ArticlePDF Available

Benefits and Costs of Earthquake Early Warning

Authors:

Abstract

Earthquake early warning (EEW) is the rapid detection of earthquakes underway and the alerting of people and infrastructure in harms way. Public warning systems are now operational in Mexico and Japan, and smaller-scale systems deliver alerts to specific users in Turkey, Taiwan, China, Romania, and the United States. The warnings can arrive seconds to minutes before strong shaking, and a review of early warning applications around the world shows this time can be used to reduce the impact of an earthquake by many sectors of society. Individuals can use the alert time to drop, cover, and hold on, reducing injuries and fatalities, or if alert time allows, evacuate hazardous buildings. Train derailments can be reduced, chemical splits limited, patients in hospitals protected, fire ignitions prevented; workers in hazardous environments protected from fall/pinch hazards, reducing head injuries and/or death. It is impossible to complete an exhaustive list of applications and savings generated by a warning system in the United States, but the benefits clearly outweigh the costs. Three lives saved, two semiconductor plants warned, one Bay Area Rapid Transit train slowed, a 1% reduction in nonfatal injuries, and a 0.25% avoidance of gas-related fire damage would each save enough money to pay for 1 year of operation of a public warning system for the entire U.S. West Coast. EEWcould also reduce the number of injuries in earthquakes by more than 50%.
Benefits and Costs of Earthquake Early
Warning
by Jennifer A. Strauss and Richard M. Allen
ABSTRACT
Earthquake early warning (EEW) is the rapid detection of
earthquakes underway and the alerting of people and infra-
structure in harms way. Public warning systems are now opera-
tional in Mexico and Japan, and smaller-scale systems deliver
alerts to specific users in Turkey,Taiwan, China, Romania, and
the United States. The warnings can arrive seconds to minutes
before strong shaking, and a review of early warning applica-
tions around the world shows this time can be used to reduce
the impact of an earthquake by many sectors of society. Indi-
viduals can use the alert time to drop, cover, and hold on,
reducing injuries and fatalities, or if alert time allows, evacuate
hazardous buildings. Train derailments can be reduced, chemi-
cal splits limited, patients in hospitals protected, fire ignitions
prevented; workers in hazardous environments protected from
fall/pinch hazards, reducing head injuries and/or death. It is
impossible to complete an exhaustive list of applications and
savings generated by a warning system in the United States,
but the benefits clearly outweigh the costs. Three lives saved,
two semiconductor plants warned, one Bay Area Rapid Transit
train slowed, a 1% reduction in nonfatal injuries, and a 0.25%
avoidance of gas-related fire damage would each save enough
money to pay for 1 year of operation of a public warning sys-
tem for the entire U.S. West Coast. EEW could also reduce the
number of injuries in earthquakes by more than 50%.
INTRODUCTION
Earthquake early warning (EEW) can provide a few seconds to
a few minutes of warning prior to ground shaking at a given
location. EEW is used publically, and prototypically, in several
countries around the world, with the aim of reducing the dam-
age, costs, and casualties resulting from an earthquake. Actions
taken in response to the alerts range from personal safety ap-
proaches (such as drop, cover, and hold on) to automated con-
trols and situational awareness. In this article, we provide a
summary of the status of EEW around the world for the non-
specialist and provide examples of cost-saving response actions.
This article is intended for prospective users of early warning,
government officials setting policies, and others outside of the
seismological community, illustrating the broad landscape of
mitigation possibilities that early warning provides.
Unlike seismic retrofits, where a direct costbenefit of
damage reduction is readily made, early warning mitigates
many hidden costs that are difficult to monetarily delineate but
are ultimately crucial for long-term resiliency postrupture. At-
tempts to calculate potential annual loss reductions specifically
resulting from EEW actions are difficult, due to the fact that
few outside of the seismological community are aware of the
technical capabilities. For that reason, we here illustrate known
possible savings from EEW and show that EEW can aid in mit-
igation for broad-risk categories, including reducing train de-
railments and chemical spills, isolating radioactive sources,
protecting patients, reducing fall/pinch hazards, and reducing
head injuries and/or death. Though we cannot a priori deter-
mine which individual risks will occur in any given earthquake,
the savings are so significant and so diverse that a robust EEW
system would be a good return on investment. Saving three
individual lives, or alerting two semiconductor plants, or pre-
venting the derailment of one Bay Area Rapid Transit (BART)
train, would each individually save enough money to pay for
one year of operation of the system for the entire U.S. West
Coast. The savings are not limited to just the risks outlined in
this article, even though these alone would be sufficient to jus-
tify the costs of a warning system.
