From Eos: “Distant Quake Triggered Slow Slip on Southern San Andreas”

From AGU
Eos news bloc

From Eos

23 September 2019
Terri Cook

A high-resolution map of surface displacements indicates that the 2017 Chiapas earthquake caused substantial creep along a segment of the San Andreas Fault, located 3,000 kilometers away.

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The 2017 magnitude 8.3 Chiapas earthquake caused up to 15 millimeters of creep on the segment of the San Andreas Fault that runs along the northeastern edge of California’s Salton Sea. Credit: USGS/NASA’s Earth Observatory

In the traditional model of the earthquake cycle, a seismic event occurs when an active fault abruptly releases strain that has built up over time. About 20 years ago, however, seismologists began finding that some faults, or sections of faults, can experience slow earthquakes—a gradual type of aseismic slip, or “creep,” that can last for months. Because both types of events release pent-up energy, determining the proportion of seismic versus aseismic slip along active faults is crucial for estimating their potential hazard.

Although conventional interpretations predict that aseismic slip should occur at a roughly constant rate, geodetic observations have shown that at some locations fault creep is anything but steady. Measurements along the southern San Andreas Fault in California, one of the most studied examples of a creeping fault, have shown that this section often experiences bouts of accelerated creep and that these events can be spontaneous or triggered by seismic events. But the underlying conditions and mechanisms that cause slow slip are still poorly understood.

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San Andreas Fault. Temblor

Now Tymofyeyeva et al. [JGR Solid Earth] report detailed observations of a slow-slip event that occurred along the southern San Andreas Fault following the magnitude 8.3 earthquake that hit offshore Chiapas, Mexico, in September 2017. The team combined the results of field mapping with creepmeter and Sentinel-1 interferometric synthetic aperture radar observations to create a high-resolution map of surface displacements near the Salton Sea. The researchers then entered the results into numerical models to constrain the crustal properties that could generate the observed behavior.

The results indicated that surface slip along the 40-kilometer-long section between Bombay Beach and the Mecca Hills accelerated within minutes of the Chiapas earthquake and continued for more than a year. The event resulted in total surface offsets that averaged 5-10 millimeters, comparable to the slow slip triggered by the 2010 magnitude 7.2 El Mayor-Cucapah (Baja) earthquake, even though the stress changes along the southern San Andreas due to the Chiapas earthquake were several orders of magnitude lower.

The findings offer compelling evidence that the Chiapas earthquake triggered the 2017 slow-slip event along the southern San Andreas Fault, according to the researchers, and show that although shallow creep near the Salton Sea is roughly constant on decadal timescales, it can vary significantly over shorter periods of time. The authors conclude that the response of the southern San Andreas, and potentially other major faults, to different seismic events is complex and likely reflects crustal conditions as well as local creep history.

See the full article here .

Earthquake Alert

1

Earthquake Alert

Earthquake Network projectEarthquake 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

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From LANL via WIRED: “AI Helps Seismologists Predict Earthquakes”

LANL bloc

Los Alamos National Laboratory

via

Wired logo

From WIRED

Machine learning is bringing seismologists closer to an elusive goal: forecasting quakes well before they strike.

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Remnants of a 2,000-year-old spruce forest on Neskowin Beach, Oregon — one of dozens of “ghost forests” along the Oregon and Washington coast. It’s thought that a mega-earthquake of the Cascadia subduction zone felled the trees, and that the stumps were then buried by tsunami debris.Photograph: Race Jones/Outlive Creative

In May of last year, after a 13-month slumber, the ground beneath Washington’s Puget Sound rumbled to life. The quake began more than 20 miles below the Olympic mountains and, over the course of a few weeks, drifted northwest, reaching Canada’s Vancouver Island. It then briefly reversed course, migrating back across the US border before going silent again. All told, the monthlong earthquake likely released enough energy to register as a magnitude 6. By the time it was done, the southern tip of Vancouver Island had been thrust a centimeter or so closer to the Pacific Ocean.

Because the quake was so spread out in time and space, however, it’s likely that no one felt it. These kinds of phantom earthquakes, which occur deeper underground than conventional, fast earthquakes, are known as “slow slips.” They occur roughly once a year in the Pacific Northwest, along a stretch of fault where the Juan de Fuca plate is slowly wedging itself beneath the North American plate. More than a dozen slow slips have been detected by the region’s sprawling network of seismic stations since 2003. And for the past year and a half, these events have been the focus of a new effort at earthquake prediction by the geophysicist Paul Johnson.

Johnson’s team is among a handful of groups that are using machine learning to try to demystify earthquake physics and tease out the warning signs of impending quakes. Two years ago, using pattern-finding algorithms similar to those behind recent advances in image and speech recognition and other forms of artificial intelligence, he and his collaborators successfully predicted temblors in a model laboratory system—a feat that has since been duplicated by researchers in Europe.

Now, in a paper posted this week on the scientific preprint site arxiv.org, Johnson and his team report that they’ve tested their algorithm on slow slip quakes in the Pacific Northwest. The paper has yet to undergo peer review, but outside experts say the results are tantalizing. According to Johnson, they indicate that the algorithm can predict the start of a slow slip earthquake to “within a few days—and possibly better.”

“This is an exciting development,” said Maarten de Hoop, a seismologist at Rice University who was not involved with the work. “For the first time, I think there’s a moment where we’re really making progress” toward earthquake prediction.

