Geology topics

Andrea L. Llenos

Publications and source records attributed to Andrea L. Llenos.

35 records · Page 2Linked to original sources

USGS2020

Regionally Optimized Background Earthquake Rates from ETAS (ROBERE) for probabilistic seismic hazard assessment

We use an epidemic‐type aftershock sequence (ETAS) based approach to develop a regionally optimized background earthquake rates from ETAS (ROBERE) method for probabilistic seismic hazard assessment. ROBERE fits parameters to the full seismicity catalog for a region with maximum‐likelihood estimation, including uncertainty. It then averages the earthquake rates over a suite of catalogs from which foreshocks and aftershocks have been removed using stochastic declustering while maintaining the same Gaussian smoothing currently used for the U.S. Geological Survey National Seismic Hazard Model (NSHM). The NSHM currently determines these rates by smoothing a single catalog from which foreshocks and aftershocks have been removed using the method of Gardner and Knopoff (1974 ; hereafter, GK74). The parameters used in GK74 were determined from subjectively identified aftershock sequences, unlike ROBERE, in which both background rate and aftershock triggering parameters are objectively fitted. A major difference between the impacts of the two methods is GK74 significantly reduces the b "> b ‐value, a critical value for seismic hazard analysis, whereas ROBERE maintains the original b "> b ‐value from the full catalog. We apply these methods to the induced seismicity in Oklahoma and Kansas and tectonic activity in the San Francisco Bay Region. Using GK74 gives lower overall earthquake rates but estimates higher hazard due to the reduction in the b "> b ‐value. ROBERE provides higher earthquake rates, at the magnitude of completeness, but lower hazard because it does not alter the b "> b ‐value. We test two other declustering methods that produce results closer to ROBERE but do not use objectively fit parameters, include uncertainty, and may not work as well in other areas. We suggest adopting ROBERE for the NSHM so that our hazard estimates are based on an objective analysis, including uncertainty, and do not depend strongly on potentially biased b "> b ‐values, which was never the goal of the existing methodology.

Bulletin of the Seismological Society of America↗

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

Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm

Earthquake swarms, typically modeled as time-varying changes in background seismicity that are driven by external processes such as fluid flow or aseismic creep, present challenges for operational earthquake forecasting. While the time decay of aftershock sequences can be estimated with the modified Omori law, it is difficult to forecast the temporal behavior of seismicity rates during a swarm. To explore these issues, we apply the Epidemic-Type Aftershock Sequence (ETAS) model (Ogata, JASA, 1988) to the 2015 San Ramon, California swarm, which lasted several weeks and had almost 100 2≤M≤3.6 earthquakes. We develop 3-day forecasts during the swarm based on an ETAS model fit to all prior seismicity in the region as well as an ETAS model fit only to previous swarms in the region, which is better at capturing the higher background rate during the swarm. We also explore forecasts where the background rate is updated periodically during the swarm using data over different lookback windows and find that generally these models perform better than the models where the background rate is fixed. Finally, we construct ensemble forecasts by combining the different models weighted according to their performance. The ensemble forecasts outperform all of the individual models and allow us to avoid making arbitrary choices at the outset of a swarm as to which single model will perform the best.

California↗

USGS2019

Improving earthquake forecasts during swarms with a duration model

Earthquake swarms present a challenge for operational earthquake forecasting because they are driven primarily by transient external processes, such as fluid flow, the behavior and duration of which are difficult to predict. In this study, we develop a swarm duration model to estimate how long a swarm is likely to last based on actuarial statistics of previous swarms in a given region. We demonstrate this approach using swarms that have been identified in the Salton trough in southern California, finding that swarms last an average of ∼ 7 "> ∼ 7 ∼7 days and have a relatively constant 15%–16% chance of terminating each day for the first 14 days of the swarm. Cataloged swarm durations are exponentially distributed, so we use a Poissonian model for swarm termination to encapsulate and extend the actuarial statistics. We then show how using the swarm duration model would have affected the earthquake forecast that was released during the 2016 Bombay Beach swarm. The earthquake forecast is substantially improved by incorporating a probabilistic model for how long the swarm is likely to last.

