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USGS2020

Earthquake magnitude and Lg Q variations between the Grenville and northern Appalachian geologic provinces of eastern Canada

This article assesses the ability of regionally specific, frequency‐dependent crustal attenuation ( ⁠ 1 / Q "> 1 / Q ⁠ ) to reduce mean magnitude discrepancies between seismic stations in the northern Appalachian and Grenville provinces (NAP and GP) of Canada. Lg Q ( f ) "> Q ( f ) is an important parameter in ground‐motion models used in probabilistic seismic hazard analysis. Discrepancies in regional magnitude estimates have long been noted to exist between stations in the two provinces for common event origins. Such discrepancies could arise from systematic site condition variations between the geologic provinces or from varying crustal attenuative properties. To evaluate the effect of frequency‐dependent anelastic attenuation, Lg Q ( f ) "> Q ( f ) on estimated magnitudes, we analyze Lg amplitudes from > 6000 "> > 6000 waveforms recorded by Grenville and northern Appalachian receivers from 420 natural earthquakes of M N "> M N magnitude 3–5.6. Waveform analysis is strictly limited to analyst‐reviewed, vertical‐component waveforms in which Lg is clearly identified, ensuring that the datasets exhibit dominant, high‐frequency energy in the Lg velocity window. Lg Q ( f ) "> Q ( f ) is found to be higher in the GP than in the northern Appalachians. In the Grenville, Q ( f ) = 761 ( ± 145 ) f 0.25 ( ± 0.014 ) "> Q ( f ) = 761 ( ± 145 ) f 0.25 ( ± 0.014 ) ⁠ , and in the northern Appalachians, attenuation is higher: Q ( f ) = 506 ( ± 172 ) f 0.33 ( ± 0.310 ) "> Q ( f ) = 506 ( ± 172 ) f 0.33 ( ± 0.310 ) . Earthquake magnitude determined using the peak amplitude of the Lg phase ( ⁠ m b L g "> m b L g ) for eastern Canada is corrected to incorporate the frequency‐dependent, regionally specific Lg Q ( f ) "> Q ( f ) determined in this study. Using the new Lg Q ( f ) "> Q ( f ) values diminishes and nearly resolves magnitude discrepancies between the provinces. Correcting regional magnitude discrepancies between provinces is critical for reliable regional seismic hazard estimates because magnitude error in a particular region could lead to increased uncertainty in seismic hazard models.

Grenville Geologic Province, Northern Appalachian ↗
USGS2020

Basin amplification effects in the Puget Lowland, Washington from strong motion recordings and 3D simulations

Sedimentary basins in the Puget Sound region, Washington State, increase ground‐motion intensity and duration of shaking during local earthquakes. We analyze Pacific Northwest Seismic Network and U.S. Geological Survey strong‐motion recordings of five local earthquakes ( M 3.9–6.8), including the 2001 Nisqually earthquake, to characterize sedimentary basin effects within the Seattle and Tacoma basins. We observe basin‐edge generated surface waves at sites within the Seattle basin for most ray paths that cross the Seattle fault zone. We also note previously undocumented basin‐edge surface waves in the Tacoma basin during one of the local earthquakes. To place quantitative constraints on basin amplification, we determine amplification factors by computing the spectral ratios of inside‐basin sites to outside‐basin sites at 1, 2, 3, and 5 s periods. Ground shaking is amplified in the Seattle basin for all the earthquakes analyzed and for a subset of events in the Tacoma basin. We find that the largest amplification factors in the Seattle basin are produced by a shallow earthquake located to the southwest of the basin. Our observation suggests that future shallow crustal and megathrust earthquakes rupturing west of the Puget Lowland will produce greater amplification within the Seattle basin than has been seen for intraslab events. We also perform ground‐motion simulations using a finite‐difference method to validate a 3D Cascadia velocity model (CVM) by comparing properties of observed and synthetic waveforms up to a frequency of 1 Hz. Basin‐edge effects are well reproduced in the Seattle basin, but are less well resolved in the Tacoma basin. Continued study of basin effects in the Tacoma basin would improve the CVM.