Mostafa Mousavi, a geophysicist at Stanford University, called the new results “interesting and motivating.” He, de Hoop, and others in the field stress that machine learning has a long way to go before it can reliably predict catastrophic earthquakes—and that some hurdles may be difficult, if not impossible, to surmount. Still, in a field where scientists have struggled for decades and seen few glimmers of hope, machine learning may be their best shot.

Sticks and Slips

The late seismologist Charles Richter, for whom the Richter magnitude scale is named, noted in 1977 that earthquake prediction can provide “a happy hunting ground for amateurs, cranks, and outright publicity-seeking fakers.” Today, many seismologists will tell you that they’ve seen their fair share of all three.

But there have also been reputable scientists who concocted theories that, in hindsight, seem woefully misguided, if not downright wacky. There was the University of Athens geophysicist Panayiotis Varotsos, who claimed he could detect impending earthquakes by measuring “seismic electric signals.” There was Brian Brady, the physicist from the US Bureau of Mines who in the early 1980s sounded successive false alarms in Peru, basing them on a tenuous notion that rock bursts in underground mines were telltale signs of coming quakes.

Paul Johnson is well aware of this checkered history. He knows that the mere phrase “earthquake prediction” is taboo in many quarters. He knows about the six Italian scientists who were convicted of manslaughter in 2012 for downplaying the chances of an earthquake near the central Italian town of L’Aquila, days before the region was devastated by a magnitude 6.3 temblor. (The convictions were later overturned.) He knows about the prominent seismologists who have forcefully declared that “earthquakes cannot be predicted.”

But Johnson also knows that earthquakes are physical processes, no different in that respect from the collapse of a dying star or the shifting of the winds. And though he stresses that his primary aim is to better understand fault physics, he hasn’t shied away from the prediction problem.

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Paul Johnson, a geophysicist at Los Alamos National Laboratory, photographed in 2008 with a block of acrylic plastic, one of the materials his team uses to simulate earthquakes in the laboratory.Photograph: Los Alamos National Laboratory

More than a decade ago, Johnson began studying “laboratory earthquakes,” made with sliding blocks separated by thin layers of granular material. Like tectonic plates, the blocks don’t slide smoothly but in fits and starts: They’ll typically stick together for seconds at a time, held in place by friction, until the shear stress grows large enough that they suddenly slip. That slip—the laboratory version of an earthquake—releases the stress, and then the stick-slip cycle begins anew.

When Johnson and his colleagues recorded the acoustic signal emitted during those stick-slip cycles, they noticed sharp peaks just before each slip. Those precursor events were the laboratory equivalent of the seismic waves produced by foreshocks before an earthquake. But just as seismologists have struggled to translate foreshocks into forecasts of when the main quake will occur, Johnson and his colleagues couldn’t figure out how to turn the precursor events into reliable predictions of laboratory quakes. “We were sort of at a dead end,” Johnson recalled. “I couldn’t see any way to proceed.”

At a meeting a few years ago in Los Alamos, Johnson explained his dilemma to a group of theoreticians. They suggested he reanalyze his data using machine learning—an approach that was well known by then for its prowess at recognizing patterns in audio data.

Together, the scientists hatched a plan. They would take the roughly five minutes of audio recorded during each experimental run—encompassing 20 or so stick-slip cycles—and chop it up into many tiny segments. For each segment, the researchers calculated more than 80 statistical features, including the mean signal, the variation about that mean, and information about whether the segment contained a precursor event. Because the researchers were analyzing the data in hindsight, they also knew how much time had elapsed between each sound segment and the subsequent failure of the laboratory fault.

Armed with this training data, they used what’s known as a “random forest” machine learning algorithm to systematically look for combinations of features that were strongly associated with the amount of time left before failure. After seeing a couple of minutes’ worth of experimental data, the algorithm could begin to predict failure times based on the features of the acoustic emission alone.

Johnson and his co-workers chose to employ a random forest algorithm to predict the time before the next slip in part because—compared with neural networks and other popular machine learning algorithms—random forests are relatively easy to interpret. The algorithm essentially works like a decision tree in which each branch splits the data set according to some statistical feature. The tree thus preserves a record of which features the algorithm used to make its predictions—and the relative importance of each feature in helping the algorithm arrive at those predictions.

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A polarizing lens shows the buildup of stress as a model tectonic plate slides laterally along a fault line in an experiment at Los Alamos National Laboratory.Photograph: Los Alamos National Laboratory.

When the Los Alamos researchers probed those inner workings of their algorithm, what they learned surprised them. The statistical feature the algorithm leaned on most heavily for its predictions was unrelated to the precursor events just before a laboratory quake. Rather, it was the variance—a measure of how the signal fluctuates about the mean—and it was broadcast throughout the stick-slip cycle, not just in the moments immediately before failure. The variance would start off small and then gradually climb during the run-up to a quake, presumably as the grains between the blocks increasingly jostled one another under the mounting shear stress. Just by knowing this variance, the algorithm could make a decent guess at when a slip would occur; information about precursor events helped refine those guesses.

The finding had big potential implications. For decades, would-be earthquake prognosticators had keyed in on foreshocks and other isolated seismic events. The Los Alamos result suggested that everyone had been looking in the wrong place—that the key to prediction lay instead in the more subtle information broadcast during the relatively calm periods between the big seismic events.

To be sure, sliding blocks don’t begin to capture the chemical, thermal and morphological complexity of true geological faults. To show that machine learning could predict real earthquakes, Johnson needed to test it out on a real fault. What better place to do that, he figured, than in the Pacific Northwest?