Bulletin of the Seismological Society of America↗

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

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 ≥ 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 ≥ 3 "> M ≥ 3 and 4 M ≥ 4 "> M ≥ 4 ), Raton basin (Colorado/New Mexico border, six earthquakes M ≥ 3 "> M ≥ 3 ), and the New Madrid seismic zone (11 earthquakes M ≥ 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 ≥ 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↗

USGS2017

Forecasting the (un)productivity of the 2014 M 6.0 South Napa aftershock sequence

The 24 August 2014 M w 6.0 South Napa mainshock produced fewer aftershocks than expected for a California earthquake of its magnitude. In the first 4.5 days, only 59 M ≥1.8 aftershocks occurred, the largest of which was an M 3.9 that happened a little over two days after the mainshock. We investigate the aftershock productivity of the South Napa sequence and compare it with other M ≥5.5 California strike‐slip mainshock–aftershock sequences. While the productivity of the South Napa sequence is among the lowest, northern California mainshocks generally have fewer aftershocks than mainshocks further south, although the productivities vary widely in both regions. An epidemic‐type aftershock sequence (ETAS) model ( Ogata, 1988 ) fit to Napa seismicity from 1980 to 23 August 2014 fits the sequence well and suggests that low‐productivity sequences are typical of this area. Utilizing regional variations in productivity could improve operational earthquake forecasting (OEF) by improving the model used immediately after the mainshock. We show this by comparing the daily rate of M ≥2 aftershocks to forecasts made with the generic California model ( Reasenberg and Jones, 1989 ; hereafter, RJ89), RJ89 models with productivity updated daily, a generic California ETAS model, an ETAS model based on premainshock seismicity, and ETAS models updated daily following the mainshock. RJ89 models for which only the productivity is updated provide better forecasts than the generic RJ89 California model, and the Napa‐specific ETAS models forecast the aftershock rates more accurately than either generic model. Therefore, forecasts that use localized initial parameters and that rapidly update the productivity may be better for OEF than using a generic model and/or updating all parameters.

California↗

USGS2017

2017 One‐year seismic‐hazard forecast for the central and eastern United States from induced and natural earthquakes

We produce a one‐year 2017 seismic‐hazard forecast for the central and eastern United States from induced and natural earthquakes that updates the 2016 one‐year forecast; this map is intended to provide information to the public and to facilitate the development of induced seismicity forecasting models, methods, and data. The 2017 hazard model applies the same methodology and input logic tree as the 2016 forecast, but with an updated earthquake catalog. We also evaluate the 2016 seismic‐hazard forecast to improve future assessments. The 2016 forecast indicated high seismic hazard (greater than 1% probability of potentially damaging ground shaking in one year) in five focus areas: Oklahoma–Kansas, the Raton basin (Colorado/New Mexico border), north Texas, north Arkansas, and the New Madrid Seismic Zone. During 2016, several damaging induced earthquakes occurred in Oklahoma within the highest hazard region of the 2016 forecast; all of the 21 moment magnitude ( M ) ≥4 and 3 M ≥5 earthquakes occurred within the highest hazard area in the 2016 forecast. Outside the Oklahoma–Kansas focus area, two earthquakes with M ≥4 occurred near Trinidad, Colorado (in the Raton basin focus area), but no earthquakes with M ≥2.7 were observed in the north Texas or north Arkansas focus areas. Several observations of damaging ground‐shaking levels were also recorded in the highest hazard region of Oklahoma. The 2017 forecasted seismic rates are lower in regions of induced activity due to lower rates of earthquakes in 2016 compared with 2015, which may be related to decreased wastewater injection caused by regulatory actions or by a decrease in unconventional oil and gas production. Nevertheless, the 2017 forecasted hazard is still significantly elevated in Oklahoma compared to the hazard calculated from seismicity before 2009.