EARTHQUAKE EARLY WARNING
EEW, like warnings for other natural disasters such as torna-
does, hurricanes, and tsunamis, is a forecast of activity that is
imminent. However, unlike hurricane warnings, which can
come days in advance of severe weather, or tsunami warnings,
which build over the course of a few minutes to a few hours
before the tsunami makes landfall, earthquakes have a much
shorter lead time, shorter even than a funnel cloud that starts
spiraling toward the earth. A warning could be just seconds.
This short warning time is a product of the physical proc-
ess of an earthquake rupture. A schematic regional EEWsystem
doi: 10.1785/0220150149 Seismological Research Letters Volume 87, Number 3 May/June 2016 765
is outlined in Figure 1. In essence, EEW uses seismometers to
detect the first signature of an earthquake (Pwave, yellow arc),
to process the waveform information, and to forecast the in-
tensity of shaking that will arrive after the Swave (red arc). For
local EEW installations, the Pwave is detected onsite (i.e., at
the user location), and the difference between the P- and
S-wave arrival times defines the maximum alert time. For
regional networks, the Pwaves are detected by sensors closest
to the epicenter, and estimates are immediately relayed to
earthquake alerting applications (TV, smartphones, radio,
etc.) to provide businesses, citizens, and emergency responders
more advance knowledge of the expected arrival and intensity
of shaking at their location.
Heaton et al. (1985) proposed a model for a computerized
seismic alert network, which laid the groundwork for the EEW
systems in place around the world today. They proposed that
this computer-backed system could protect hazardous chemi-
cals, initiate electrical isolation, and protect fixed-rail transport
systems, hospitals, fire stations, etc. These ideas have now been
tested, and some are operational for several EEW systems
globally.
EEW AROUND THE WORLD
The U.S. Geological Survey (USGS), in partnership with the
University of California at Berkeley, the California Institute of
Technology, and the University of Washington, with support
from the Gordon and Betty Moore Foundation, created an
EEW initiative called ShakeAlert (Fig. 2). This system incor-
porates existing sensors from the California Integrated Seismic
Network and the Pacific Northwest Seismic Network and
sends alerts to a cadre of test usersover 50 groups including
the BART, the cities of San Francisco and Los Angeles, Boeing,
and Intel. It is currently an end-to-end demonstration system,
and conversion to a more redundant and robust production
prototype is underway, with a view toward limited rollouts
Figure 1. Representative illustration of the regional earthquake
early warning concept. Provided by Erin Burkett (U.S. Geological
Survey [USGS]) and Jeff Goertzen (Orange County Register).
Figure 2. (a) ShakeAlert UserDisplay showing a snapshot of
the warning from a simulation of the 1989 Loma Prieta earth-
quake. The red star is the epicentral location, and the yellow
and red circles are the Pand Swavefronts. The key alert infor-
mation is the shaking intensity and time of the Swave (repre-
senting onset of strong shaking) at the users location. This is
the warning at University of California, Berkeley, as indicated by
the location of the blue house icon. The UserDisplay is a java-
based application that can run on any computer and is available
to ShakeAlert test users. (b) MyEEW smartphone app for the
same scenario event. An audible alert with the shaking intensity
at the users location is first received automatically (top of left
screenshot). When the user touches the notification, a simple
screen shows the expected shaking intensity at the userslo-
cation and counts down until the S-wave arrival (middle screen-
shot). By touching the Maplink (top right) a screen with more
information is displayed showing a map of the event and user
location and the magnitude, in addition to the shaking intensity
and countdown (right screenshot).
766 Seismological Research Letters Volume 87, Number 3 May/June 2016
in the near future. The system currently combines single-sta-
tion algorithms (OnSite, Bose et al., 2012), with multistation
approaches (ElarmS, Serdar Kuyuk et al., 2013; Virtual Seis-
mologist, Cua et al., 2009) to provide the quickest and most
accurate alerts possible. Speed is critical for the U.S. West
Coast, because fault lines and their associated hazards coincide
with areas of high population density. Learning from other sys-
tems in operation today worldwide, the ShakeAlert project also
augments the traditional seismic results with Global Position-
ing System (Grapenthin et al., 2014a,b) and Bayesian ap-
proaches (Bose et al., 2014).