Out of the Lab

Most if not all of the places on Earth that can experience a magnitude 9 earthquake are subduction zones, where one tectonic plate dives beneath another. A subduction zone just east of Japan was responsible for the Tohoku earthquake and the subsequent tsunami that devastated the country’s coastline in 2011. One day, the Cascadia subduction zone, where the Juan de Fuca plate dives beneath the North American plate, will similarly devastate Puget Sound, Vancouver Island and the surrounding Pacific Northwest.

Cascadia plate zones

Cascadia subduction zone

The Cascadia subduction zone stretches along roughly 1,000 kilometers of the Pacific coastline from Cape Mendocino in Northern California to Vancouver Island. The last time it breached, in January 1700, it begot a magnitude 9 temblor and a tsunami that reached the coast of Japan. Geological records suggest that throughout the Holocene, the fault has produced such megaquakes roughly once every half-millennium, give or take a few hundred years. Statistically speaking, the next big one is due any century now.

That’s one reason seismologists have paid such close attention to the region’s slow slip earthquakes. The slow slips in the lower reaches of a subduction-zone fault are thought to transmit small amounts of stress to the brittle crust above, where fast, catastrophic quakes occur. With each slow slip in the Puget Sound-Vancouver Island area, the chances of a Pacific Northwest megaquake ratchet up ever so slightly. Indeed, a slow slip was observed in Japan in the month leading up to the Tohoku quake.

For Johnson, however, there’s another reason to pay attention to slow slip earthquakes: They produce lots and lots of data. For comparison, there have been no major fast earthquakes on the stretch of fault between Puget Sound and Vancouver Island in the past 12 years. In the same time span, the fault has produced a dozen slow slips, each one recorded in a detailed seismic catalog.

That seismic catalog is the real-world counterpart to the acoustic recordings from Johnson’s laboratory earthquake experiment. Just as they did with the acoustic recordings, Johnson and his co-workers chopped the seismic data into small segments, characterizing each segment with a suite of statistical features. They then fed that training data, along with information about the timing of past slow slip events, to their machine learning algorithm.

After being trained on data from 2007 to 2013, the algorithm was able to make predictions about slow slips that occurred between 2013 and 2018, based on the data logged in the months before each event. The key feature was the seismic energy, a quantity closely related to the variance of the acoustic signal in the laboratory experiments. Like the variance, the seismic energy climbed in a characteristic fashion in the run-up to each slow slip.

The Cascadia forecasts weren’t quite as accurate as the ones for laboratory quakes. The correlation coefficients characterizing how well the predictions fit observations were substantially lower in the new results than they were in the laboratory study. Still, the algorithm was able to predict all but one of the five slow slips that occurred between 2013 and 2018, pinpointing the start times, Johnson says, to within a matter of days. (A slow slip that occurred in August 2019 wasn’t included in the study.)

For de Hoop, the big takeaway is that “machine learning techniques have given us a corridor, an entry into searching in data to look for things that we have never identified or seen before.” But he cautions that there’s more work to be done. “An important step has been taken—an extremely important step. But it is like a tiny little step in the right direction.”

Sobering Truths

The goal of earthquake forecasting has never been to predict slow slips. Rather, it’s to predict sudden, catastrophic quakes that pose danger to life and limb. For the machine learning approach, this presents a seeming paradox: The biggest earthquakes, the ones that seismologists would most like to be able to foretell, are also the rarest. How will a machine learning algorithm ever get enough training data to predict them with confidence?

The Los Alamos group is betting that their algorithms won’t actually need to train on catastrophic earthquakes to predict them. Recent studies suggest that the seismic patterns before small earthquakes are statistically similar to those of their larger counterparts, and on any given day, dozens of small earthquakes may occur on a single fault. A computer trained on thousands of those small temblors might be versatile enough to predict the big ones. Machine learning algorithms might also be able to train on computer simulations of fast earthquakes that could one day serve as proxies for real data.

But even so, scientists will confront this sobering truth: Although the physical processes that drive a fault to the brink of an earthquake may be predictable, the actual triggering of a quake—the growth of a small seismic disturbance into full-blown fault rupture—is believed by most scientists to contain at least an element of randomness. Assuming that’s so, no matter how well machines are trained, they may never be able to predict earthquakes as well as scientists predict other natural disasters.

“We don’t know what forecasting in regards to timing means yet,” Johnson said. “Would it be like a hurricane? No, I don’t think so.”

In the best-case scenario, predictions of big earthquakes will probably have time bounds of weeks, months or years. Such forecasts probably couldn’t be used, say, to coordinate a mass evacuation on the eve of a temblor. But they could increase public preparedness, help public officials target their efforts to retrofit unsafe buildings, and otherwise mitigate hazards of catastrophic earthquakes.

Johnson sees that as a goal worth striving for. Ever the realist, however, he knows it will take time. “I’m not saying we’re going to predict earthquakes in my lifetime,” he said, “but … we’re going to make a hell of a lot of progress.”

See the full article here .

Earthquake Alert

1

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.

3
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

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From University of Washington: “USGS awards $10.4M to ShakeAlert earthquake early warning system in the Pacific Northwest “

U Washington

From University of Washington

August 19, 2019

The U.S. Geological Survey today announced $10.4 million in funding to the Pacific Northwest Seismic Network, based at University of Washington, to support the ShakeAlert earthquake early warning system. Some $7.3 million of the funding will go to the UW.

The PNSN is responsible for monitoring earthquakes and volcanoes in Washington and Oregon. It is a partnership between the University of Washington, the University of Oregon and the USGS. The support for the PNSN is among the new ShakeAlert cooperative agreements announced today by the USGS.