Washington↗
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↗
USGS2020

Evolution of faulting induced by deep fluid injection, Paradox Valley, Colorado

High‐pressure fluid injection into a subhorizontal confined aquifer at 4.3–4.6 km depth induced > 7000 "> > 7000 >7000 earthquakes between 1991 and 2012 within once seismically quiescent Paradox Valley in Colorado, with magnitudes up to M w "> M w Mw 3.9. Earthquake hypocenters expanded laterally away from the well with time, defining the margins of the aquifer pressurized by injection at the well. Within 5 km of the well, alignment of earthquake hypocenters defines strikes of nine vertical fault zones. Previous studies show that these fault zones predate injection, producing left‐stepping offsets in the normal faults of the Wray‐Mesa fault system that cradles Paradox Valley. Hypocenters, rakes, and strikes of 2041 well‐constrained focal mechanisms show that most injection‐related earthquakes occur where these vertical faults intersect the pressurized aquifer. Well‐defined focal mechanisms show that this induced seismicity consists of Riedel shear faults at acute angles to the strikes of these fault zones. These small faults develop an anastomosing fault structure of focal planes along each planar fault zone, as fluid injection continues, even as their hypocenters define a single planar fault zone. Failure conditions at each hypocenter are found using a fully coupled poroelastic analysis of stress induced by fluid injection, and this analysis indicates a minimum Coulomb failure condition of 0.1 MPa. This failure condition is primarily a result of aquifer pore‐fluid pressurization, as almost all well‐located seismicity is within the pressurized aquifer. Reducing the rate of injection and frequent well shutdowns in the second decade nearly eliminated induced seismicity, except very near the well where gradients in pressurization are the largest. Despite these decreases in failure conditions and seismicity, some fault zones continued to produce earthquakes larger than M 3 as injection continued.

California↗
USGS2020

Types and areal distribution of ground failure associated with the 2019 Ridgecrest, California, earthquake sequence

T he July 2019 Ridgecrest, California, earthquake sequence included the largest earthquake ( M 7.1) to strike the conterminous United States in the past 20 yr. To characterize the types, numbers, and areal distributions of different types of ground failure (landslides, liquefaction, and ground cracking), I conducted a field investigation of ground failure triggered by the sequence around the periphery of the epicentral area (which had limited access). The earthquake sequence triggered sparse and widely scattered landslides over an area of ∼ 22 , 000    km 2 "> ∼ 22 , 000 km 2 ∼22,000 km2 and at a maximum epicentral distance of 114 km; these metrics are within the upper bounds as compared with global averages for earthquakes of similar size. Some rock falls blocked primary and secondary roads, but no other landslide damage was reported. Almost all of the landslides in the peripheral area were small rock falls ( ⁠ ∼ 1 – 10    m 3 "> ∼ 1 – 10 m 3 ∼1–10 m3 ⁠ ), but a few larger ( ⁠ ∼ 100    m 3 "> ∼ 100 m 3 ∼100 m3 ⁠ ) rock slides also occurred. Though there are only informal reports about ground failure in the immediate epicentral area and we lack a detailed survey there, the small number (hundreds) and size of the landslides still seems to be far below global averages for M 7.1. This could be a result of the arid landscape and lack of a deeply weathered zone of soil and regolith. Liquefaction occurred along part of the western margin of Searles Valley. One large ( ⁠ ∼ 0.4    km 2 "> ∼ 0.4 km 2 ∼0.4 km2 ⁠ ) lateral spread caused by liquefaction severely damaged parts of Trona. Minor liquefaction also occurred in a ∼ 100 ‐ m ‐ wide "> ∼ 100 ‐ m ‐ wide ∼100‐m‐wide band along the fault‐rupture zone in some places.

California↗
USGS2020

Repeatable source, path, and site effects from the 2019 Ridgecrest M7.1 earthquake sequence

We use a large instrumental dataset from the 2019 Ridgecrest earthquake sequence ( Rekoske et al. , 2019 , 2020 ) to examine repeatable source‐, path‐, and site‐specific ground motions. A mixed‐effects analysis is used to partition total residuals relative to the Boore et al. (2014 ; hereafter, BSSA14) ground‐motion model. We calculate the Arias intensity stress drop for the earthquakes and find strong correlation with our event terms, indicating that they are consistent with source processes. We look for physically meaningful trends in the partitioned residuals and test the ability of BSSA14 to capture the behavior we observe in the data. We find that BSSA14 is a good match to the median observations for M > 4 "> M > 4 M>4 ⁠ . However, we find bias for individual events, especially those with small magnitude and hypocentral depth ≥ 7    km "> depth ≥ 7 km depth≥7 km ⁠ , for which peak ground acceleration is underpredicted by a factor of 2.5. Although the site amplification term captures the median site response when all sites are considered together, it does not capture variations at individual stations across a range of site conditions. We find strong basin amplification in the Los Angeles, Ventura, and San Gabriel basins. We find weak amplification in the San Bernardino basin, which is contrary to simulation‐based findings showing a channeling effect from an event with a north–south azimuth. This and an additional set of ground motions from earthquakes southwest of Los Angeles suggest that there is an azimuth‐dependent southern California basin response related to the orientation of regional structures when ground motion from waves traveling south–north are compared with those in the east–west direction. These findings exhibit the power of large, spatially dense ground‐motion datasets and make clear that nonergodic models are a way to reduce bias and uncertainty in ground‐motion estimation for applications like the U.S. Geological Survey National Seismic Hazard Model and the ShakeAlert earthquake early warning System.