ShakeAlert successfully alerted test users for both the 2014
M6.0 South Napa earthquake (Brocher et al., 2015;Dreger
et al., 2015) and the 2014 M5.1 La Habra earthquake (Hauks-
son et al., 2014). The BART system in San Francisco activated
its hazard mitigation protocol, which triggers trains to auto-
matically slow or stop, depending on predetermined condi-
tions. However, no trains were running at 3:20 a.m. when the
Napa earthquake occurred.
Mexico is home to the oldest public EEW system in the
world. The effort began in 1991 with Mexicos strong-motion
accelerometer network, which monitored large subduction
zone earthquakes off of the western coast and alerted citizens
of Mexico City that heavy shaking was on its way. El Sistema
de Alerta Sísmica Mexicano (SASMEX) now sends alerts to
Mexico City, Oaxaca, Acapulco, Chilpancingo, and most re-
cently Morelia via TV, AM/FM radio, National Oceanic and
Atmospheric Administration weather radios, and the Mexican
Hazard Alert System (Espinosa-Aranda and Petel, 2014). In
2009, the 230 registered users for the system were surveyed,
and 91% respondents considered EEW a useful tool for their
institution as a civil protection measure and maintain a positive
view of the system as a whole (Suarez et al., 2009). The city of
Acapulco received 24 s of warning from SASMEX for the
M7.2 Guerrero earthquake on Good Friday, 2014. Mexico
City (situated almost 400 km away) was provided more than
68 s of early warning (see Data and Resources).
The Japanese EEW system successfully alerted several mil-
lion people near the epicenter, providing 1520 s of early warn-
ing, for the 2011 M9.0 Tohoku-Oki earthquake and tsunami
(Fujinawa and Noda, 2013). Ninety percent of the people
alerted were able to take action in response to the warning to
aid in their survival; this high rate of effectiveness was a result
of EEW education and training (Fujinawa and Noda, 2013).
Post-earthquake surveys indicated that almost 80% of respon-
dents were alerted by the EEW and were prompted to take
action. About 82%91% of respondents (the rate varies de-
pending on the survey group) thought favorably of the EEW
system. The system has been in operation since October 2007
and is arguably the most advanced EEW system in the world.
The alerts and automated responses are tied into the high-
speed rail infrastructure, schools, and businesses, and many pri-
vate sector groups provide value-added services to augment the
public alerts provided by the Japan Meteorological Agency.
In June 2015, the Chinese government approved a project
to construct EEW systems in four large regions of the country:
north China, southeast Coastal, the northsouth seismic belt,
and northwestern Xinjiang. The project builds on demonstra-
tions systems that have been running in the Capitol City Zone,
Lanzhou City, and the Fujian Province for several years. The
project will deploy 2000 broadband and strong-motion seismic
stations, an additional 3000 strong-motion sensors, and it
plans to start delivering warning by 2020.
The Seismic eArly warning For EuRope (SAFER) and
Real-time EArthquake risK reducTion (REAKT) projects in-
volved many institutions in Europe funded to explore the pos-
sibility of warning across Europe. A system in Bucharest, above
the deep Vrancea subduction earthquakes, provides a prelimi-
nary shake map to a nuclear research facility within 45sof
the origin time (Zschau et al., 2009). A regional EEW system is
undergoing testing in the Irpinia region east of Naples and
could provide 816 s warning to the city (Zollo et al., 2009).
EEW was implemented in Istanbul in 2002 in response to the
1999 earthquakes. The system provides traffic control for the
Fatih Sultan Mehmet suspension bridge and Marmaray tube
tunnel across the Bosporus Straits as well as the regulator stations
and natural gas valves for the Istanbul Natural Gas Distribution
Network (Alcik et al.,2009). Finally, a demonstration warning
system is operational in Switzerland, and alerts are being deliv-
ered to nuclear power plants (Cauzzi et al.,2014).
Other groups worldwide are also working toward better
earthquake response through early warning. Taiwan is cur-
rently testing its own EEW system, with alerts sent to users in
the railway and disaster-prevention sectors. Hsiao et al. (2009)
discussed that, between 2001 and 2009, 225 alerts were gen-
erated for events greater than M4.5 both inland and off the
coast, with a latency time of 20 s after the origin time of the
earthquake (Hsiao et al., 2009). Israeli Seismic Network scien-
tists are working with University of California, Berkeley, to
implement the Earthquake Alarms Systems (ElarmS) algorithm
in Israel. The system is running in both real time and in real-
time playback modes with a new visualization tool called
ElarmS Visualization System (ElViS). As the technology gains
deeper global penetration, inhabitants of other high-fault-haz-
ard zones will begin looking toward EEW as a possible solution
to their own risk exposure.
