New opportunities to study earthquake precursors
No abstract available.
Seismological Research Letters↗
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Now trending … Earthquake information
The U.S. Geological Survey Earthquake Hazards Program has overall successfully fulfilled its mission of providing timely earthquake information via web applications and other methods. Imagine a single month of earthquake data delivery, serving 3.6 billion total data requests, including 29 million pageviews by 7.1 million users, 606 million automated data feeds, and 45 million catalog downloads. Yet, some challenges and lapses in delivery have happened at critical times, including during the Ridgecrest earthquakes in 2019. We delve into the evolving demand for real‐time information as well as the technologies put in place to support the ever‐growing number of users in an increasingly mobile world.
Seismological Research Letters↗
Recording the aurora borealis (northern lights) at seismometers across Alaska
We examine three continuously recording data sets related to the aurora: all‐sky camera images, three‐component magnetometer data, and vertical‐component, broadband seismic data as part of the EarthScope project (2014 to present). Across Alaska there are six all‐sky cameras, 13 magnetometers, and > 200 "> > 200 >200 seismometers. The all‐sky images and magnetometers have the same objective, which is to monitor space weather and improve our understanding of auroral activity, including the influence on magnetic fields in the ground. These variations in the magnetic field are also visible on seismometers, to the extent that during an auroral event, the long‐period (40–800 s) waves recorded by a seismometer are magnetic field variations, not true ground motion. Although this is a problem—one that can be rectified with magnetic shielding at each seismometer site—it is also an opportunity because the present seismic array in Alaska is much broader than the coverage by magnetometers and all‐sky cameras. Here we focus on three aurora events and document a direct link between aurora images in the night sky and seismometer recordings on ground. Simultaneous recordings by magnetometers provide a critical link between the sky images and the seismometer recordings. We document qualitative correlations among sky, magnetic, and seismic data. The findings suggest that the signature of auroral activity is widespread across seismometers in Alaska, implying that the seismic array could be used to enhance the spatial resolution of the existing network of all‐sky cameras and magnetometers. Future efforts to improve the multisensor seismic stations in Alaska, for the purpose of monitoring seismic and auroral activity, should consider installation of all‐sky cameras, installation of magnetometers, and magnetic shielding of seismic sensors.
Alaska↗
Shaking is almost always a surprise: The earthquakes that produce significant ground motion
Although small earthquakes are expected to produce weak shaking, ground motion is highly variable and there are outlier earthquakes that generate more shaking than expected—sometimes significantly more. We explore datasets of M 0.5–8.3 earthquakes to determine the relative impact of frequent, smaller-magnitude earthquakes that rarely produce strong ground motion, to rare, large earthquakes that always cause strong shaking. We find that the natural variability of ground motion, combined with the Gutenberg–Richter magnitude–frequency relationship, ensures that most occurrences of any ground motion come from earthquakes of smaller magnitude than expected, often > 2 magnitude units smaller. This holds even for very strong shaking ( > 20% g ), suggesting that M < 7 earthquakes could be a significant source of damage.
Seismological Research Letters↗
Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center
Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations. Automatic seismic arrival detections made from standard picking methods (e.g., short‐term average/long‐term average [STA/LTA]) are fed to trained neural network models to improve automatic seismic‐arrival (pick) timing and estimate seismic‐arrival phase type and source‐station distances. These additional data are used to improve the capabilities of the NEIC associator. We compile a dataset of 1.3 million seismic‐phase arrivals that represent a globally distributed set of source‐station paths covering a range of phase types, magnitudes, and source distances. We train three separate convolutional neural network models to predict arrival time onset, phase type, and distance. We validate the performance of the trained networks on a subset of our existing dataset and further extend validation by exploring the model performance when applied to NEIC automatic pick data feeds. We show that the information provided by these models can be useful in downstream event processing, specifically in seismic‐phase association, resulting in reduced false associations and improved location estimates.