Seismological Research Letters↗

USGS2016

Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States

The U.S. Geological Survey (USGS) has produced a one‐year (2016) probabilistic seismic‐hazard assessment for the central and eastern United States (CEUS) that includes contributions from both induced and natural earthquakes that are constructed with probabilistic methods using alternative data and inputs. This hazard assessment builds on our 2016 final model ( Petersen et al. , 2016 ) by adding sensitivity studies, illustrating hazard in new ways, incorporating new population data, and discussing potential improvements. The model considers short‐term seismic activity rates (primarily 2014–2015) and assumes that the activity rates will remain stationary over short time intervals. The final model considers different ways of categorizing induced and natural earthquakes by incorporating two equally weighted earthquake rate submodels that are composed of alternative earthquake inputs for catalog duration, smoothing parameters, maximum magnitudes, and ground‐motion models. These alternatives represent uncertainties on how we calculate earthquake occurrence and the diversity of opinion within the science community. In this article, we also test sensitivity to the minimum moment magnitude between M 4 and M 4.7 and the choice of applying a declustered catalog with b =1.0 rather than the full catalog with b =1.3. We incorporate two earthquake rate submodels: in the informed submodel we classify earthquakes as induced or natural, and in the adaptive submodel we do not differentiate. The alternative submodel hazard maps both depict high hazard and these are combined in the final model. Results depict several ground‐shaking measures as well as intensity and include maps showing a high‐hazard level (1% probability of exceedance in 1 year or greater). Ground motions reach 0.6 g horizontal peak ground acceleration (PGA) in north‐central Oklahoma and southern Kansas, and about 0.2 g PGA in the Raton basin of Colorado and New Mexico, in central Arkansas, and in north‐central Texas near Dallas–Fort Worth. The chance of having levels of ground motions corresponding to modified Mercalli intensity (MMI) VI or greater earthquake shaking is 2%–12% per year in north‐central Oklahoma and southern Kansas and New Madrid similar to the chance of damage at sites in high‐hazard portions of California caused by natural earthquakes. Hazard is also significant in the Raton basin of Colorado/New Mexico; north‐central Arkansas; Dallas–Fort Worth, Texas; and in a few other areas. Hazard probabilities are much lower (by about half or more) for exceeding MMI VII or VIII. Hazard is 3‐ to 10‐fold higher near some areas of active‐induced earthquakes than in the 2014 USGS National Seismic Hazard Model (NSHM), which did not consider induced earthquakes. This study in conjunction with the LandScan TM Database (2013) indicates that about 8 million people live in areas of active injection wells that have a greater than 1% chance of experiencing damaging ground shaking (MMI≥VI) in 2016. The final model has high uncertainty, and engineers, regulators, and industry should use these assessments cautiously to make informed decisions on mitigating the potential effects of induced and natural earthquakes.

Seismological Research Letters↗

USGS2016

Characterizing potentially induced earthquake rate changes in the Brawley Seismic Zone, southern California

The Brawley seismic zone (BSZ), in the Salton trough of southern California, has a history of earthquake swarms and geothermal energy exploitation. Some earthquake rate changes may have been induced by fluid extraction and injection activity at local geothermal fields, particularly at the North Brawley Geothermal Field (NBGF) and at the Salton Sea Geothermal Field (SSGF). We explore this issue by examining earthquake rate changes and interevent distance distributions in these fields. In Oklahoma and Arkansas, where considerable wastewater injection occurs, increases in background seismicity rate and aftershock productivity and decreases in interevent distance were indicative of fluid‐injection‐induced seismicity. Here, we test if similar changes occur that may be associated with fluid injection and extraction in geothermal areas. We use stochastic epidemic‐type aftershock sequence models to detect changes in the underlying seismogenic processes, shown by statistically significant changes in the model parameters. The most robust model changes in the SSGF roughly occur when large changes in net fluid production occur, but a similar correlation is not seen in the NBGF. Also, although both background seismicity rate and aftershock productivity increased for fluid‐injection‐induced earthquake rate changes in Oklahoma and Arkansas, the background rate increases significantly in the BSZ only, roughly corresponding with net fluid production rate increases. Moreover, in both fields the interevent spacing does not change significantly during active energy projects. This suggests that, although geothermal field activities in a tectonically active region may not significantly change the physics of earthquake interactions, earthquake rates may still be driven by fluid injection or extraction rates, particularly in the SSGF.

California↗

USGS2016

2016 one-year seismic hazard forecast for the Central and Eastern United States from induced and natural earthquakes

The U.S. Geological Survey (USGS) has produced a 1-year seismic hazard forecast for 2016 for the Central and Eastern United States (CEUS) that includes contributions from both induced and natural earthquakes. The model assumes that earthquake rates calculated from several different time windows will remain relatively stationary and can be used to forecast earthquake hazard and damage intensity for the year 2016. This assessment is the first step in developing an operational earthquake forecast for the CEUS, and the analysis could be revised with updated seismicity and model parameters. Consensus input models consider alternative earthquake catalog durations, smoothing parameters, maximum magnitudes, and ground motion estimates, and represent uncertainties in earthquake occurrence and diversity of opinion in the science community. Ground shaking seismic hazard for 1-percent probability of exceedance in 1 year reaches 0.6 g (as a fraction of standard gravity [g]) in northern Oklahoma and southern Kansas, and about 0.2 g in the Raton Basin of Colorado and New Mexico, in central Arkansas, and in north-central Texas near Dallas. Near some areas of active induced earthquakes, hazard is higher than in the 2014 USGS National Seismic Hazard Model (NHSM) by more than a factor of 3; the 2014 NHSM did not consider induced earthquakes. In some areas, previously observed induced earthquakes have stopped, so the seismic hazard reverts back to the 2014 NSHM. Increased seismic activity, whether defined as induced or natural, produces high hazard. Conversion of ground shaking to seismic intensity indicates that some places in Oklahoma, Kansas, Colorado, New Mexico, Texas, and Arkansas may experience damage if the induced seismicity continues unabated. The chance of having Modified Mercalli Intensity (MMI) VI or greater (damaging earthquake shaking) is 5–12 percent per year in north-central Oklahoma and southern Kansas, similar to the chance of damage caused by natural earthquakes at sites in parts of California.