The first year’s funding of $5.4 million to the PNSN begins this month. The UW will receive about $3.75 million in direct support of its PNSN activities and $1.66 million will support the PNSN team at the University of Oregon. The second-year funding, of an additional $5 million, is contingent on approval by Congress and will be similarly shared.

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Karl Hagel and Pat McChesney, field engineers with the Pacific Northwest Seismic Network team at the University of Washington, install earthquake monitoring equipment on the slopes of Mount St. Helens, with Mount Hood in the distance.Marc Biundo/University of Washington.

“This investment in the PNSN represents a major increase in federal support for earthquake monitoring in the Cascadia region,” said Harold Tobin, director of the PNSN and professor in the UW’s Department of Earth and Space Sciences. “At the end of the two years of funding we anticipate having essentially doubled the number of seismic stations across our whole region that contribute to real-time earthquake early warning. This would allow for full public alerts of any potentially damaging earthquakes, across our entire region of Washington and Oregon, by the end of the two-year period.”

This new award will allow for installation of 104 new seismic stations in Washington state and 44 in Oregon, during the two-year period. It will also support improved, more-sophisticated detection of earthquakes as they begin, and new efforts to engage potential users of the warnings.

ShakeAlert’s network of instruments detect the first, less damaging waves from a major earthquake close to where the earthquake begins. The system then issues alerts for the estimated size and location of the earthquake, providing seconds or minutes of warning before the more damaging ground shaking begins – enough for someone to pull off the road, stop a surgery, or find a safe place to take shelter.

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A sample warning, with a countdown of the number of seconds until the strong shaking reaches the user.Pacific Northwest Seismic Network

In the Pacific Northwest’s pilot phase of the system, early adopters in the region have developed pilot projects with guidance and support from the PNSN and USGS, and have received ShakeAlert warning messages for the past two years. These warnings are currently used to trigger loss-reduction measures at critical facilities — such as turning off water valves in public utility districts — before dangerous shaking would arrive.

The additional funding will support the development of new pilot projects in schools, businesses, communities and critical infrastructure facilities in preparation for the eventual goal of open alerts to the general public, as launched recently in the Los Angeles region. The improvements to PNSN’s network supported by this funding will meet the USGS’ recommended station-density standard for public alerting in almost all areas of Washington and Oregon.

“It will enable us to rapidly build out our network to produce faster and more accurate alerts for Cascadia Region earthquakes,” Tobin said.

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Existing Pacific Northwest Seismic Network ShakeAlert stations, as of spring 2019. The new funding will roughly double the number of stations in Washington and Oregon.

The funding will also support ongoing research to integrate GPS data into ShakeAlert, which will allow quicker estimates of the magnitude of offshore Cascadia Subduction Zone earthquakes as they unfold. The UW is sharing its research in this area with the National Oceanic and Atmospheric Administration and NASA in the hope of improving tsunami-warning capabilities. The UW is working with Central Washington University, also supported by USGS, to receive near-real-time GPS data from across Washington and Oregon that will be integrated into future releases of ShakeAlert.

The regional ShakeAlert effort began in 2011, when the UW joined the University of California, Berkeley and California Institute of Technology as a primary ShakeAlert center in the developing a West Coast warning system. The Gordon and Betty Moore Foundation awarded $2 million to each university to kick-start ShakeAlert from a research project to an operational system. With support from Congress, the USGS ramped up support for ShakeAlert as the foundation’s seed funding expired.

Additional support for PNSN operations comes from the U.S. Department of Energy and the states Oregon and Washington. The Washington legislature, in its current biennium budget, allocated $1.24 million over two years for additional enhancements to the ShakeAlert network.

See the full article here .


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The University of Washington is one of the world’s preeminent public universities. Our impact on individuals, on our region, and on the world is profound — whether we are launching young people into a boundless future or confronting the grand challenges of our time through undaunted research and scholarship. Ranked number 10 in the world in Shanghai Jiao Tong University rankings and educating more than 54,000 students annually, our students and faculty work together to turn ideas into impact and in the process transform lives and our world. For more about our impact on the world, every day.
So what defines us —the students, faculty and community members at the University of Washington? Above all, it’s our belief in possibility and our unshakable optimism. It’s a connection to others, both near and far. It’s a hunger that pushes us to tackle challenges and pursue progress. It’s the conviction that together we can create a world of good. Join us on the journey.

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From University or Oregon via EarthSky: “A big earthquake in the US Pacific Northwest?”

From University or Oregon

via

1

EarthSky

August 5, 2019
Miles Bodmer, University of Oregon
Doug Toomey, University of Oregon

Most people don’t associate the US Pacific Northwest with earthquakes, but maybe they should. It’s home to the 600-mile (1,000-km) Cascadia megathrust fault, stretching from northern California to Canada’s Vancouver Island.

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Data derived from NaturalEarthData.com, 10m datasets. Projected into NAD83 UTM 9N. Alicia.iverson

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This is the USGS’ scenario ShakeMap for a M9 shock on the Casdadia Subduction Zone. This is not a real event.
23 December 2016
Source Earthquakes Shakemap usCasc9.0_se
Author United States Geological Survey

The Pacific Northwest is known for many things – its beer, its music, its mythical large-footed creatures. Most people don’t associate it with earthquakes, but they should. It’s home to the Cascadia megathrust fault that runs 600 miles (966 km) from Northern California up to Vancouver Island in Canada, spanning several major metropolitan areas including Seattle and Portland, Oregon.