Seismological Research Letters↗
Imaging the tectonic grain of the Northern Cordillera orogen using Transportable Array receiver functions
Azimuthal variations in receiver function conversions can image lithospheric structural contrasts and anisotropic fabrics that together compose tectonic grain. We apply this method to data from EarthScope Transportable Array in Alaska and additional stations across the northern Cordillera. The best‐resolved quantities are the strike and depth of dipping fabric contrasts or interfaces. We find a strong geographic gradient in such anomalies, with large amplitudes extending inboard from the present‐day subduction margin, the Aleutian arc, and an influence of flat‐slab subduction of the Yakutat microplate north of the Denali fault. An east–west band across interior Alaska shows low‐amplitude crustal anomalies. Anomaly amplitudes correlate with structural intensity (density of aligned geological elements), but are the highest in areas of strong Cenozoic deformation, raising the question of an influence of current stress state. Imaged subsurface strikes show alignment with surface structures. We see concentric strikes around arc volcanoes implying dipping magmatic structures and fabric into the middle crust. Regions with present‐day weaker deformation show lower anomaly amplitudes but structurally aligned strikes, suggesting pre‐Cenozoic fabrics may have been overprinted or otherwise modified. We observe general coherence of the signal across the brittle‐plastic transition. Imaged crustal fabrics are aligned with major faults and shear zones, whereas intrafault blocks show imaged strikes both parallel to and at high angles to major block‐bounding faults. High‐angle strikes are subparallel to neotectonic deformation, seismicity, fault lineaments, and prominent metallogenic belts, possibly due to overprinting and/or co‐evolution with fault‐parallel fabrics. We suggest that the underlying tectonic grain in the northern Cordillera is broadly distributed rather than strongly localized. Receiver functions thus reveal key information about the nature and continuity of tectonic fabrics at depth and can provide unique insights into the deformation history and distribution of regional strain in complex orogenic belts.
Alaska↗
The Alaska Amphibious Community Seismic Experiment
The Alaska Amphibious Community Seismic Experiment (AACSE) is a shoreline‐crossing passive‐ and active‐source seismic experiment that took place from May 2018 through August 2019 along an ∼ 700    km "> ∼ 700 km ∼700 km long section of the Aleutian subduction zone spanning Kodiak Island and the Alaska Peninsula. The experiment featured 105 broadband seismometers; 30 were deployed onshore, and 75 were deployed offshore in Ocean Bottom Seismometer (OBS) packages. Additional strong‐motion instruments were also deployed at six onshore seismic sites. Offshore OBS stretched from the outer rise across the trench to the shelf. OBSs in shallow water ( < 262    m "> < 262 m <262 m depth) were deployed with a trawl‐resistant shield, and deeper OBSs were unshielded. Additionally, a number of OBS‐mounted strong‐motion instruments, differential and absolute pressure gauges, hydrophones, and temperature and salinity sensors were deployed. OBSs were deployed on two cruises of the R/V Sikuliaq in May and July 2018 and retrieved on two cruises aboard the R/V Sikuliaq and R/V Langseth in August–September 2019. A complementary 398‐instrument nodal seismometer array was deployed on Kodiak Island for four weeks in May–June 2019, and an active‐source seismic survey on the R/V Langseth was arranged in June 2019 to shoot into the AACSE broadband network and the nodes. Additional underway data from cruises include seafloor bathymetry and sub‐bottom profiles, with extra data collected near the rupture zone of the 2018 M w "> M w Mw 7.9 offshore‐Kodiak earthquake. The AACSE network was deployed simultaneously with the EarthScope Transportable Array (TA) in Alaska, effectively densifying and extending the TA offshore in the region of the Alaska Peninsula. AACSE is a community experiment, and all data were made available publicly as soon as feasible in appropriate repositories.
Alaska↗
Evaluation of seismic hazard models with fragile geologic features
We provide an overview of a 2019 workshop on the use of fragile geologic features (FGFs) to evaluate seismic hazard models. FGFs have been scarcely utilized in the evaluation of seismic hazard models, despite nearly 30 yr having passed since the first recognition of their potential value. Recently, several studies have begun to focus on the implementation of FGFs in seismic hazard modeling. The workshop was held to capture a “snapshot” of the state‐of‐the‐art in FGF work and to define key research areas that would increase confidence in FGF‐based evaluation of seismic hazard models. It was held at the annual meeting of the Southern California Earthquake Center on 8 September 2019, and the conveners were Mark Stirling (University of Otago, New Zealand) and Michael Oskin (University of California, Davis). The workshop attracted 44 participants from a wide range of disciplines. The main topics of discussion were FGF fragility age estimation (age at which an FGF achieved its current fragile geometry), fragility estimation, FGF‐based evaluation of seismic hazard models, and ethical considerations relating to documentation and preservation of FGFs. There are now many scientists working on, or motivated to work on, FGFs, and more types of FGFs are being worked on than just the precariously balanced rock (PBR) variety. One of the ideas presented at the workshop is that fragility ages for FGFs should be treated stochastically rather than assuming that all share a common age. In a similar vein, new studies propose more comprehensive methods of fragility assessment beyond peak ground acceleration and peak ground velocity‐based approaches. Two recent studies that apply PBRs to evaluate probabilistic seismic hazard models use significantly different methods of evaluation. Key research needs identified from the workshop will guide future, focused efforts that will ultimately facilitate the uptake of FGFs in seismic hazard analysis.