HAZARD MITIGATION AND EEW
Risk exposure refers to the potential loss of life, personal injury,
economic injury, and property damage resulting from natural
hazards by assessing the vulnerability of people, buildings, and
infrastructure to natural hazards (Federal Emergency Manage-
ment Agency [FEMA], 2014). EEW is a tool that can reduce
risk through personal preparedness, situational awareness, and
automated controls. Personal preparedness (including drop,
cover, and hold on) prevents the most common injuries during
an earthquakethose resulting from falling and flying
objectsand increases the safety of the population, particularly
in schools and public places (Zschau et al., 2009;Earthquake
Country Alliance, 2014a). The elderly and persons with dis-
abilities are disproportionally affected by natural disasters
Seismological Research Letters Volume 87, Number 3 May/June 2016 767
and, as such, could most directly benefit from early warnings
and a clear preparedness plan (Brittingham and Wachtendorf,
2013;Earthquake Country Alliance, 2014b). Situational
awareness provided by EEW allows civil protection authorities
advance notice for more rapid and efficient mobilization and
adaptable response (Zschau et al., 2009). Awareness of the lo-
cation, extent, and intensity of the coming shaking allows
responders to assess the impact and their potential next steps.
Protecting critical structures (e.g., hospitals, air traffic con-
trol facilities, schools, and businesses) through EEW-automated
controls allows them to remain operational and is crucial for
long-term resiliency. Earthquake-induced secondary effects
(e.g., fires and industrial accidents) are reduced through the
application of computer-initiated controls that can safeguard
operations, transport systems, and lifelines, thus allowing social
facilities to return to normal as soon as possible (Heaton et al.,
1985;Zschau et al., 2009).
Hospitals
Since 2003, EEW actions in a hospital setting have been imple-
mented and tested at the National Hospital Organization Dis-
aster Medical Center in Japan. Stopping surgery safely and
temporarily disconnecting ventilator tubes are easy and highly
effective ways to prevent fatal errors in the emergency room
during an earthquake (Horiuchi, 2009). Opening doors to pro-
vide egress routes, closing blinds/curtains to minimize glass
debris, and raising awareness of falling hazards aid in reducing
risk to both staff and patients. Securing radioactive sources and
bringing equipment into a safe mode can also effectively pro-
tect people in radiography departments. In the operating room,
staff can stabilize a patient quickly and easily in response to an
early warning. Hazard mitigation plans involving EEW for hos-
pitals must consider the proximity of their staff to the actions
they need to implement as well as the time required to com-
plete said actions for each department independently.
Schools
Schools are another sector where staffs need to protect them-
selves as well as a vulnerable population. General protective mea-
sures such as closing curtains to prevent injuries from broken
glass, opening classroom doors to ensure egress, and raising aware-
ness of falling hazards are applicable for schools just as it is for
hospitals. Many schools in Japan are equipped with EEW,and
installation in all schoolsisunderway(Fujinawa and Noda,
2013). Schools receive arrival time and seismic strength informa-
tion and forward alerts to loudspeakers, announcement systems,
and TV receivers in classrooms (Motosaka and Homma, 2009).
On 14 June 2008, the staff of the junior high school in Shiroishi
City (110 km from epicenter of the M6.9 IwateMiyagi Nairiku
earthquake, Japan) took action with 21 s of early warning,
allowing 102 students (including 10 disabled students) to drop,
cover, and hold on to avoided injury.
Police, Fire, and Other Emergency Response Groups
Police, fire, and other emergency-response groups may be in-
volved in rescue efforts and cleanup operations that may be
compromised by aftershocks. Opening firehouse bay doors
in advance of shaking to prevent jamming and activating
municipal Emergency Operations Centers before communica-
tions are lost aids response. Fire and Police departments also
benefit from situational awareness of the forecasted severity of
the shaking. Often, first responders rely on mutual aid from
outside areas to augment their efforts. Simply knowing in ad-
vance which municipalities are going to be affected and which
ones could be called upon for assistance helps to streamline the
process after the event, particularly if communications become
disabled.
