From temblor : “Strong earthquake increases seismic hazard in Qinghai in China”

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From temblor

January 13, 2022

By Zhigang Peng, Ph.D., School of Earth and Atmospheric Sciences, The Georgia Institute of Technology (US), Jing Liu-Zeng, Ph.D., Tianjin University[天津大學](CN), Yangfan Deng, Ph.D., The Chinese Academy of Sciences [中国科学院](CN) Center for Excellence in Deep Earth Science, Guangzhou, China, Shinji Toda, Ph.D., International Research Institute of Disaster Science, Tohoku University [東北大学](JP).

A powerful magnitude-6.6 earthquake occurred in the Qinghai province in Western China on January 7, 2022 (Figure 1). The quake struck at 1:45 a.m. local time in a remote region of Menyuan county. It was the largest earthquake in China since the magnitude-7.3 Maduo earthquake in the same province in May 2021. The Menyuan earthquake was widely felt in surrounding regions and caused temporary halts of several high-speed rail lines. But the region is sparsely populated, and only minor injuries and property damage were reported.

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Figure 1. Active faults in the northeastern Tibetan plateau and the focal mechanism of the most recent Menyuan earthquake in Northwestern China. The inset marks the map in a larger map of Tibetan Plateau. HYF: Haiyuan Fault; ATF: Altyn Tagh Fault; KF: Kunlun fault; XHF: Xianshuihe Fault. Credit: Wenqian Yao.

Tectonic Environment

The earthquake occurred in the northeastern margin of the Tibetan Plateau, which was created by the collision between the Eurasian and Indian tectonic plates. Near the recent epicenter, tectonic movement is mostly accommodated by a combination of thrust faults and left-lateral strike-slip fault systems such as the Altyn Tagh, the Kunlun and Haiyuan faults (Figure 1). The most recent Menyuan earthquake occurred on the Lenglongling (meaning “Cold Dragon Ridge” in Chinese) Fault, which is the western branch of the Haiyuan fault. This region is seismically active. Moderate-sized earthquakes occurred in 1986 and 2016 within 40 kilometers to the east of the recent epicenter. Both preceding events involved thrust motion, and so were different from this strike-slip event. All three quakes occurred in a “restraining bend” of the Haiyuan fault, meaning that there is compression straddling the fault, leading to a combination of thrusting and strike-slip motion.

Compared with the 2016 event, the 2022 earthquake started in the same bend or jog, but the rupture appeared to propagate further to the west along the main strike-slip fault, producing roughly 22-kilometer surface ruptures on the ground. Further to the east, two roughly magnitude-8.0 earthquakes occurred in the past century (the 1920 Haiyuan and 1927 Gulang earthquakes), causing significant damage and casualties (Figure 2). The great 1920 Haiyuan earthquake also triggered numerous landslides in the terrain mantled by loess — windblown sand or dust, often derived from glacier deposits. Between these great earthquakes is a 260-kilometer-long segment of the Haiyuan Fault that has not ruptured in the past 1000 years (Liu-Zeng et al., 2007). The section is known as the “Tianzhu” seismic gap (Gaudemer et al. 1995) and could host large damaging earthquakes in the future.

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Figure 2. Tectonic map and earthquake locations/focal mechanisms in the Northeastern Tibetan Plateau. The blue lines mark ruptures associated with previous large earthquakes and the red line mark the Tianzhu seismic gap. Modified after Deng et al. (2020).

Mainshock Slip Patterns and Intensities

The mainshock focal mechanism is primarily left-lateral, which is consistent with the tectonic movement of the nearby Lenglongling Fault. Rapid finite fault modeling based on long-period teleseismic waves has shown that the mainshock ruptured in both directions along the fault from its nucleation point, with more slip to the east (Figure 3). In contrast, back-projections of short-period teleseismic P waves suggest that the mainshock ruptured primarily to the northwest (Figure 4). This is perhaps not surprising because these approaches use different techniques and frequency bands, and hence they are mostly sensitive to different types of earthquake rupture. For example, long-period finite fault modeling results likely correspond to smooth ruptures that produce significant fault slip. In comparison, short-period back-projection results likely image seismic ruptures on a relatively rough patch that produce significant high-frequency shaking. This is qualitatively consistent with the near-field strong motion and intensity recordings (Figure 5), showing high peak accelerations primarily around the mainshock epicenter and to the northwest direction.

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Figure 3. A preliminary finite fault modeling result for the 2022 magnitude-6.6 Menyuan mainshock based on teleseismic P waves. The inset marks the fault strike with respect to north. Modified from results by Weiming Wang.

