocks have more foreshocks. In sum, we find that UCERF3-ETAS differs from the observed catalog in ways that are foreseeable from its modeling simplifications. The tests we present here can be used on any model which produces suites of synthetic catalogs; as such, in addition to providing avenues for future improvements to the model, they could also be incorporated into testing platforms such as Collaboratory for the Study of Earthquake Predictability (CSEP).

Bulletin of the Seismological Society of America↗
USGS2017

A synoptic view of the Third Uniform California Earthquake Rupture Forecast (UCERF3)

Probabilistic forecasting of earthquake‐producing fault ruptures informs all major decisions aimed at reducing seismic risk and improving earthquake resilience. Earthquake forecasting models rely on two scales of hazard evolution: long‐term (decades to centuries) probabilities of fault rupture, constrained by stress renewal statistics, and short‐term (hours to years) probabilities of distributed seismicity, constrained by earthquake‐clustering statistics. Comprehensive datasets on both hazard scales have been integrated into the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3). UCERF3 is the first model to provide self‐consistent rupture probabilities over forecasting intervals from less than an hour to more than a century, and it is the first capable of evaluating the short‐term hazards that result from multievent sequences of complex faulting. This article gives an overview of UCERF3, illustrates the short‐term probabilities with aftershock scenarios, and draws some valuable scientific conclusions from the modeling results. In particular, seismic, geologic, and geodetic data, when combined in the UCERF3 framework, reject two types of fault‐based models: long‐term forecasts constrained to have local Gutenberg–Richter scaling, and short‐term forecasts that lack stress relaxation by elastic rebound.

Seismological Research Letters↗
USGS2017

A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast

We, the ongoing Working Group on California Earthquake Probabilities, present a spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3), with the goal being to represent aftershocks, induced seismicity, and otherwise triggered events as a potential basis for operational earthquake forecasting (OEF). Specifically, we add an epidemic‐type aftershock sequence (ETAS) component to the previously published time‐independent and long‐term time‐dependent forecasts. This combined model, referred to as UCERF3‐ETAS, collectively represents a relaxation of segmentation assumptions, the inclusion of multifault ruptures, an elastic‐rebound model for fault‐based ruptures, and a state‐of‐the‐art spatiotemporal clustering component. It also represents an attempt to merge fault‐based forecasts with statistical seismology models, such that information on fault proximity, activity rate, and time since last event are considered in OEF. We describe several unanticipated challenges that were encountered, including a need for elastic rebound and characteristic magnitude–frequency distributions (MFDs) on faults, both of which are required to get realistic triggering behavior. UCERF3‐ETAS produces synthetic catalogs of M ≥2.5 events, conditioned on any prior M ≥2.5 events that are input to the model. We evaluate results with respect to both long‐term (1000 year) simulations as well as for 10‐year time periods following a variety of hypothetical scenario mainshocks. Although the results are very plausible, they are not always consistent with the simple notion that triggering probabilities should be greater if a mainshock is located near a fault. Important factors include whether the MFD near faults includes a significant characteristic earthquake component, as well as whether large triggered events can nucleate from within the rupture zone of the mainshock. Because UCERF3‐ETAS has many sources of uncertainty, as will any subsequent version or competing model, potential usefulness needs to be considered in the context of actual applications.

California↗
USGS2016

Potentially induced earthquakes during the early twentieth century in the Los Angeles Basin

Recent studies have presented evidence that early to mid‐twentieth‐century earthquakes in Oklahoma and Texas were likely induced by fossil fuel production and/or injection of wastewater ( Hough and Page, 2015 ; Frohlich et al. , 2016 ). Considering seismicity from 1935 onward, Hauksson et al. (2015) concluded that there is no evidence for significant induced activity in the greater Los Angeles region between 1935 and the present. To explore a possible association between earthquakes prior to 1935 and oil and gas production, we first revisit the historical catalog and then review contemporary oil industry activities. Although early industry activities did not induce large numbers of earthquakes, we present evidence for an association between the initial oil boom in the greater Los Angeles area and earthquakes between 1915 and 1932, including the damaging 22 June 1920 Inglewood and 8 July 1929 Whittier earthquakes. We further consider whether the 1933 M w 6.4 Long Beach earthquake might have been induced, and show some evidence that points to a causative relationship between the earthquake and activities in the Huntington Beach oil field. The hypothesis that the Long Beach earthquake was either induced or triggered by an foreshock cannot be ruled out. Our results suggest that significant earthquakes in southern California during the early twentieth century might have been associated with industry practices that are no longer employed (i.e., production without water reinjection), and do not necessarily imply a high likelihood of induced earthquakes at the present time.

California↗
USGS2016

Three ingredients for Improved global aftershock forecasts: Tectonic region, time-dependent catalog incompleteness, and inter-sequence variability

Following a large earthquake, seismic hazard can be orders of magnitude higher than the long‐term average as a result of aftershock triggering. Because of this heightened hazard, emergency managers and the public demand rapid, authoritative, and reliable aftershock forecasts. In the past, U.S. Geological Survey (USGS) aftershock forecasts following large global earthquakes have been released on an ad hoc basis with inconsistent methods, and in some cases aftershock parameters adapted from California. To remedy this, the USGS is currently developing an automated aftershock product based on the Reasenberg and Jones (1989) method that will generate more accurate forecasts. To better capture spatial variations in aftershock productivity and decay, we estimate regional aftershock parameters for sequences within the García et al. (2012) tectonic regions. We find that regional variations for mean aftershock productivity reach almost a factor of 10. We also develop a method to account for the time‐dependent magnitude of completeness following large events in the catalog. In addition to estimating average sequence parameters within regions, we develop an inverse method to estimate the intersequence parameter variability. This allows for a more complete quantification of the forecast uncertainties and Bayesian updating of the forecast as sequence‐specific information becomes available.

California↗