Seismological Research Letters↗
Nodal seismograph recordings of the 2019 Ridgecrest Earthquake Sequence
The 2019 Ridgecrest, California earthquake sequence included M w 6.4 and Mw 7.1 earthquakes that occurred on successive days beginning on 4 July 2019. These two largest earthquakes of the sequence occurred on orthogonal faults that ruptured the Earth’s surface. To better evaluate the 3D subsurface fault structure, ( P - and S -wave) velocity, 3D and temporal variations in seismicity, and other important aspects of the earthquake sequence, we recorded aftershocks and ambient noise using up to 461 three-component nodal seismographs for about two months, beginning about one day after the M w 7.1 mainshock. The ~ 30,000 M w ≥1 earthquakes that were recorded on the dense arrays provide an unusually large volume of data with which to evaluate the earthquake sequence. This report describes the recording arrays and is intended to provide metadata for researchers interested in evaluating various aspects of the 2019 Ridgecrest earthquake sequence using the nodal data set.
California↗
Latency of waveform data delivery from the Southern California Seismic Network during the 2019 Ridgecrest earthquake sequence and its effect on ShakeAlert
The occurrence of the 4–6 July 2019 M w 6.4 and M w 7.1 Ridgecrest earthquake sequence provided the first full‐scale test of the network and telemetry readiness of the Southern California Seismic Network (SCSN), to support the ShakeAlert earthquake early warning (EEW) system in California. ShakeAlert is a U.S. Geological Survey (USGS)‐led collaboration to detect earthquakes and, when possible, to alert the public before the arrival of the strongest shaking. The SCSN performed well in its regional monitoring role for both the 4 July M w 6.4 and the 6 July M w 7.1 earthquakes. In the EEW role, it provided timely delivery of 5 s of P ‐wave data to ShakeAlert, which issued its first alert 6.9 s after origin time. Data delivery at peak data volumes for many stations exhibited some latency, and, as a consequence, some data arrived too late for analysis by one of the EEW algorithms. We find that the average link bandwidth for each station was sufficient, because all waveform data were delivered automatically to the archive, but link capacity for many stations was insufficient for peak demand. We describe the performance of the data telemetry for the sequence, including cellular, radio, hybrid, and backhaul systems. Cellular‐based telemetry systems maintained low latency throughout strong shaking and after, but some stations, even at great distances, experienced subsequent brief increases in latency. Performance of radio links depended mostly on the signal strength of the link, with short‐distance direct shots to high‐bandwidth backhaul systems showing no latency impact, whereas stations on some long distance or marginal quality links suffered latencies of tens or hundreds of seconds. Improvements are being implemented to move telemetry links onto USGS and partner high‐bandwidth microwave systems, and to reduce dependency on less robust long‐distance radio shots.
California↗
Forecasting induced earthquake hazard using a hydromechanical earthquake nucleation model
In response to the dramatic increase in earthquake rates in the central United States, the U.S Geological Survey began releasing 1 yr earthquake hazard models for induced earthquakes in 2016. Although these models have been shown to accurately forecast earthquake hazard, they rely purely on earthquake statistics because there was no precedent for forecasting induced earthquakes based upon wastewater injection data. Since the publication of these hazard models, multiple physics‐based methods have been proposed to forecast earthquake rates using injection data. Here, we use one of these methods to generate earthquake hazard forecasts. Our earthquake hazard forecasts are more accurate than statistics‐based hazard forecasts. These results imply that fluid injection data, where and when available, and the physical implications of fluid injection should be included in future induced earthquake hazard forecasts.