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Figure 4. Mainshock rupture propagation results based on back-projection stack of teleseismic P waves recorded at broadband stations in Europe. Timing (color of circles) and amplitude (size of circles) for the stack with the maximum correlation at each time step in the map view. Red and black stars represent the epicenter of the 2022 Mw 6.6 Qinghai earthquake determined by the China Earthquake Networks Center (CENC), and United States Geological Survey (USGS), respectively. Gray circles indicate the locations of aftershocks that occurred within one day following the main shock (from Lihua Fang). Red lines represent traces of faults and province boundaries, respectively. Credit: Dun Wang.

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Figure 5. Near-field peak acceleration map for the M6.6 Menyuan mainshock. Modified from a figure provided by Qiang Ma.

Aftershocks and Surface Ruptures

As of January 13, 2022, at 8 a.m. Beijing time, more than 5000 aftershocks have been identified (Figure 6). The largest aftershock has a moment magnitude of 5.3. Relocated aftershocks extended about 40 kilometers to both sides of the mainshock epicenter. To the west, the aftershocks illuminate a fault striking nearly east-west, which is consistent with a rupture on the similarly oriented Tuolaishan Fault (TLSF). To the east, aftershocks mostly follow the local strike of the Lenglongling fault (LLLF). There appears to be a few kilometers gap between the aftershocks of the 2022 magnitude-6.6 mainshock and those of the 2016 magnitude-5.9 mainshock. The 2016 event was a thrust event that likely ruptured the Northern Lenglongling Fault (NLLLF) (Liu et al., 2019), rather than the left-lateral Lenglongling Fault that ruptured in the most recent event.

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Figure 6. A comparison of relocated aftershocks following the 2022 M6.6 and 2016 M5.9 mainshocks. The aftershock locations following the 2022 mainshock were provided by Lihua Fang. LLLF: Lenglongling fault; NLLLF: Northern Lenglongling fault; TLSF: Tuolaishan fault. The 2016 aftershock locations were from Liu et al. (2019). Credit: Yangfan Deng.

Coulomb Stress Transfers and Seismic Hazard

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Figure 9. Coulomb stress changes due to the 2016 Mw5.9 earthquake resolved onto (a) the left-lateral faults parallel to the 2022 rupture plane and (b) onto the 2022 fault plane of the finite fault model of Wang et al. (Figure 3). We implemented a simple uniform slip model of the NW-striking blind thrust for the 2016 earthquake based on the USGS CMT and Wells and Coppersmith (1994) empirical relation. Credit: Shinji Toda.

Due to their proximity and timing, we explore whether the 2016 magnitude-5.9 event promoted the 2022 magnitude-6.6 earthquake by static stress transfer. As shown in Figure 9, the 2016 magnitude-5.9 earthquake imparted up to 0.4 bar (0.04 MPa) of stress on the fault plane that ruptured during the 2022 earthquake. The calculation was done using the Coulomb 3.3 Software (Toda et al., 2011), with an effective coefficient of friction of 0.4. Similarly, we also compute the Coulomb stress changes on both left-lateral faults and northwest-trending thrust faults due to the combined effects of the 2016 and 2022 events (Figure 10). As expected, both events produced positive stress changes on nearby faults, suggesting an increased likelihood of future damaging earthquakes in these regions. In particular, the 2022 earthquake may have brought the unbroken sections to the west (i.e., the Tuolaishan Fault) and east (i.e., the Lenglongling Fault) of the 2022 surface ruptures several bars closer to failure. Indeed, so far, several roughly magnitude-5.0 aftershocks have occurred, suggesting seismic hazard in these sections is relatively high.

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Figure 10. The maximum Coulomb stress imparted by both 2016 and 2022 events for (a) WNW-striking left-lateral faults, and (b) NW-trending thrust faults at a depth range of 5-15 km. The finite fault model by Wang et al. (Figure 3) is used for the 2022 earthquake stress transfer. Credit: Shinji Toda.

The recent earthquake struck in an area previously highlighted by the China Earthquake Administration as having a high probability of a magnitude-6.0 or greater earthquake (Xu et al., 2017). This earthquake provides a glimmer of hope for the scientists engaging in long- and short-term earthquake forecasting in China.

Acknowledgement

We thank Drs. Lihua Fang at Institute of Geophysics, China Earthquake Administration, Dun Wang at Chinese University of Geosciences, Wuhan, Weiming Wang at Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Qiang Ma at Institute Engineering Mechanics, China Earthquake Administration, and Jie Gao at China Earthquake Disaster Prevention Center for providing their preliminary results and field photos that are included in this news report. We also thank Dr. Weqian Yao at Tianjing University for making Figure 1.