Elevators
During heavy shaking, an elevator car and counterweight can
move out of alignment becoming jammed. Elevator stoppage
through earthquake detection or early warning protects the
occupants and system. Almost half of the elevators Otis main-
tains in Japan are already equipped with earthquake detectors,
which return the elevators to the ground floor when strong
shaking is detected so passengers can exit (Layne, 2011). Some
16,700 elevators performed an emergency shutdown during the
Tohoku-Oki earthquake in 2011, which meant that first
responders did not have to devote time and resources to rescue
any trapped or injured passengers (Layne, 2011). Other eleva-
tors are linked to EEW systems, allowing safe shutdown before
strong shaking starts. further protecting occupants.
Manufacturing
The best-documented example of manufacturing resilience due
to EEW comes from the OKI semiconductor factory in Miyagi
Prefecture, Japan. Early warning alerts trigger isolation of the
hazardous chemical systems and prompt the lithography tables
to move to a safe position in advance of shaking (Allen et al.,
2009). Several automated controls in a manufacturing context
reduce cascading failures, such as shutting off gas valves to pre-
vent secondary hazards and protection of personnel. The Horia
Hulubei National Institute of Physics and Nuclear Engineering,
Romania, prevents cascading failure by automatically securing
their nuclear source (Ionescu et al.,2007).
Other Lifelines
Predetermined risk scenarios used in conjunction with EEW
(Pittore et al., 2014) provide lifelines and emergency respond-
ers a framework of immediate estimates of damage types and
locations. Municipalities could assess activation of mutual-aid
deployment to/from neighboring cities. The Salvation Army
could predetermine which divisions would be impacted under
various earthquake scenarios and implement planning and re-
sponse accordingly (John McKnight, Director of Emergency
and Disaster Services the Salvation Army, personal comm.,
March 2015). Real-time seismic motions for lifelines such as
dams could be compared with predetermined models to inform
disaster prevention actions in the aftermath of an earthquake
(Pagano and Sica, 2012). These actions include the monitoring
of earthquake-induced effects, characterization of dam safety
conditions, and alarming those nearby to reduce exposure.
768 Seismological Research Letters Volume 87, Number 3 May/June 2016
Alerts can also trigger rapid checks of dam safety conditions
with regard to possible collapse scenarios.
Transportation Systems
Transportation systems including airports, railways, and road-
ways are important to safeguard with EEW, not only to protect
passengers but also to ensure the smooth flow of goods needed
for recovery efforts in and out of the impacted area. For air-
ports, personal safety within the terminal would center on
drop, cover, and hold on. Outside the terminal, air traffic con-
trollers with the situational awareness of a coming event can
better manage air traffic. Planes can stop taxiing; baggage han-
dlers can get away from hazardous situations; and planes on
approach can go around until the shaking is over and the run-
ways have been inspected.
The BART in San Francisco is the first transportation sys-
tem in the United States with an end-to-end early warning sys-
tem. BART uses both the ShakeAlert system and on-track
accelerometers (set to trigger at a defined threshold of 0:1g)
to slow and/or stop the trains in safe configurations. On
24 August 2014, the M6.0 South Napa earthquake shook
the Bay Area at 3:20 a.m. The BART operations center in
Oakland, California, received 8 s of early warning before
the S-wave arrival. The system preformed as desired; however,
no actions were ultimately taken, because no trains were run-
ning at the time.
The Shinkansen high-speed trains in Japan have an
impressive track record of performance in earthquakes, due
to engineering controls for the trains and EEW. No passengers
or staff were injured during the Great Tohoku earthquake in
2011, and only one train running in test mode derailed. The S-
wave detector at Cape Kinkazan triggered (120 Gal threshold),
and the emergency brakes were automatically applied to all 33
trains. The first tremors hit the trains nearest the epicenter in
Sendai 912 s after the alert, whereas the strongest shaking
took another minute to arrive (Shimamura and Keyaki, 2013).
Railways also benefit from warnings that arrive too late to
fully complete automated controlsas seen during the 2004
Niigataken Chuetsu earthquake. Train Toki 325 traveled into
the affected region and was jolted by the Pwave without warn-
ing. It received an alarm from the Compact Earthquake De-
tection and Alarm System (UrEDAS) 0.6 s later, and the power
supply was interrupted to slow the train. The driver applied the
emergency brake 1.5 s later after recognizing the Compact
UrEDAS alarm and 1.2 s later the heaviest shaking begannot
nearly enough time to fully slow the train from 204 km=hto a
safe speed. Although the train did ultimately derail, the EEW
provided crucial 1.2 s to slow the train before peak shaking and
thus the derailment was noncatastrophic (Nakamura, 2008).