This geologic fault has been relatively quiet in recent memory. There haven’t been many widely felt quakes along the Cascadia megathrust, certainly nothing that would rival a catastrophic event like the 1989 Loma Prieta earthquake along the active San Andreas in California. That doesn’t mean it will stay quiet, though. Scientists know it has the potential for large earthquakes – as big as magnitude 9.

Geophysicists have known for over a decade that not all portions of the Cascadia megathrust fault behave the same. The northern and southern sections are much more seismically active than the central section – with frequent small earthquakes and ground deformations that residents don’t often notice. But why do these variations exist and what gives rise to them?

Our research tries to answer these questions by constructing images of what’s happening deep within the Earth [Geophysical Research Letters Research], more than 90 miles (144 km) below the fault. We’ve identified regions that are rising up beneath these active sections which we think are leading to the observable differences along the Cascadia fault.

Cascadia and the ‘Really Big One’

The Cascadia subduction zone is a region where two tectonic plates are colliding. The Juan de Fuca, a small oceanic plate, is being driven under the North American plate, atop which the continental U.S. sits.

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The Juan de Fuca plate meets the North American plate beneath the Cascadia fault. Image via USGS.

Subduction systems – where one tectonic plate slides over another – are capable of producing the world’s largest known earthquakes. A prime example is the 2011 Tohoku earthquake that rocked Japan.

Cascadia is seismically very quiet compared to other subduction zones – but it’s not completely inactive. Research indicates the fault ruptured in a magnitude 9.0 event in 1700. That’s roughly 30 times more powerful than the largest predicted San Andreas earthquake. Researchers suggest that we are within the roughly 300- to 500-year window during which another large Cascadia event may occur.

Many smaller undamaging and unfelt events take place in northern and southern Cascadia every year. However, in central Cascadia, underlying most of Oregon, there is very little seismicity. Why would the same fault behave differently in different regions?

Over the last decade, scientists have made several additional observations that highlight variations along the fault.

One has to do with plate locking, which tells us where stress is accumulating along the fault. If the tectonic plates are locked – that is, really stuck together and unable to move past each other – stress builds. Eventually that stress can be released rapidly as an earthquake, with the magnitude depending on how large the patch of fault that ruptures is.

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A GPS geosensor in Washington. Image via Bdelisle.

Geologists have recently been able to deploy hundreds of GPS monitors across Cascadia to record the subtle ground deformations that result from the plates’ inability to slide past each other. Just like historic seismicity, plate locking is more common in the northern and southern parts of Cascadia.

Geologists are also now able to observe difficult-to-detect seismic rumblings known as tremor. These events occur over the time span of several minutes up to weeks, taking much longer than a typical earthquake. They don’t cause large ground motions even though they can release significant amounts of energy. Researchers have only discovered these signals in the last 15 years, but permanent seismic stations have helped build a robust catalog of events. Tremor, too, seems to be more concentrated along the northern and southern parts of the fault.

What would cause this situation, with the area beneath Oregon relatively less active by all these measures? To explain we had to look deep, over 100 kilometers (60 miles) below the surface, into the Earth’s mantle.

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Green dots and blue triangles show locations of seismic monitoring stations. Image via Bodmer et al., 2018, Geophysical Research Letters.

Imaging the Earth using distant quakes

Physicians use electromagnetic waves to “see” internal structures like bones without needing to open up a human patient to view them directly. Geologists image the Earth in much the same way. Instead of X-rays, we use seismic energy radiating out from distant magnitude 6.0-plus earthquakes to help us “see” features we physically just can’t get to. This energy travels like sound waves through the structures of the Earth. When rock is hotter or partially molten by even a tiny amount, seismic waves slow down. By measuring the arrival times of seismic waves, we create 3-D images showing how fast or slow the seismic waves travel through specific parts of the Earth.

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Ocean bottom seismometers waiting to be deployed during the Cascadia Initiative. Image via Emilie Hooft.

To see these signals, we need records from seismic monitoring stations. More sensors provide better resolution and a clearer image – but gathering more data can be problematic when half the area you’re interested in is underwater. To address this challenge, we were part of a team of scientists that deployed hundreds of seismometers on the ocean floor off the western U.S. over the span of four years, starting in 2011. This experiment, the Cascadia Initiative, was the first ever to cover an entire tectonic plate with instruments at a spacing of roughly 30 miles (50 km).

What we found are two anomalous regions beneath the fault where seismic waves travel slower than expected. These anomalies are large, about 90 miles (150 km) in diameter, and show up beneath the northern and southern sections of the fault. Remember, that’s where researchers have already observed increased activity: the seismicity. Interestingly, the anomalies are not present beneath the central part of the fault, under Oregon, where we see a decrease in activity.

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Regions where seismic waves moved more slowly, on average, are redder, while the areas where they moved more quickly are bluer. The slower anomalous areas 90 miles (150 km) beneath the Earth’s surface corresponded to where the colliding plates are more locked and where tremor is more common. Image via Bodmer et al., 2018, Geophysical Research Letters.

So what exactly are these anomalies?

The tectonic plates float on the Earth’s rocky mantle layer. Where the mantle is slowly rising over millions of years, the rock decompresses. Since it’s at such high temperatures, nearly 1500 degrees Celsius (2700 F) at 100 km (60 mi) depth, it can melt ever so slightly.

These physical changes cause the anomalous regions to be more buoyant – melted hot rock is less dense than solid cooler rock. It’s this buoyancy that we believe is affecting how the fault above behaves. The hot, partially molten region pushes upwards on what’s above, similar to how a helium balloon might rise up against a sheet draped over it. We believe this increases the forces between the two plates, causing them to be more strongly coupled and thus more fully locked.