References

Deng, Y., Peng, Z., & Liu-Zeng, J. (2020), Systematic search for repeating earthquakes along the Haiyuan fault system in Northeastern Tibet, Journal of Geophysical Research: Solid Earth, 125(7), e2020JB019583, https://doi.org/10.1029/2020JB019583.

Gaudemer, Y., Tapponnier, P., Meyer, B., Peltzer, G., Shunmin, G., Zhitai, C., et al. (1995). Partitioning of crustal slip between linked, active faults in the eastern Qilian Shan, and evidence for a major seismic gap, the ‘Tianzhu gap’, on the western Haiyuan Fault, Gansu (China). Geophysical Journal International, 120(3), 599–645. https://doi.org/10.1111/j.1365-246X.1995.tb01842.x

Liu, M., Li, H., Peng, Z., Ouyang, L., Ma, Y., Ma, J., Liang, Z., & Huang, Y. (2019), Spatial-temporal distribution of early aftershocks following the 2016 Ms 6.4 Menyuan, Qinghai, China Earthquake, Tectonophysics, 766, 469-479, https://doi.org/10.1016/j.tecto.2019.06.022.

Liu-Zeng, J., Y. Klinger, X. Xu, C. Lasserre, G. Chen, W. Chen, P. Tapponnier, and B. Zhang, 2007. Millennial Recurrence of Large Earthquakes on the Haiyuan Fault near Songshan, Gansu Province, China, Bulletin of Seismological Society of America, 97 (1B): 14-34

Toda, S. R. S. Stein, V. Sevilgen, and J. Lin (2011) Coulomb 3.3 graphic-rich deformation and stress-change software for earthquake, tectonic, and volcano research and teaching —user guide: U.S. Geological Survey Open-File Report 2011–1060, 63 p., available at https://pubs.usgs.gov/of/2011/1060/.

Wells, D.L. and Coppersmith K.J. (1994), New Empirical Relationships among Magnitude, Rupture Length, Rupture width, Rupture Area, and Surface Displacement. Bulletin of the Seismological Society of America, 84, 974-1002.

Xu, Xiwei, X. Wu, G. Yu, X. Tan, and K. Li (2017), Seismo-geological signatures for identifying M≥7.0 earthquake risk areas and their preliminary application in mainland China, Seismology and Geology, 39(2), doi:10.3969/j.isn.0253-4967.2017.02.001 (in Chinese).

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Earthquake Alert

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Earthquake Alert

Earthquake Network project Earthquake Network is a research project which aims at developing and maintaining a crowdsourced smartphone-based earthquake warning system at a global level. Smartphones made available by the population are used to detect the earthquake waves using the on-board accelerometers. When an earthquake is detected, an earthquake warning is issued in order to alert the population not yet reached by the damaging waves of the earthquake.

The project started on January 1, 2013 with the release of the homonymous Android application Earthquake Network. The author of the research project and developer of the smartphone application is Francesco Finazzi of the University of Bergamo, Italy.

Get the app in the Google Play store.

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Smartphone network spatial distribution (green and red dots) on December 4, 2015

Meet The Quake-Catcher Network

QCN bloc

Quake-Catcher Network

The Quake-Catcher Network is a collaborative initiative for developing the world’s largest, low-cost strong-motion seismic network by utilizing sensors in and attached to internet-connected computers. With your help, the Quake-Catcher Network can provide better understanding of earthquakes, give early warning to schools, emergency response systems, and others. The Quake-Catcher Network also provides educational software designed to help teach about earthquakes and earthquake hazards.

After almost eight years at Stanford, and a year at CalTech, the QCN project is moving to the University of Southern California Dept. of Earth Sciences. QCN will be sponsored by the Incorporated Research Institutions for Seismology (IRIS) and the Southern California Earthquake Center (SCEC).

The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN is one of many scientific computing projects that runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC).

The volunteer computers monitor vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever strong new motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes, and which ones represent cultural noise (like doors slamming, or trucks driving by).

There are two categories of sensors used by QCN: 1) internal mobile device sensors, and 2) external USB sensors.

Mobile Devices: MEMS sensors are often included in laptops, games, cell phones, and other electronic devices for hardware protection, navigation, and game control. When these devices are still and connected to QCN, QCN software monitors the internal accelerometer for strong new shaking. Unfortunately, these devices are rarely secured to the floor, so they may bounce around when a large earthquake occurs. While this is less than ideal for characterizing the regional ground shaking, many such sensors can still provide useful information about earthquake locations and magnitudes.