Drivers on roadways may be unable to identify the shaking
as coming from an earthquake, so alerts on signage can bring
awareness and prompt actions such as preventing motorists
from entering bridges and tunnels. The California Department
of Transportation (Caltrans) made use of an EEW system to
protect workers during the small but hazardous (due to all the
unstable debris) aftershocks of the Loma Prieta earthquake.
The radio receiver at the Caltrans headquarters at the damaged
Cypress St. section of the I-880 freeway in Oakland received a
20 s warning before the M4.5 aftershock on 2 November
1989. In the first six months of operation, the system generated
triggers for all twelve M>3:7aftershocks for which trigger
documentation is preserved, did not generate triggers on any
M3:6aftershocks, and produced only one false trigger (Ba-
kun et al., 1994).
COSTS AND BENEFITS
A fully implemented public warning system for the West Coast
of the United States would cost $16.1 million per year above
the current USGS funding levels for the Earthquake Hazards
Program (see Fig. 3), which would finance personnel to run the
system, ongoing improvements and upgrades for the instru-
mentation, and continuing research and development (R&D)
to maintain state-of-the-art alert methods. This does not in-
clude one-time costs of $38 million to increase the station den-
sity of the existing networks and upgrade old seismometers to
current standards (Burkett et al., 2014;Given et al., 2014).
The costs are well defined. The savings are envisioned
through a varied landscape of possibilities. Previous costben-
efit studies in California were assembled before the Internet
and trust in automated controls (Holden, 1989). Now society
not only counts on automation as a part of daily life, but we
have a wealth of information from other countries and their
experience with early warning to inform our choices.
In both the 1989 Loma Prieta and 1994 Northridge earth-
quakes, more than 50% of the injuries were caused by falls and
falling hazards (Shoaf et al., 1998). This includes all the injuries
caused by nonstructural hazards such as falling ceiling tiles,
lighting fixtures, bookcases, and so on. If everyone received
a few seconds of warning, and if everyone dropped, took cover,
and held on, then early warning could reduce the number of
injuries by more than 50% in future earthquakes. Porter et al.
(2006) estimated the cost of injuries in the Northridge earth-
quake to be $1.82.9 billion (in 2005 equivalent dollars), so
EEW could provide $11.5 billion in savings in a future similar
event.
The cost of injuries represents 3%4% of the estimated
$50 billion in direct capital losses and direct business interrup-
tion losses. Taking this 3%4% ratio as indicative of future
events, the economic value of future earthquake injuries
the amount that the U.S. government would deem appropriate
to expend to prevent all such injuriesis on the order of $200
million per year (in 2005 dollars, based on the $4.4 billion
expected annual loss due to earthquakes each year (Porter et al.,
2006). The cost of EEW is $16.1 million per year; a mere 1%
reduction of the injuries in the Northridge earthquake is equiv-
alent to the cost of the system for 1 year (see Fig. 3).
According to FEMAs costbenefit methodology for haz-
ard mitigation projects, the current value of a statistical life in
the United States is $6.6 million (see Fig. 3). Therefore, it
stands to reason that if three deaths per year, on average,
are avoided through implementation of EEW, the system pays
Seismological Research Letters Volume 87, Number 3 May/June 2016 769
for itself (John D. Schelling, Interim Mitigation & Recovery
Section Manager Washington Military Department, Emer-
gency Management Division, testimony before the United
States House Committee on Natural Resources, Subcommittee
on Energy and Mineral Resources, 10 June 2014).
One of the best documented returns on investment for
private industry is that of the OKI semiconductor factory in
Miyagi Prefecture, which experienced $15 million U.S. in losses
due to fire, equipment damage, and loss of productivity in two
moderate earthquakes (M7.1 and 6.4) in 2003. They invested
$600,000 U.S. in retrofits and EEW controls to automatically
shut down hazardous chemical systems and manipulate sensi-
tive equipment into a safe position. In two similar subsequent
earthquakes, the losses were reduced to only $200,000 U.S. (Al-
len et al., 2009), a savings of $7.7 million U.S. per earthquake
(see Fig. 3). There are over 1000 semiconductor companies in
California alone (see Data and Resources), thus protecting just
two of them annually with EEW and retrofits would pay for the
system as a whole.