California↗
USGS2020

A stress-similarity triggering model for aftershocks of the MW6.4 and MW7.1 Ridgecrest earthquakes

The July 2019 M w "> M w 6.4 and 7.1 Ridgecrest earthquakes triggered numerous aftershocks, including clusters of off‐fault aftershocks in an extensional stepover of the Garlock fault, near the town of Olancha, and near Panamint Valley. The locations of the off‐fault aftershocks are consistent with the stress‐similarity model of triggering, which hypothesizes that aftershocks preferentially occur in areas where the mainshock static stress change tensor is similar in orientation to the background stress tensor. The background stress field is determined from the inversion of earthquake focal mechanisms, with the spatial resolution adapted to the local density of earthquakes. The mainshock static stress change is computed using finite‐source models for the M w "> M w 6.4 foreshock and M w "> M w 7.1 mainshock. I quantify the similarity between these two stress fields using the tensor dot product of the normalized deviatoric stress tensors. The off‐fault aftershocks in the Garlock stepover and the Olancha area fall within lobes of positive stress similarity, whereas the aftershocks near Panamint Valley are partially within a lobe. The cluster in the Garlock fault stepover and the smaller of two clusters near Olancha occur in regions of locally anomalous background stress that results in higher stress similarity. I compute the spatial density of M ≥ 2.0 "> M≥2.0 aftershocks and find that the aftershock density increases as a function of stress similarity, with a factor of ∼ 15 "> ∼15 difference between high stress‐similarity and low stress‐similarity areas. This result is robust with respect to the choice of mainshock model and the uncertainty of the background stress field. The aftershock density varies substantially inside the high stress‐similarity lobes, however, indicating that other variable background conditions, such as material properties, temperature, and fluid pressure, may also be playing a role. Specifically, temperature and fluid pressure conditions might help explain the low rate of aftershocks in the Coso geothermal field.

California↗
USGS2020

Seismicity rate change at the Coso Geothermal Field following the July 2019 Ridgecrest M7.1 earthquake

Many geothermal and volcanic regions experience remote and regional triggering following large earthquakes. The transient or permanent changes in stresses acting on faults and fractures can lead to changes in seismicity rates following either the passage of teleseismic waves or the permanent change in stresses following regional events. One such region of prevalent triggering is the Coso Geothermal Field (CGF) in eastern California, which is located roughly 30km to the north of the 2019 M7.1 Ridgecrest epicenter. Previous regional earthquakes have seemingly caused increases in seismicity rate surrounding the CGF, but also showed an absence of such rate increases in the CGF itself. To test whether seismicity rates in the CGF were dissimilar to the surrounding area following the M7.1 Ridgecrest earthquake, I carry out seismicity rate change calculations using a catalog of seismicity complied using a local seismic network and find that the CGF behaves identical to the surrounding area. Comparisons of seismicity rate changes calculated using a regional network derived catalog and the local network derived catalog show that for a moderate, regional earthquake, the local network catalog reveals a change in seismicity rate while the regionally network catalog shows no significant changes. The differences are likely related to incomplete sampling of seismicity using the regional network due to the existence of a very shallow brittle ductile transition centered on the CGF. The CGF thus is prone to triggering from both teleseismic and regional earthquakes.