A general prediction for where, but not when

Our results provide new insights into how this subduction zone, and possibly others, behaves over geologic time frames of millions of years. Unfortunately our results can’t predict when the next large Cascadia megathrust earthquake will occur. This will require more research and dense active monitoring of the subduction zone, both onshore and offshore, using seismic and GPS-like stations to capture short-term phenomena.

Our work does suggest that a large event is more likely to start in either the northern or southern sections of the fault, where the plates are more fully locked, and gives a possible reason for why that may be the case.

It remains important for the public and policymakers to stay informed about the potential risk involved in cohabiting with a subduction zone fault and to support programs such as Earthquake Early Warning that seek to expand our monitoring capabilities and mitigate loss in the event of a large rupture.

See the full article here .

Earthquake Alert

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Earthquake Alert

Earthquake Network projectEarthquake 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

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The University of Oregon (also referred to as UO, U of O or Oregon) is a public flagship research university in Eugene, Oregon. Founded in 1876, the institution’s 295-acre campus is along the Willamette River. Since July 2014, UO has been governed by the Board of Trustees of the University of Oregon. The university has a Carnegie Classification of “highest research activity” and has 19 research centers and institutes. UO was admitted to the Association of American Universities in 1969.

The University of Oregon is organized into five colleges (Arts and Sciences, Business, Design, Education, and Honors) and seven professional schools (Accounting, Architecture and Environment, Art and Design, Journalism and Communication, Law, Music and Dance, and Planning, Public Policy and Management) and a graduate school. Furthermore, UO offers 316 undergraduate and graduate degree programs. Most academic programs follow the 10 week Quarter System.

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From UC Berkeley via Science Alert: “A Tectonic Plate Under Oregon Is Being Slowly Ripped Apart”

From UC Berkeley

via

ScienceAlert

Science Alert

31 JUL 2019
DAVID NIELD

Spare a thought for the Juan de Fuca tectonic plate, not long for this world (in tectonic plate terms) as it slowly slides under the continent of North America.

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Map of the Juan de Fuca Plate. No image credit. Wikipedia.

Geologists are hoping it can help solve one of the biggest mysteries in their field – how tectonic plates die.

The Juan de Fuca plate is the last remnant of the much bigger Farallon plate, which has been disappearing under North America for tens of millions of years. It’s the perfect opportunity to study how plates eventually get swallowed up, and how that might cause seismic and volcanic activity on the surface.

In particular, researchers William Hawley and Richard Allen, from the University of California, Berkeley, are interested in a gap that’s appearing in the Juan de Fuca plate – which may in fact represent a tearing of the plate way down below the surface.

“The tearing not only causes volcanism on North America but also causes deformation of the not‐yet‐subducted sections of the oceanic plate offshore,” write the researchers in their newly published paper [Geophysical Letters Research].

“This tearing may eventually cause the plate to fragment, and what is left of the small pieces of the plate will attach to other plates nearby.”

All the rock that gets buried as a plate is subsumed has to go somewhere, and the large-scale deformations and breaks that can occur aren’t easy for scientists to predict or map.

Using data from 217 earthquakes and more than 30,000 seismic waves, Hawley and Allen have been able to put together a detailed 3D picture of this particular part of the Cascadia Subduction Zone.

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Cascadia subduction zone. USGS.

Specifically, they identified which parts of the rock were from the Juan de Fuca plate.

They found what looks like a tear more than 150 kilometres (93 miles) deep, and it matches a previously identified area of weakness on the Juan de Fuca plate at the surface, known as a propagator wake.

The researchers suggest that as the Juan de Fuca plate turns and twists, parts of it are being pulled off and separated, creating the gap that experts have observed. Some of it might even live on as part of another plate.

More evidence is needed to be sure of what is happening here, but the hypothesis matches seismic activity around southern Oregon and northern California, as well as unusual patterns of volcanism in the region.

Those unusual patterns are the volcanoes known as the High Lava Plains in southern Oregon, where the newest eruptions are at the wrong end of the series from where geologists would expect them to be, based on the direction of drift of the North American tectonic plate.

Fresh volcanic activity caused by the propagator wake and deeper weakness in the Juan de Fuca could perhaps explain this anomaly, the researchers suggest.

As Juan de Fuca disappears, further research – as well as readings from the EarthScope project and the Cascadia Initiative, which were used in this study – should shed more light on how tectonic plates die, and how they’ve formed the world we live on.

“In many ways, when we’re looking at these things, we’re looking back in time,” seismologist Lara Wagner from the Carnegie Institution for Science, who wasn’t involved in the study, told National Geographic.

“If we don’t understand how those processes work[ed] in the past, where we can see the whole story and study it, then our chances of seeing what’s happening today and understanding how that might evolve in the future are zero.”

See the full article here .

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Founded in the wake of the gold rush by leaders of the newly established 31st state, the University of California’s flagship campus at Berkeley has become one of the preeminent universities in the world. Its early guiding lights, charged with providing education (both “practical” and “classical”) for the state’s people, gradually established a distinguished faculty (with 22 Nobel laureates to date), a stellar research library, and more than 350 academic programs.

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From Caltech: Women in STEM “What is it Like to be a Caltech Seismologist During a Big Quake?” Dr. Jennifer Andrews

Caltech Logo

From Caltech

July 18, 2019
Robert Perkins
(626) 395‑1862
rperkins@caltech.edu

When an earthquake strikes, seismologists at Caltech’s Seismological Laboratory spring into action.