Open-File Report↗

USGS2015

The Mw6.0 24 August 2014 South Napa earthquake

The M w 6.0 South Napa earthquake, which occurred at 10:20 UTC 24 August 2014 was the largest earthquake to strike the greater San Francisco Bay area since the M w 6.9 1989 Loma Prieta earthquake. The rupture from this right‐lateral earthquake propagated mostly unilaterally to the north and up‐dip, directing the strongest shaking toward the city of Napa, where peak ground accelerations (PGAs) between 45% g and 61% g were recorded and modified Mercalli intensities (MMIs) of VII–VIII were reported. Tectonic surface rupture with dextral slip of up to 46 cm was observed on a 12.5 km long segment, some of which was along a previously mapped strand of the West Napa fault system, although the rupture extended to the north of the mapped Quaternary strand. Modeling of seismic and geodetic data suggests an average coseismic slip of 50 cm, with a maximum slip of about 1 m at depths of 10–11 km. We observed up to 35 cm of afterslip along the surface trace in the week following the mainshock, primarily along the southern half of the surface rupture that experienced relatively little coseismic offset. Relocation of the sparse aftershock sequence suggests en echelon southwest‐ and northeast‐dipping fault planes, reflective of the complex fault geometry in this region. The Napa basin and historic and late Holocene alluvial flood deposits in downtown Napa amplified the ground motions there. Few ground failures were mapped, reflecting the dry season (as well as a persistent drought that had lowered the groundwater table) and the short duration of strong shaking in the epicentral area.

California↗

USGS2015

Increasing seismicity in the U. S. midcontinent: Implications for earthquake hazard

Earthquake activity in parts of the central United States has increased dramatically in recent years. The space-time distribution of the increased seismicity, as well as numerous published case studies, indicates that the increase is of anthropogenic origin, principally driven by injection of wastewater coproduced with oil and gas from tight formations. Enhanced oil recovery and long-term production also contribute to seismicity at a few locations. Preliminary hazard models indicate that areas experiencing the highest rate of earthquakes in 2014 have a short-term (one-year) hazard comparable to or higher than the hazard in the source region of tectonic earthquakes in the New Madrid and Charleston seismic zones.

The Leading Edge↗

USGS2015

Incorporating induced seismicity in the 2014 United States National Seismic Hazard Model: results of the 2014 workshop and sensitivity studies

The U.S. Geological Survey National Seismic Hazard Model for the conterminous United States was updated in 2014 to account for new methods, input models, and data necessary for assessing the seismic ground shaking hazard from natural (tectonic) earthquakes. The U.S. Geological Survey National Seismic Hazard Model project uses probabilistic seismic hazard analysis to quantify the rate of exceedance for earthquake ground shaking (ground motion). For the 2014 National Seismic Hazard Model assessment, the seismic hazard from potentially induced earthquakes was intentionally not considered because we had not determined how to properly treat these earthquakes for the seismic hazard analysis. The phrases “potentially induced” and “induced” are used interchangeably in this report, however it is acknowledged that this classification is based on circumstantial evidence and scientific judgment. For the 2014 National Seismic Hazard Model update, the potentially induced earthquakes were removed from the NSHM’s earthquake catalog, and the documentation states that we would consider alternative models for including induced seismicity in a future version of the National Seismic Hazard Model. As part of the process of incorporating induced seismicity into the seismic hazard model, we evaluate the sensitivity of the seismic hazard from induced seismicity to five parts of the hazard model: (1) the earthquake catalog, (2) earthquake rates, (3) earthquake locations, (4) earthquake Mmax (maximum magnitude), and (5) earthquake ground motions. We describe alternative input models for each of the five parts that represent differences in scientific opinions on induced seismicity characteristics. In this report, however, we do not weight these input models to come up with a preferred final model. Instead, we present a sensitivity study showing uniform seismic hazard maps obtained by applying the alternative input models for induced seismicity. The final model will be released after further consideration of the reliability and scientific acceptability of each alternative input model. Forecasting the seismic hazard from induced earthquakes is fundamentally different from forecasting the seismic hazard for natural, tectonic earthquakes. This is because the spatio-temporal patterns of induced earthquakes are reliant on economic forces and public policy decisions regarding extraction and injection of fluids. As such, the rates of induced earthquakes are inherently variable and nonstationary. Therefore, we only make maps based on an annual rate of exceedance rather than the 50-year rates calculated for previous U.S. Geological Survey hazard maps.