Kansas, Oklahoma↗
Ensemble ShakeMaps for magnitude 9 earthquakes on the Cascadia Subduction Zone
We develop ensemble ShakeMaps for various magnitude 9 ( M "> M M 9) earthquakes on the Cascadia megathrust. Ground‐shaking estimates are based on 30 M "> M M 9 Cascadia earthquake scenarios, which were selected using a logic‐tree approach that varied the hypocenter location, down‐dip rupture limit, slip distribution, and location of strong‐motion‐generating subevents. In a previous work, Frankel et al. (2018) used a hybrid approach (i.e., 3D deterministic simulations for frequencies < 1    Hz "> < 1 Hz <1 Hz and stochastic synthetics for frequencies > 1    Hz "> > 1 Hz >1 Hz ) and uniform site amplification factors to create broadband seismograms from this set of 30 earthquake scenarios. Here, we expand on this work by computing site‐specific amplification factors for the Pacific Northwest and applying these factors to the ground‐motion estimates derived from Frankel et al. (2018) . In addition, we use empirical ground‐motion models (GMMs) to expand the ground‐shaking estimates beyond the original model extent of Frankel et al. (2018) to cover all of Washington State, Oregon, northern California, and southern British Columbia to facilitate the use of these ensemble ShakeMaps in region‐wide risk assessments and scenario planning exercises. Using this updated set of 30 M "> M M 9 Cascadia earthquake scenarios, we present ensemble ShakeMaps for the median, 2nd, 16th, 84th, and 98th percentile ground‐motion intensity measures. Whereas traditional scenario ShakeMaps are based on a single hypothetical earthquake rupture, our ensemble ShakeMaps take advantage of a logic‐tree approach to estimating ground motions from multiple earthquake rupture scenarios. In addition, 3D earthquake simulations capture important features such as strong ground‐motion amplification in the Pacific Northwest’s sedimentary basins, which are not well represented in the empirical GMMs that compose traditional scenario ShakeMaps. Overall, our results highlight the importance of strong‐motion‐generating subevents for coastal sites, as well as the amplification of long‐period ground shaking in deep sedimentary basins, compared with previous scenario ShakeMaps for Cascadia.
California, Oregon, Washington↗
Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars
Structure‐from‐motion (SfM) modeling has dramatically increased the speed of generating geometrically accurate orthophoto mosaics of paleoseismic trenches, but some aspects of this technique remain time and labor intensive. Model accuracy relies on control points to establish scale, reduce distortion, and orient 3D models. Traditional SfM methods use total station or Global Navigation Satellite System (GNSS) surveys to constrain models, but collecting control points along a vertical trench wall is often inhibited by poor line of sight to the survey sensor or limited sky view and requires many hours in the field and office. We used physical scale bars printed with coded targets to constrain SfM models of a dusty, 46‐m‐long trench excavation across the Teton fault (Wyoming, U.S.A.). We present a workflow for generating quick and accurate 3D SfM models and orthophoto mosaics and compare the effectiveness of using scale bar, GNSS, and total‐station control in the models. Our results show that the scale bar model deviates from total station survey points by an average of 3.1 cm (maximum of 5.3 cm). In addition, the scale‐bar model only deviates an average of 1.7 cm (maximum 3.5 cm) when compared to the best model alternative, the SfM model controlled by the total station survey. Scale bars eliminate several hours needed to collect and incorporate control points from total station or GNSS surveys and significantly simplify the workflow, at the cost of slightly increased 3D model and orthophoto mosaic error. Our results further suggest that trench models can be constrained with at least four physical scale bars, but using five to six physical scale bars provides redundant control for field deployment and model optimization. The scale bar method for paleoseismic trenches proves to be portable and fast, minimizes the need for specialized survey equipment, and maintains model accuracy needed for mapping trench walls.
Seismological Research Letters↗
Monitoring network changes during the 2018 Kīlauea Volcano eruption
In the summer of 2018, Kīlauea Volcano underwent one of its most significant eruptions in the past few hundred years. The volcano’s summit and East Rift Zone magma system partially drained, resulting in a series of occasionally explosive partial caldera collapses, and widespread lava flows in the lower East Rift Zone. The Hawaiian Volcano Observatory (HVO) operates a robust permanent monitoring network of about 250 stations, recording a variety of real‐time data streams: seismic (short‐period, broadband, strong‐motion), infrasound, Global Navigation Satellite Systems (GNSS), tilt, camera, laser rangefinder, and gas geochemistry. During the eruption, HVO staff quickly established 35 new temporary monitoring stations, to better constrain evolving volcanic hazards. The partial collapses of the caldera threatened to disrupt important telemetry links in the HVO monitoring network, and a major effort was undertaken in the midst of the eruption crisis to reroute radio telemetry and maintain continuity of data flow. In the process, a new data center was established in Hilo, to mitigate a long‐standing potential single point of failure at the HVO facility. Over the course of the eruption from May through August, lava, ashfall, wildfire, and cliff collapse destroyed or disabled 36 stations. Thousands of earthquakes damaged the main HVO facility at Uēkahuna Bluff, causing staff to evacuate the building and relocate observatory operations in the midst of the eruption response, adding more complexity to the response effort. Throughout these events, the HVO team maintained the monitoring network, provided timely information to the public and emergency managers, and collected valuable scientific data to better understand Kīlauea Volcano.