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Dr. Jennifer Andrews

An arm of Caltech’s Division of Geological and Planetary Sciences (GPS), the Seismo Lab is home to dozens of seismologists who collaborate with the United States Geological Survey (USGS) to operate one of the largest seismic networks in the nation.Together, they analyze data to provide the public with information about where the quake occurred and how big it was. That information not only helps first responders, but feeds into the scientific understanding on earthquakes and when and where the next big quicks are likely to strike.

After the two largest Ridgecrest earthquakes on July 4 and 5 (Magnitude 6.4 and 7.1, respectively), Caltech staff seismologist Jen Andrews was part of the Seismo Lab team that rushed to respond. Recently, she described that experience.

Where were you when the earthquakes hit?

For Thursday’s quake, I was at home in my shower. I didn’t even realize at the time that it was a quake. But when I got out and looked at my computer, I saw the report. Then the phone rang, and it was Egill [Hauksson, research professor of geophysics at Caltech], saying it was time to go to work. It was all hands on deck.

For Friday’s quake, I was at the ballet at the Dorothy Chandler Pavilion in Downtown Los Angeles. They’d just finished act 1 and were in intermission, so fortunately no dancers were on stage to be knocked off their feet. I was in the balcony, so the movement I felt was probably amplified by the height (and also the soft sediment beneath Downtown). The chandeliers were swaying, but no one panicked. As soon as I felt it shake, I started counting. We felt it as a roll, so I knew the epicenter wasn’t right beneath us. Once I reached 20 seconds, I knew this was a big earthquake, even bigger than the first one. I immediately got in a taxi and headed straight to campus.

What did you do next?

Here at the Seismo Lab, it’s our responsibility to verify that all of the info we’re putting out about earthquakes—the locations and magnitudes, for example—are correct. We’re responsible for getting info about the origin out within two minutes of the shaking, so we have fully automated systems that send updates to the National Earthquake Information Center right away. All of that happens without anyone touching anything, before we can even get to our desks. But once we get there, we look at the waveforms and make sure that we’re correctly identifying the P and S waves. [During an earthquake, several types of seismic waves radiate out from the quake’s epicenter, including compressional waves (or P-waves), transverse waves (or S-waves), and surface waves.] We also know the speed at which seismic waves should travel, so we can use that to make sure that we’re correctly identifying where the quake originated. It turns out that the automatic systems did a brilliant job of getting most of the information correct.

What is it like to be in the Seismo Lab after a big earthquake?

It’s very busy. There’s a lot of people: seismologists, news reporters, even curious students and people who are on campus who just want to know what’s going on. Meanwhile, we have a lot of issues to deal with: we have seismologists on the phone with state representatives and others speaking to members of the press, while still others are trying to process data coming in from seismometers. Within a few hours of a quake, the USGS tries to figure out who’s going out to the location of the earthquake, and what equipment they’ll be taking. For the Ridgecrest quakes, they did flyovers in a helicopter looking for ruptures, and then sent people on the ground to measure the rupture. They then deployed additional seismometers so that we could get an even clearer picture of any aftershocks.

How long after the earthquake will things stay busy for you?

The media attention relaxes after a few hours or days, but I’m going to be looking at the data we gathered from these quakes for a long time. I was here every day over the holiday weekend and the following week working on it. It could take months or even years for our group to process all the data.

Do you learn more from big earthquakes like these than you do from little ones?

You learn different things. The data will be incorporated into earthquake hazard models, though likely will not make big changes. But these quakes in particular were interesting, as two perpendicular faults were involved. We can study the rupture dynamics, which you can’t resolve in smaller quakes. Also, having two strong quakes caused variations in fault slip and ground motion that will be important to study and understand.

See the full article here .

Earthquake Alert

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Earthquake Alert

Earthquake Network projectEarthquake 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


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Please help promote STEM in your local schools.


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The California Institute of Technology (commonly referred to as Caltech) is a private research university located in Pasadena, California, United States. Caltech has six academic divisions with strong emphases on science and engineering. Its 124-acre (50 ha) primary campus is located approximately 11 mi (18 km) northeast of downtown Los Angeles. “The mission of the California Institute of Technology is to expand human knowledge and benefit society through research integrated with education. We investigate the most challenging, fundamental problems in science and technology in a singularly collegial, interdisciplinary atmosphere, while educating outstanding students to become creative members of society.”

Caltech campus

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From Scientific American: “Oregon Is About to Get a Lot More Hazardous”

Scientific American

From Scientific American

June 29, 2019
Dana Hunter

State leadership is failing its citizens—and there will be a body count.

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Credit: Dale Simonson (CC BY-SA 2.0)

When you live in an area at as much geologic risk as Oregon, you would expect that government officials would maybe, possibly, take those risks seriously. But the people who currently govern Oregon seem quite determined to ignore hazards and let the state languish unprepared.

It’s bad enough that legislators voted this month to allow “new schools, hospitals, jails, and police and fire stations” to be built in areas that will most certainly be inundated in the event of a tsunami. Both parties think it’s a good idea now; I doubt they’ll still be feeling great about locating schools right in the path of rampaging seawater when the big one hits. But short-term economic gain outweighs long-term planning, so here we are. What else can we expect from a statehouse where lawmakers who would rather flee the state than be forced to deal with climate change?

People say they’re willing to accept the risks. However, the state government is now planning to make it far harder for residents to even know what those risks are, because Oregon’s Department of Geology and Mineral Industries (DOGAMI for short) is severely underfunded and will now lose three critically-needed experts on staff as a punishment for going over budget. As if that weren’t bad enough, the governor’s office is considering whether the agency should even continue to exist:

“In a note on the preliminary budget proposal for the agency, the Joint Ways and Means Committee said the Governor’s office would be “evaluating if the Department should continue to exist as an independent or recommendations to abolish and move the individual programs to other entities.”