California↗
USGS2020

Kinematics of fault slip associated with the July 4-6 2019 Ridgecrest, Californai earthquakes sequence

The 2019 Ridgecrest, California, earthquake sequence produced observable crustal deformation over much of central and southern California, as well as surface rupture over several tens of kilometers. To obtain a detailed picture of the fault slip involved in the 4 July M 6.4 foreshock and 6 July M 7.1 mainshock, we combine strong‐motion seismic waveforms with crustal deformation observations to obtain kinematic and static slip models of both events. We sample the regional seismic wavefield for both the foreshock and mainshock with three‐component records from 31 stations of the California Integrated Seismic Network. The deformation observations include Global Positioning System (GPS), Interferometric Synthetic Aperture Radar (InSAR), and borehole strainmeter recordings of the dynamic strain field. These data collectively constrain the kinematic coseismic slip distributions of the events, with measurements variously observing coseismic slip from one event (e.g., seismic waveforms, kinematic solutions from continuous GPS, and strainmeter time series) or coseismic slip from both events combined (InSAR). We find that the foreshock ruptured two separate faults, one with left‐lateral strike slip on a northeast–southwest‐trending fault and the other with right‐lateral strike slip on an orthogonal fault, with unilateral rupture propagation along both. The mainshock ruptured a series of northwest–southeast‐trending faults with right‐lateral strike slip concentrated in the uppermost 6 km with exceptionally low‐rupture velocity averaging 1.0 – 1.5    km / s ">

California↗
USGS2020

Magnetic field variations in Alaska: Recording space weather events on seismic stations in Alaska

Seismometers are highly sensitive instruments to not only ground motion but also many other nonseismic noise sources (e.g., temperature, pressure, and magnetic field variations). We show that the Alaska component of the Transportable Array is particularly susceptible to recording magnetic storms and other space weather events because the sensors used in this network are unshielded and magnetic flux variations are stronger at higher latitudes. We also show that vertical‐component seismic records across Alaska are directly recording magnetic field variations between 40 and 800 s period as opposed to actual ground motion during geomagnetic events with sensitivities ranging from 0.004 to 0.48    ( m / s 2 ) / T "> 0.48 ( m / s 2 ) / T 0.48 (m/s2)/T ⁠ . These sensitivities were found on a day where the root mean square variation in the magnetic field was 225 nT. Using a method developed by Forbriger (2007 , his section 3.1), we show that improving vertical seismic resolution of an unshielded sensor by as much as 10 dB in the 100–400 s period band using magnetic data from a collocated three‐component magnetometer is possible. However, due to large spatial variations in Earth’s magnetic field, this methodology becomes increasingly ineffective as the distance between the seismometer and magnetometer increases (no more than 200 km separation). A potential solution to this issue may be to incorporate relatively low‐cost magnetometers as an additional environmental data stream at high‐latitude seismic stations. We demonstrate that the Bartington Mag‐690 sensors currently deployed at Global Seismographic Network sites are not only acceptable for performing corrections to seismic data, but are also capable of recording many magnetic field signals with similar signal‐to‐noise ratios, in the 20–1000 s period band, as the observatory grade magnetometers operated by the U.S. Geological Survey Geomagnetism Program. This approach would densify magnetic field observations and could also contribute to space weather monitoring by supplementing highly calibrated magnetometers with additional sensors.

Alaska↗
USGS2020

Real-time performance of the PLUM earthquake early warning method during the 2019 M6.4 and M7.1 Ridgecrest, California, Earthquakes

We evaluate the timeliness and accuracy of ground‐motion‐based earthquake early warning (EEW) during the July 2019 M 6.4 and 7.1 Ridgecrest earthquakes. In 2018, we began retrospective and internal real‐time testing of the propagation of local undamped motion (PLUM) method for earthquake warning in California, Oregon, and Washington, with the potential that PLUM might one day be included in the ShakeAlert EEW system. A real‐time version of PLUM was running on one of the ShakeAlert EEW system’s development servers at the time of the 2019 Ridgecrest sequence, allowing us to evaluate the timeliness and accuracy of PLUM’s warnings for the M 6.4 and 7.1 mainshocks in real time with the actual data availability and latencies of the operational ShakeAlert EEW system. The latter is especially important because high‐data latencies during the M 7.1 earthquake degraded ShakeAlert’s performance. PLUM proved to be largely immune to these latencies. In this article, we present a retrospective analysis of PLUM performance and explore three potential regional alerting strategies ranging from spatially large regions (counties), to moderate‐size regions (National Weather Service public forecast zones), to high‐spatial specificity (50 km regular geographic grid). PLUM generated initial shaking forecasts for the two mainshocks 5 and 6 s after their respective origin times, and faster than the ShakeAlert system’s first alerts. PLUM was also able to accurately forecast shaking across southern California for all three alerting strategies studied. As would be expected, a cost‐benefit analysis of each approach illustrates trade‐offs between increasing warning time and minimizing the area receiving unneeded alerts. Choosing an optimal alerting strategy requires knowledge of users’ false alarm tolerance and minimum required warning time for taking protective action, as well as the time required to distribute alerts to users.