USB Sensors: MEMS sensors can be mounted to the floor and connected to a desktop computer via a USB cable. These sensors have several advantages over mobile device sensors. 1) By mounting them to the floor, they measure more reliable shaking than mobile devices. 2) These sensors typically have lower noise and better resolution of 3D motion. 3) Desktops are often left on and do not move. 4) The USB sensor is physically removed from the game, phone, or laptop, so human interaction with the device doesn’t reduce the sensors’ performance. 5) USB sensors can be aligned to North, so we know what direction the horizontal “X” and “Y” axes correspond to.

If you are a science teacher at a K-12 school, please apply for a free USB sensor and accompanying QCN software. QCN has been able to purchase sensors to donate to schools in need. If you are interested in donating to the program or requesting a sensor, click here.

BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.

Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can join together to improve earthquake monitoring, earthquake awareness, and the science of earthquakes. The Quake-Catcher Network (QCN) links existing networked laptops and desktops in hopes to form the worlds largest strong-motion seismic network.

Below, the QCN Quake Catcher Network map
QCN Quake Catcher Network map

ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States

The U. S. Geological Survey (USGS) along with a coalition of State and university partners is developing and testing an earthquake early warning (EEW) system called ShakeAlert for the west coast of the United States. Long term funding must be secured before the system can begin sending general public notifications, however, some limited pilot projects are active and more are being developed. The USGS has set the goal of beginning limited public notifications in 2018.

Watch a video describing how ShakeAlert works in English or Spanish.

The primary project partners include:

United States Geological Survey
California Governor’s Office of Emergency Services (CalOES)
California Geological Survey
California Institute of Technology
University of California Berkeley
University of Washington
University of Oregon
Gordon and Betty Moore Foundation

The Earthquake Threat

Earthquakes pose a national challenge because more than 143 million Americans live in areas of significant seismic risk across 39 states. Most of our Nation’s earthquake risk is concentrated on the West Coast of the United States. The Federal Emergency Management Agency (FEMA) has estimated the average annualized loss from earthquakes, nationwide, to be $5.3 billion, with 77 percent of that figure ($4.1 billion) coming from California, Washington, and Oregon, and 66 percent ($3.5 billion) from California alone. In the next 30 years, California has a 99.7 percent chance of a magnitude 6.7 or larger earthquake and the Pacific Northwest has a 10 percent chance of a magnitude 8 to 9 megathrust earthquake on the Cascadia subduction zone.

Part of the Solution

Today, the technology exists to detect earthquakes, so quickly, that an alert can reach some areas before strong shaking arrives. The purpose of the ShakeAlert system is to identify and characterize an earthquake a few seconds after it begins, calculate the likely intensity of ground shaking that will result, and deliver warnings to people and infrastructure in harm’s way. This can be done by detecting the first energy to radiate from an earthquake, the P-wave energy, which rarely causes damage. Using P-wave information, we first estimate the location and the magnitude of the earthquake. Then, the anticipated ground shaking across the region to be affected is estimated and a warning is provided to local populations. The method can provide warning before the S-wave arrives, bringing the strong shaking that usually causes most of the damage.

Studies of earthquake early warning methods in California have shown that the warning time would range from a few seconds to a few tens of seconds. ShakeAlert can give enough time to slow trains and taxiing planes, to prevent cars from entering bridges and tunnels, to move away from dangerous machines or chemicals in work environments and to take cover under a desk, or to automatically shut down and isolate industrial systems. Taking such actions before shaking starts can reduce damage and casualties during an earthquake. It can also prevent cascading failures in the aftermath of an event. For example, isolating utilities before shaking starts can reduce the number of fire initiations.

System Goal

The USGS will issue public warnings of potentially damaging earthquakes and provide warning parameter data to government agencies and private users on a region-by-region basis, as soon as the ShakeAlert system, its products, and its parametric data meet minimum quality and reliability standards in those geographic regions. The USGS has set the goal of beginning limited public notifications in 2018. Product availability will expand geographically via ANSS regional seismic networks, such that ShakeAlert products and warnings become available for all regions with dense seismic instrumentation.

Current Status

The West Coast ShakeAlert system is being developed by expanding and upgrading the infrastructure of regional seismic networks that are part of the Advanced National Seismic System (ANSS); the California Integrated Seismic Network (CISN) is made up of the Southern California Seismic Network, SCSN) and the Northern California Seismic System, NCSS and the Pacific Northwest Seismic Network (PNSN). This enables the USGS and ANSS to leverage their substantial investment in sensor networks, data telemetry systems, data processing centers, and software for earthquake monitoring activities residing in these network centers. The ShakeAlert system has been sending live alerts to “beta” users in California since January of 2012 and in the Pacific Northwest since February of 2015.