That drastic of a move could come with big consequences,” Avy said.

“It would be incredibly disruptive to staff and it is likely that some on-going studies would be discontinued,” he said.”Oregon would lose a valued agency and may lose talented staff in our Geological Survey and Services Program which provides a focus on geologic and mineral mapping and natural hazard identification.”

Can we be real for a minute, here? Oregon is a geologically young state in an active subduction zone, located on an ocean that has subduction zones on both sides, which generate ocean-spanning tsunamis on a regular basis. The local subduction zone, plus Basin and Range crustal stretching and faulting, also produces active volcanoes. Many, many volcanoes. Also, too, all of this folding and faulting and uplifting and volcanoing leaves the state terribly landslide prone. This is not a place where you can safely starve your local geological survey of funds, and then shut it down when it needs extra money to identify and quantify the hazards you face.

So if you live in Oregon, or even if you just visit, I’d strongly consider writing a polite but serious missive to Governor Kate Brown, letting her know that it would perhaps be a good idea to look further into the possible repercussions of signing that deplorable tsunami bill (I mean, at least take the schools out of the mix!), and also fully fund DOGAMI rather than further crippling it and then stripping it for parts.

Let’s have a brief tour of Oregon’s geohazards which DOGAMI helps protect us from, then, shall we?

Tsunamis

The Oregon coast is extremely susceptible to tsunamis, both generated from Cascadia and from other subduction zones along the Pacific Ocean. You can see evidence of them everywhere.

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Cascadia subduction zone. This is the site of recurring en:megathrust earthquakes at average intervals of about 500 years, including the en:Cascadia Earthquake of en:1700.

One of the starkest reminders in recent times was the dock that was ripped from the shoreline in Misawa, Japan, in the brutal 2011 Tōhoku Earthquake. The tsunami that sheared it loose and set it afloat also washed ashore in California and Oregon, causing millions of dollars in damage; loss of life in the United States was only avoided due to ample warnings.

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Ocean energy distribution forecast map for the 2011 Sendai earthquake from the U.S. NOAA. Note the location of Australia for scale.

Just over a year later, the dock washed up on Agate Beach, Oregon.

At Agate Beach, homes and businesses are built right in the path of the next Cascadia tsunami. I can’t describe to you the eerie sensation you feel turning away from that dock to see vulnerable structures that will be piles of flooded rubble after the next tsunami hits.

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Residences and businesses on Agate Beach. Even a modest tsunami will cause untold damage to these structures. Credit: Dana Hunter

The people here will have minutes to find high ground after the shaking stops, if that long. There is some high ground nearby, but not much, and perhaps not near enough. Roads will probably be destroyed or blocked in the quake. This is the sort of location the legislature has decided it would be fine to site schools.

Earthquakes

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The stump of a drowned spruce at Sunset Bay, Shore Acres, OR. Lockwood DeWitt for scale. Credit: Dana Hunter

Sunset Bay is the site of one of Oregon’s many ghost forests. Here, a Cascadia earthquake dropped the shoreline about 1,200 years ago, suddenly drowning huge, healthy trees in salt water. At least seven spectacular earthquakes have hit the Oregon coast in the past 3,500 years. It may not sound like much, or often… but look to Japan for the reason why we should take the threat extremely seriously. And Oregon doesn’t just have to worry about Cascadia quakes: the state is full of faults, stretching from north to south and from coast to interior.

Volcanoes

Huge swathes of Oregon are volcanic. As in, recently volcanic. As in, will definitely erupt again quite soon.

Mount Hood, a sibling to Mount St. Helens, is right outside of Portland and last erupted in the mid-1800s. It is hazardous as heck.

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Mount Hood reflected in Trillium Lake, Oregon, United States

But Hood is very, very far from the only young volcano in the state, and evidence of recent eruptions is everywhere. Belknap shield volcano and its associated volcanoes on McKenzie Pass ceased erupting only 1,500 years ago, and the forces that created it are still active today.

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Belknap Crater, Oregon. Cascades Volcano Observatory

Another volcanic center like it could emerge in the near future. And you see here just a tiny swath of the destruction such a volcanic center causes.

You know what you really don’t want to be caught unawares by? A volcano. And even once they’ve stopped erupting, the buggers can be dangerous. Sector collapses, lahars, and other woes plague old volcanoes. You need people who can keep a sharp eye on them. And I’m sorry, but the USGS can’t be everywhere at once. Local volcano monitoring is important!

Landslides and debris flows

If you’re an Oregon resident, you’ll probably remember how bloody long it took to finish the Eddyville Bypass due to the massive landslide that got reactivated during construction. Steep terrain plus plenty of rain equals lots of rock and soil going where we’d prefer it didn’t.

Debris flows and landslides regularly take out Oregon roads, including this stretch on a drainage by Mount Hood.

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Construction equipment copes with damage caused by massive debris flows coming down from Mount Hood. Credit: Dana Hunter

We know from the Oso mudslide just how deadly these mass movements can be. Having experts out there who understand how to map the geology of an area and identify problem areas is critically important, especially in places where a lot of people want to live, work, and play.

Contact the governor’s office and let her know if you don’t think it’s worth letting a budget shortfall torpedo the agency that should be doing the most to identify these hazards and help us mitigate them.

See the full article here .


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Scientific American, the oldest continuously published magazine in the U.S., has been bringing its readers unique insights about developments in science and technology for more than 160 years.

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