Geology topics

Research about Ridgecrest, California

Source-linked reports with geographic coverage including Ridgecrest, California.

31 records · Page 2Linked to original sources

USGS2020

Human behavioral response in the Ridgecrest earthquakes: Assessing immediate actions based on data from “Did You Feel It?”

Human behavioral response to earthquake ground motion has long been a subject of multidisciplinary interest and research. In most versions of seismic intensity scales, human perceptions and behavior are one component of the assignment of intensity. Public health research has shown that actions taken during earthquakes have a significant impact on the incidence of injury or the maintenance of safety. Based on this research, emergency managers and organizations promoting emergency preparedness have advocated strategies such as drop, cover, and hold on (DCHO) and promoted this safety measure through public education and annual drills. The “Did You Feel It?” (DYFI) mapping system (see Data and Resources) based on an online questionnaire developed and maintained by the U.S. Geological Survey has provided opportunities for those who have experienced an earthquake to report this experience worldwide since 2004. The DYFI questionnaire, although designed to assign intensity, also contains questions regarding the behavior in which one has engaged during the earthquake. The questionnaire includes other important information that may elucidate behavioral response to earthquakes, including assigned intensity, emotional reaction, and whether damage occurred at the location where the earthquake was experienced. The very large number of people who completed DYFI questionnaires following the July 2019 Ridgecrest, California, earthquakes provides a robust dataset for analysis and suggests that as intensity and levels of fear increase, behavior becomes more active in terms of physical movement to locations of presumed safety. Among active responses including DCHO, going to a doorway, and running outside, DCHO was the least likely to be implemented. The study provides possible explanations for low participation in DCHO despite active campaigns to promote this strategy.

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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.

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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 ">

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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.

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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.

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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.

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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.

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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.

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USGS2020

Response study of the tallest California building inferred from the Mw7.1 Ridgecrest, California earthquake of 5 July 2019 and ambient motions

The newly constructed tallest building in California, the 73-story Wilshire Grand in Los Angeles, California, is designed in conformance with performance-based design procedures. The building is designed with concrete core–shear walls, three outriggers with buckling restrained braces (BRBs) located along the height, and two three-story truss-belt structural systems. The building is equipped with a 36-channel accelerometric seismic monitoring array that recorded the recent Mw7.1 Ridgecrest earthquake of 5 July 2019, as well as the Mw6.4 Ridgecrest earthquake of 4 July 2019. In this article, only the Mw7.1 event of 5 July 2019 is studied because of a larger response of the subject building during that earthquake. The earthquake records of 5 July 2019 are specifically studied to determine its dynamic characteristics and building-specific behavior. The structure exhibits torsional behavior most likely due to abrupt asymmetrical changes in the thickness and size in-plan of the core–shear walls. The translational and torsional modes during the earthquake are not closely coupled, which does not lead to a beating effect even though there is an appearance of it in the records. Available ambient records are used only to identify modal frequencies of the building and compare them with those from the Mw7.1 event of 5 July 2019. Due to the relatively low amplitude of shaking during the earthquake, the drift ratios are too small to cause any damage. It is expected that during stronger shaking levels likely to be caused by future events, these characteristics may change and the effect of BRBs can be better assessed.

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USGS2020

The 2019 Ridgecrest, California, earthquake sequence ground motions: Processed records and derived intensity metrics

Following the 2019 Ridgecrest, California, earthquake sequence, we compiled ground‐motion records from multiple data centers and processed these records using newly developed ground‐motion processing software that performs quality assurance checks, performs standard time series processing steps, and computes a wide range of ground‐motion metrics. In addition, we compute station and waveform metrics such as the time‐averaged shear‐wave velocity to 30 m depth ( ⁠ V S 30 "> V S 30 ⁠ ), finite‐rupture distances, and spectral accelerations. This data set includes 22,708 records from 133 events from 4 July 2019 (UTC) to 18 October 2019 with a magnitude range from 3.6 to 7.1. We expect that the rapid collection and dissemination of this information will facilitate detailed studies of these ground motions. In this article, we describe the data selection, processing steps, and how to access the data.

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USGS2020

Caltech/USGS Southern California Seismic Network (SCSN) and Southern California Earthquake Data Center (SCEDC): Data availability for the 2019 Ridgecrest sequence

The 2019 M6.4 and M7.1 Ridgecrest earthquake sequence occurred in the eastern California shear zone (ECSZ). The mainshock ruptured the Little Lake fault zone and aftershocks extended from the Garlock fault in the south, to the southern end of the 1872 M7.5 Owens Valley earthquake rupture in the north. We present data from the Southern California Seismic Network (SCSN) and partner seismic networks recorded by the SCSN in the region. These time series data and related products such as the SCSN earthquake picks and catalogs, available from the Southern California Earthquake Data Center (SCEDC), provide the most comprehensive seismic datasets for the 2019 Ridgecrest earthquake sequence.

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USGS2020

The U.S. Geological Survey’s Rapid Seismic Array Deployment for the 2019 Ridgecrest Earthquake Sequence

Rapid seismic deployments following large earthquakes capture ephemeral near‐field recordings of aftershocks and ambient noise that can provide valuable data for seismological studies. The U.S. Geological Survey installed 19 temporary seismic stations following the 4 July 2019 M w 6.4 and 6 July 2019 (UTC) M w 7.1 earthquakes near the city of Ridgecrest, California. The stations record the aftershock sequence beginning two days after the mainshock and are expected to remain in the field through approximately January 2020. The deployment augments the permanent seismic network in the area to improve azimuthal coverage and provide additional near‐field observations. This article summarizes the motivation and goals of the deployment; details of station installation, instrumentation, and configurations; and initial data quality and observations from the network. We expect these data to be useful for a range of studies including detailing near‐field variability in strong ground motions, determining stress drops and rupture directivity of small events, imaging the fault zone, documenting the evolution of crustal properties within and outside of the fault zone, and others.

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USGS2020

An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence

Previous research has shown that online social networks can provide valuable insights regarding collective human responses to extreme natural events, such as earthquakes. Most previous studies focused on one large earthquake, while the 2019 Ridgecrest earthquakes involved two significant earthquakes occurring within a short period of time (a M6.4 foreshock on July 4 and a M7.1 mainshock on July 5 in southern California). These earthquakes were the first time in more than a decade that the southern California region, with an estimated population of 15 million, felt light to moderate shaking over an extended period of time. This valuable opportunity allows us to study how people respond dynamically to such sequences of extreme events. We collected 510,579 tweets about the 2019 Ridgecrest earthquakes to answer the following research questions: (1) Which Twitter accounts were the major players? Did they behave differently and get different responses? (2) How did the publics' response change during these sequential earthquakes? and (3) Which earthquake-related rumors were disseminated on Twitter during the earthquake sequence, by whom, and at what time?

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