The Reliability Engineering group for the BART analyzes
passenger flow models for the entire system. Taking Tuesday,
Wednesday, and Thursday averages from 7:00 a.m. to 6:30 p.m.,
3040 trains are moving at any given time, totaling 300400
individual cars in motion (Kevin Copley, Manager of Com-
puter Systems Engineering at BART, personal comm., March
2015). Preventing derailment of one single train during the
workday could save 10 individual rail cars. At a total project
cost of $3.3 million per car, that translates to a possible $33
million of savings, equivalent to 2 years of operation of Shake-
Alert (see Fig. 3). This calculation considers just the cost for
train-car replacement alone; the cost savings of avoiding inju-
ries to passengers would increase the benefit substantially. As an
example, the 12 May 2015 derailment of the Philadelphia,
Pennsylvania, Amtrak train number 188 resulted in 8 fatalities
and 200 injuries at a cost in excess of $9.2 million (National
Transportation Safety Board, 2015).
Other transportation sectors have similarly large assets to
protect. The cost of a single modern airplane, such as the Air-
bus A318 with a list price of $74 million (see Data and Re-
sources), is well in excess of the cost of a 10-car BART
train. Protecting such large capital investments though the use
of an early warning system to divert planes on approach during
heavy shaking could reduce the risk of a costly crash, not only
in the monetary terms for the plane itself, but also for the crew
and passengers who would remain safely on board.
In both the United States and Japan, fire was the single
most destructive seismic agent of damage in the twentieth cen-
tury (Scawthorn et al., 2005). For an M7 earthquake on the
Hayward fault, the loss estimates to fire are around $50 billion
(Charles Scawthorn, after Fires and the Hayward Earthquake
Workshop, written communication, October 2014). This loss
quantity only considers the residential and building replace-
ment value. The total number of ignitions is estimated to be
around 1000, with 25% of those stemming from gas connec-
tions and underground lines. Some gas valves during the 1994
Northridge earthquake had seismic shut-offs installed, which
helped reduce ignition (Scawthorn et al., 2005); implementa-
tion of EEW-based shut-offs would be able to boost their effect.
If only one quarter of 1% (0.25%) of the damage due to gas-
related ignitions could be prevented by early warning, a savings
of $31.25 million could be realized (see Fig. 3).
Figure 3. Comparison of the cost of running a U.S. West Coast early warning system (orange) with some of the identifiable savings
(green). All disks are scaled relative to the white disk representing $10 million.
770 Seismological Research Letters Volume 87, Number 3 May/June 2016
CONCLUSION
Implementation of EEW systems is increasing around the
world: Mexico, Japan, Europe, Israel, Taiwan, China, and now
the United States, all have systems and provide alerts to users.
There are now real-life demonstrations of the benefits of EEW.
Building occupants in Mexico are able to evacuate structures
that are likely to collapse in an earthquake. School children
took shelter during the 2011 Tohoku-Oki earthquake. Trains
can be slowed to reduce the risk of derailment. Factory workers
using heavy machinery can reduce crush injuries or pinch haz-
ards with advanced notice of shaking. This is not an exhaustive
list, but rather a snapshot of the critical lifelines and industries
that could benefit from early warning.
EEW is not a panacea, nor a replacement for robust infra-
structure or seismic retrofits. EEW is a tool that augments risk
mitigation efforts both before and after a rupture. The benefits
clearly outweigh the costs. Three lives saved, two semiconduc-
tor plants warned, one BARTtrain slowed, a 1% reduction in
nonfatal injuries, a 0.25% avoidance in gas-related fire damage,
could each in theory save enough money to pay for one year of
operation of the system for the entire U.S. West Coast. EEW
could also reduce the number of injuries in earthquakes by
more than 50%.
These specific examples represent just the beginning of
what will be a much longer list of possible applications for
EEW.AsEEW technology becomes better known and under-
stood, as EEW system are further implemented around the
world, and as our world becomes ever more interconnected
and automated, more and more businesses will be able to iden-
tify appropriate applications to safeguard their own assets. It
therefore seems clear that the savings substantially outweigh
the costs of implementing EEW.
DATA AND RESOURCES
The video of the early warning alert can be found at https://
www.youtube.com/watch?v=f3zGvs_hjdo (last accessed Feb-
ruary 2016). The semiconductor companies in California list-
ing can be found at http://semiconductorcompanies.com
(last accessed March 2015). Airbus A318 listing can be found
at http://www.airbus.com/presscentre/pressreleases/press-
release-detail/detail/new-airbus-aircraft-list-prices-for-2015/
(last accessed April 2015).