California↗
USGS2020

Optimizing earthquake early warning alert distance strategies using the July 2019 Mw6.4 and Mw7.1 Ridgecrest, California, earthquakes

The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median‐expected peak ground motions with distance, then using these ground motions to determine median‐expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground‐motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground‐motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground‐motion uncertainties, we find MMI IV alert regions using median‐expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground‐motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade‐off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

California↗
USGS2020

Liquefaction and related ground failure from July 2019 Ridgecrest earthquake sequence

The 2019 Ridgecrest earthquake sequence produced a 4 July M 6.5 foreshock and a 5 July M 7.1 mainshock, along with 23 events with magnitudes greater than 4.5 in the 24 hr period following the mainshock. The epicenters of the two principal events were located in the Indian Wells Valley, northwest of Searles Valley near the towns of Ridgecrest, Trona, and Argus. We describe observed liquefaction manifestations including sand boils, fissures, and lateral spreading features, as well as proximate non‐ground failure zones that resulted from the sequence. Expanding upon results initially presented in a report of the Geotechnical Extreme Events Reconnaissance Association, we synthesize results of field mapping, aerial imagery, and inferences of ground deformations from Synthetic Aperture Radar‐based damage proxy maps (DPMs). We document incidents of liquefaction, settlement, and lateral spreading in the Naval Air Weapons Station China Lake US military base and compare locations of these observations to pre‐ and postevent mapping of liquefaction hazards. We describe liquefaction and ground‐failure features in Trona and Argus, which produced lateral deformations and impacts on several single‐story masonry and wood frame buildings. Detailed maps showing zones with and without ground failure are provided for these towns, along with mapped ground deformations along transects. Finally, we describe incidents of massive liquefaction with related ground failures and proximate areas of similar geologic origin without ground failure in the Searles Lakebed. Observations in this region are consistent with surface change predicted by the DPM. In the same region, geospatial liquefaction hazard maps are effective at identifying broad percentages of land with liquefaction‐related damage. We anticipate that data presented in this article will be useful for future liquefaction susceptibility, triggering, and consequence studies being undertaken as part of the Next Generation Liquefaction project.

California↗
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

The predictive skills of elastic Coulomb rate-and-state aftershock forecasts during the 2019 Ridgecrest, California, earthquake sequence

Operational earthquake forecasting protocols commonly use statistical models for their recognized ease of implementation and robustness in describing the short-term spatiotemporal patterns of triggered seismicity. However, recent advances on physics-based aftershock forecasting reveal comparable performance to the standard statistical counterparts with significantly improved predictive skills when fault and stress field heterogeneities are considered. Here, we perform a pseudo-prospective forecasting experiment during the first month of the 2019 Ridgecrest (California) earthquake sequence. We develop seven Coulomb rate-and-state models that couple static stress change estimates with continuum mechanics expressed by the rate-and-state friction laws. Our model parametrization supports a gradually increasing complexity; we start from a preliminary model implementation with simplified slip distributions and spatially homogeneous receiver faults to reach an enhanced one featuring optimized fault constitutive parameters, finite-fault slip models, secondary triggering effects, and spatially heterogenous planes informed by pre-existing ruptures. The data-rich environment of Southern California allows us to test whether incorporating data collected in near real-time during an unfolding earthquake sequence boosts our predictive power. We assess the absolute and relative performance of the forecasts by means of statistical tests used within the Collaboratory for the Study of Earthquake Predictability (CSEP) and compare their skills against a standard benchmark ETAS model for the short (24 hours after the two Ridgecrest mainshocks) and intermediate-term (one month). Stress-based forecasts expect heightened rates along the whole near-fault region and increased expected seismicity rates in Central Garlock Fault. Our comparative model evaluation supports that faulting heterogeneities coupled with secondary triggering effects are the most critical success components behind physics-based forecasts, but also underlines the importance of model updates incorporating near real-time available aftershock data reaching better performance than ETAS models. We explore the physical basis behind our results by investigating the localized shut down of pre-existing normal faults in the Ridgecrest near-source area.