Hawaii↗
Seismic monitoring during crises at the NEIC in support of the ANSS
Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome crises is built on the development and implementation of a continuity of operations plan, well‐designed infrastructure, adaptive software systems, experienced staff, and extensive collaboration. The NEIC does not operate in a vacuum but benefits from contributions of United States and international seismic networks. Similarly, the overall resilience of earthquake monitoring in the United States and around the globe benefits from the NEIC’s role as the national center for the Advanced National Seismic System (ANSS). Here, we highlight significant adaptations the NEIC has made in the face of crises. We discuss the COVID‐19 pandemic, which represents the most significant operational crisis to impact the NEIC. The NEIC has maintained continuous operations during the ongoing COVID‐19 pandemic by shifting from a fully onsite operations center to a distributed hybrid of onsite and telework staffing. We then discuss cases in which the NEIC has supported regional monitoring in the face of significant crises. In 2018, the NEIC assisted the Hawaiian Volcano Observatory with the Kīlauea volcano eruption by responding to large events, implementing contingency monitoring procedures, and calculating moment magnitudes for the low‐frequency caldera collapses. Impacts of a crisis extend beyond the immediate response and often require a significant postevent assessment and a rebuilding phase. After the 2017 Hurricane Maria, the NEIC, the USGS National Strong‐Motion Program, and the USGS Albuquerque Seismological Laboratory worked with the Puerto Rico Seismic Network and the Puerto Rico Strong‐Motion program to assess, plan, and implement upgrades at sites that experienced storm damage.
Seismological Research Letters↗
Coseismic fault slip and afterslip associated with the M5.7 March 18, 2020 Magna, Utah, earthquake
The 2020 Magna, Utah, earthquake produced observable crustal deformation over a ∼ 100 km 2 area around the southeast margin of Great Salt Lake, but it did not produce any surface rupture. To obtain a detailed picture of the fault slip, we combine strong motion seismic waveforms with GPS static offsets and Interferometric Synthetic Aperture Radar (InSAR) observations to obtain kinematic and static slip models of the event. We sample the regional seismic wavefield with 3-component records from 68 stations of the University of Utah Seismograph Stations network. We find that coseismic slip and afterslip, with predominantly normal slip, distributed on a shallowly west-dipping plane, possibly augmented by afterslip on a steeply northeast-dipping plane, best fits the joint dataset. The west-dipping plane locates near previously inferred sources of interseismic creep at depth. Hence the earthquake may have occurred on the downdip ex-tension of the Wasatch fault and activated further slip (afterslip) at shallow depth east of the hypocenter. This inferred afterslip may have driven the vigorous aftershock activity that was concentrated east of the hypocenter.
Utah↗
Rupture process of the M6.5 Stanley, Idaho, earthquake inferred from seismic waveform and geodetic data
The 2020 M 6.5 Stanley, Idaho, earthquake produced rupture in the north of the active Sawtooth fault in the northern basin and range at depth, without any observable surface rupture. Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR) data yield several millimeters of static offsets out to ∼100 km from the rupture and up to ∼0.1 m of near‐field crustal deformation. We combine the GPS and InSAR data with long‐period regional seismic waveforms to derive models of kinematic slip and afterslip. We find that the coseismic rupture is complex, likely involving up to 2 m combined left‐lateral strike slip and normal slip on a previously unidentified ∼south‐southeast‐striking fault. This slip is predominantly left‐lateral strike slip, different from the dominant east‐northeast–west‐northwest normal faulting of the region. At least one ∼northeast‐trending fault, likely associated with the Trans‐Challis fault system, is inferred to have accommodated a few decimeters of right‐lateral afterslip, consistent with vigorous aftershock activity at depth along northeast‐trending lineations.
Idaho↗
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↗