In February of 2016 the USGS, along with its partners, rolled-out the next-generation ShakeAlert early warning test system in California joined by Oregon and Washington in April 2017. This West Coast-wide “production prototype” has been designed for redundant, reliable operations. The system includes geographically distributed servers, and allows for automatic fail-over if connection is lost.

This next-generation system will not yet support public warnings but does allow selected early adopters to develop and deploy pilot implementations that take protective actions triggered by the ShakeAlert notifications in areas with sufficient sensor coverage.

Authorities

The USGS will develop and operate the ShakeAlert system, and issue public notifications under collaborative authorities with FEMA, as part of the National Earthquake Hazard Reduction Program, as enacted by the Earthquake Hazards Reduction Act of 1977, 42 U.S.C. §§ 7704 SEC. 2.

For More Information

Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

QuakeAlertUSA

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About Early Warning Labs, LLC

Early Warning Labs, LLC (EWL) is an Earthquake Early Warning technology developer and integrator located in Santa Monica, CA. EWL is partnered with industry leading GIS provider ESRI, Inc. and is collaborating with the US Government and university partners.

EWL is investing millions of dollars over the next 36 months to complete the final integration and delivery of Earthquake Early Warning to individual consumers, government entities, and commercial users.

EWL’s mission is to improve, expand, and lower the costs of the existing earthquake early warning systems.

EWL is developing a robust cloud server environment to handle low-cost mass distribution of these warnings. In addition, Early Warning Labs is researching and developing automated response standards and systems that allow public and private users to take pre-defined automated actions to protect lives and assets.

EWL has an existing beta R&D test system installed at one of the largest studios in Southern California. The goal of this system is to stress test EWL’s hardware, software, and alert signals while improving latency and reliability.

Earthquake Early Warning Introduction

The United States Geological Survey (USGS), in collaboration with state agencies, university partners, and private industry, is developing an earthquake early warning system (EEW) for the West Coast of the United States called ShakeAlert. The USGS Earthquake Hazards Program aims to mitigate earthquake losses in the United States. Citizens, first responders, and engineers rely on the USGS for accurate and timely information about where earthquakes occur, the ground shaking intensity in different locations, and the likelihood is of future significant ground shaking.

The ShakeAlert Earthquake Early Warning System recently entered its first phase of operations. The USGS working in partnership with the California Governor’s Office of Emergency Services (Cal OES) is now allowing for the testing of public alerting via apps, Wireless Emergency Alerts, and by other means throughout California.

ShakeAlert partners in Oregon and Washington are working with the USGS to test public alerting in those states sometime in 2020.

ShakeAlert has demonstrated the feasibility of earthquake early warning, from event detection to producing USGS issued ShakeAlerts ® and will continue to undergo testing and will improve over time. In particular, robust and reliable alert delivery pathways for automated actions are currently being developed and implemented by private industry partners for use in California, Oregon, and Washington.

Earthquake Early Warning Background

The objective of an earthquake early warning system is to rapidly detect the initiation of an earthquake, estimate the level of ground shaking intensity to be expected, and issue a warning before significant ground shaking starts. A network of seismic sensors detects the first energy to radiate from an earthquake, the P-wave energy, and the location and the magnitude of the earthquake is rapidly determined. Then, the anticipated ground shaking across the region to be affected is estimated. The system can provide warning before the S-wave arrives, which brings the strong shaking that usually causes most of the damage. Warnings will be distributed to local and state public emergency response officials, critical infrastructure, private businesses, and the public. EEW systems have been successfully implemented in Japan, Taiwan, Mexico, and other nations with varying degrees of sophistication and coverage.

Earthquake early warning can provide enough time to:

Instruct students and employees to take a protective action such as Drop, Cover, and Hold On
Initiate mass notification procedures
Open fire-house doors and notify local first responders
Slow and stop trains and taxiing planes
Install measures to prevent/limit additional cars from going on bridges, entering tunnels, and being on freeway overpasses before the shaking starts
Move people away from dangerous machines or chemicals in work environments
Shut down gas lines, water treatment plants, or nuclear reactors
Automatically shut down and isolate industrial systems

However, earthquake warning notifications must be transmitted without requiring human review and response action must be automated, as the total warning times are short depending on geographic distance and varying soil densities from the epicenter.