California↗
USGS2020

Mild displacements of boulders during the 2019 Ridgecrest Earthquakes

Strong seismic waves from the July 2019 Ridgecrest, California, earthquakes displaced rocks in proximity to the M 7.1 mainshock fault trace at several locations. In this report, we document large boulders that were displaced at the Wagon Wheel Staging Area (WWSA), approximately 4.5 km southeast of the southern terminus of the large M 6.4 foreshock rupture (hereafter “the large foreshock”) and 9 km southwest of the nearest approach of the M 7.1 mainshock surface rupture. Some boulders appear to have slid along essentially flat surfaces, which suggest that dynamic stresses overcame the coefficient of friction. Other boulders appear to have rocked within their sockets. In both cases, we use simple mechanical models to estimate total peak dynamic accelerations between 0.5 and 1g⁠, commensurate with modified Mercalli intensity 9. It is unclear if the strongest shaking at this location occurred during the large foreshock or the M 7.1 mainshock. The inferred accelerations are higher than predicted mainshock ground motions at WWSA, although local high accelerations could have been generated by path, site, or source effects. Gaps between boulders and their sockets are easily visible in the immediate aftermath of earthquakes and provide a quick indication of strong shaking. More importantly, the gaps quickly fill with surficial organic debris, including seeds and leaves of the year, that quickly become entombed. Boulders may thus potentially be extracted to examine gap fillings associated with past earthquakes, providing a new datable paleoseismic method.

California↗
USGS2020

Kinematic rupture and 3D wave propagation simulations of the 2019 Mw 7.1 Ridgecrest, California, earthquake

We model the kinematic rupture process of the 2019 M w "> M w Mw 7.1 Ridgecrest, California, earthquake using numerical simulations to reproduce the elastodynamic wave field observed by inertial seismometers, high‐rate Global Navigation Satellite System stations, and borehole strainmeters. This was the largest earthquake in Southern California in 20 yr and was widely felt throughout the region. The M w "> M w Mw 7.1 mainshock was part of a large sequence of ∼ 30 , 000 "> ∼ 30 , 000 ∼30,000 aftershocks and was notably preceded by an M w "> M w Mw 6.4 foreshock by 34 hr on fault structures that were once poorly understood. A large number of seismic and geodetic instruments measured the rupture process for both events, with many stations located in the near field. Hence, this is a rare opportunity to better understand complex earthquake processes that arise in an immature fault zone using advanced computing. Of the kinematic rupture models that we tested, our preferred is the simplest one that reproduces signals recorded by the three different geophysical datasets; it is composed of four distinct ruptures that progressively migrate to the southeast with delayed initiation times, and typical rupture speeds. This type of model does a better job at matching the recorded ground motions and deformations than does one composed of a continuous rupture with very low‐rupture velocity, as proposed in other studies of this earthquake.

California↗
USGS2020

ShakeAlert Earthquake Early Warning System Performance During the 2019 Ridgecrest Earthquake Sequence

During July 2019, a sequence of earthquakes including a Mw6.4 foreshock and a Mw7.1 mainshock occurred near Ridgecrest, California. ShakeAlert, the U.S. Geological Survey (USGS) ShakeAlert public Earthquake Early Warning (EEW) system being developed for the U.S. West Coast, was operational during this time, though public alerting was only available within LA County. ShakeAlert created alert messages for many of the earthquakes, including the two largest events, and for many of the larger aftershocks. In this study, we dissect log files and replay data through the system to reconstruct the sequence of events and analyze the performance of the system during that time period. While the system performed reasonably well overall, the sequence also revealed various issues and short comings that will be addressed in impending and future system upgrades, with most parts of the system working as they should. ShakeAlert correctly detected and rapidly characterized both the Mw6.4 and Mw7.1 earthquakes within 6.9 s of their origin times and created alert messages that were available to ShakeAlert’s pilot users. No public alerts were sent out by the ShakeAlertLA cellphone app (the only publicly available alerting method at the time) because the predicted shaking for LA County was below the app’s alerting threshold of MMI 4.0. For the Mw6.4 event this was accurate. For the Mw7.1 event, public alerts for LA County were warranted, but ShakeAlert underpredicted the shaking levels because both the point-source and the finite-fault algorithms underestimated the magnitude of the earthquake by 0.8 units. A number of software and hardware issues that were responsible for the magnitude underestimation of the mainshock have been identified and will be addressed in future ShakeAlert releases. We also analyze the hypothetical alerting performance of ShakeAlert had public alerting been available throughout southern California with a lower alerting threshold of 〖MMI〗_alert=2.5MMI 2.5. We find that, despite the magnitude underestimation, ShakeAlert could have provided timely warnings to a large fraction of affected sites, including some of the near-epicentral sites with high ground motion intensities.

California↗