Open-File Report↗

USGS2013

Modeling earthquake rate changes in Oklahoma and Arkansas: possible signatures of induced seismicity

The rate of ML≥3 earthquakes in the central and eastern United States increased beginning in 2009, particularly in Oklahoma and central Arkansas, where fluid injection has occurred. We find evidence that suggests these rate increases are man‐made by examining the rate changes in a catalog of ML≥3 earthquakes in Oklahoma, which had a low background seismicity rate before 2009, as well as rate changes in a catalog of ML≥2.2 earthquakes in central Arkansas, which had a history of earthquake swarms prior to the start of injection in 2009. In both cases, stochastic epidemic‐type aftershock sequence models and statistical tests demonstrate that the earthquake rate change is statistically significant, and both the background rate of independent earthquakes and the aftershock productivity must increase in 2009 to explain the observed increase in seismicity. This suggests that a significant change in the underlying triggering process occurred. Both parameters vary, even when comparing natural to potentially induced swarms in Arkansas, which suggests that changes in both the background rate and the aftershock productivity may provide a way to distinguish man‐made from natural earthquake rate changes. In Arkansas we also compare earthquake and injection well locations, finding that earthquakes within 6 km of an active injection well tend to occur closer together than those that occur before, after, or far from active injection. Thus, like a change in productivity, a change in interevent distance distribution may also be an indicator of induced seismicity.

Arkansas;Oklahoma↗

USGS2013

Near real-time monitoring of volcanic surface deformation from GPS measurements at Long Valley Caldera, California

Long Valley Caldera in eastern California is an active volcanic area and has shown continued unrest in the last three decades. We have monitored surface deformation from Global Positioning System (GPS) data by using a projection method that we call Targeted Projection Operator (TPO). TPO projects residual time series with secular rates and periodic terms removed onto a predefined spatial pattern. We used the 2009–2010 slow deflation as a target spatial pattern. The resulting TPO time series shows a detailed deformation history including the 2007–2009 inflation, the 2009–2010 deflation, and a recent inflation that started in late-2011 and is continuing at the present time (November 2012). The recent inflation event is about four times faster than the previous 2007–2009 event. A Mogi source of the recent event is located beneath the resurgent dome at about 6.6 km depth at a rate of 0.009 km3/yr volume change. TPO is simple and fast and can provide a near real-time continuous monitoring tool without directly looking at all the data from many GPS sites in this potentially eruptive volcanic system.

California↗

USGS2011

Detecting aseismic strain transients from seismicity data

Aseismic deformation transients such as fluid flow, magma migration, and slow slip can trigger changes in seismicity rate. We present a method that can detect these seismicity rate variations and utilize these anomalies to constrain the underlying variations in stressing rate. Because ordinary aftershock sequences often obscure changes in the background seismicity caused by aseismic processes, we combine the stochastic Epidemic Type Aftershock Sequence model that describes aftershock sequences well and the physically based rate‐ and state‐dependent friction seismicity model into a single seismicity rate model that models both aftershock activity and changes in background seismicity rate. We implement this model into a data assimilation algorithm that inverts seismicity catalogs to estimate space‐time variations in stressing rate. We evaluate the method using a synthetic catalog, and then apply it to a catalog of M ≥ 1.5 events that occurred in the Salton Trough from 1990 to 2009. We validate our stressing rate estimates by comparing them to estimates from a geodetically derived slip model for a large creep event on the Obsidian Buttes fault. The results demonstrate that our approach can identify large aseismic deformation transients in a multidecade long earthquake catalog and roughly constrain the absolute magnitude of the stressing rate transients. Our method can therefore provide a way to detect aseismic transients in regions where geodetic resolution in space or time is poor.

Journal of Geophysical Research B: Solid Earth↗