ACKNOWLEDGMENTS
ThisworkwasfundedbytheGordonandBettyMooreFoun-
dation through Grant Number GBMF3024 to University of
California, Berkeley, and the U.S. Geological Survey (USGS)/
National Earthquake Hazards Reduction Program Award
G12AC20348. The authors would also like to thank Kevin
Copley at Bay Area Rapid Transit (BART), John McKnight
of The Salvation Army, and Margaret Vinci at Caltech for
their insight.
REFERENCES
Alcik, H., O. Ozel, N. Apaydin, and M. Erdik (2009). A study on warning
algorithms for Istanbul earthquake early warning system, Geophys.
Res. Lett. 36, L00B05, doi: 10.1029/2008GL036659.
Allen, R. M., P. Gasparini, O. Kamigaichi, and M. Bose (2009). The sta-
tus of earthquake early warning around the world: An introductory
overview, Seismol. Res. Lett. 80, 682693.
Bakun,W.H.,F.G.Fischer,E.G.Jensen,andJ.Vanschaack(1994).
Early warning system for aftershocks, Bull.Seismol.Soc.Am.
84, 359365.
Bose, M., R. M. Allen, H. Brown, G. Gua, M. Fischer, E. Hauksson, T.
Heaton, M. Hellweg, M. Liukis, D. Neuhauser, et al. (2014). CISN
ShakeAlert: An earthquake early warning demonstration system for
California, in Early Warning for Geological Disasters, F. Wenzel and
J. Zschau (Editors), Springer, Berlin, Germany, 4969.
Bose, M., T. Heaton, and E. Hauksson (2012). Rapid estimation of earth-
quake source and ground-motion parameters for earthquake early
warning using data from a single three-component broadband or
strong-motion sensor, Bull. Seismol. Soc. Am. 102, 738750.
Brittingham, R., and T. Wachtendorf (2013). The effect of situated access
on people with disabilities: An examination of sheltering and tem-
porary housing after the 2011 Japan earthquake and tsunami,
Earthq. Spectra 29, S433S455.
Brocher, T. M., A. S. Baltay, J. L. Hardebeck, F. F. Pollitz, J. R. Murray, A.
L. Llenos, D. P. Schwartz, J. L. Blair, D. J. Ponti, J. J. Lienkaemper,
et al. (2015). The Mw6.0 24 August 2014 South Napa earthquake,
Seismol. Res. Lett. 86, 309326.
Burkett, E. R., D. D. Given, and L. M. Jones (2014). ShakeAlertAn
Earthquake Early Warning System for the United States West Coast,
U.S. Department of the Interior, U.S. Geological Survey, factsheet
2014-3083.
Cauzzi, C., Y. Behr, J. Clinton, S. Wiemer, J. Wössner, M. Caprio, G.
Cua, T. Le Guenan, J. Douglas, and S. Auclair (2014). Final report
on the feasibility study and initial EEW implementation efforts for
nuclear power plants in Switzerland, 28 pp.
Cua, G., M. Fischer, T. Heaton, and S. Wiemer (2009). Real-time per-
formance of the virtual seismologist earthquake early warning algo-
rithm in southern California, Seismol. Res. Lett. 80, 740747.
Dreger, D. S., M. Huang, A. Rodgers, T. Taira, and K. Wooddell (2015).
Kinematic finite-source model for the 24 August 2014 South Napa,
California, earthquake from joint inversion of seismic, GPS, and
InSAR data, Seismol. Res. Lett. 86, 327334.
Earthquake Country Alliance (2014a). How to Protect Yourself During an
Earthquake,http://www.earthquakecountry.info/dropcoverholdon/
#whattodo (last accessed November 2015).
Earthquake Country Alliance (2014b). Earthquake Preparedness Guide
for People with Disabilities and Other Access or Functional Needs,
http://www.earthquakecountry.org/downloads/ShakeOut_Earthquake_
Guide_Disabilities_AFN.pdf (last accessed November 2015).
Espinosa-Aranda, J. M., and E. Petel (2014). Earthquake alerts: From
black magic to science and engineering, Third International
Conference on Earthquake Early Warning, UC Berkeley, Berkeley,
California, 35 September 2014.
Federal Emergency Management Agency (FEMA) (2014). Hazard mit-
igation planning risk assessment.
Fujinawa, Y., and Y. Noda (2013). Japans earthquake early warning sys-
tem on 11 March 2011: Performance, shortcomings, and changes,
Earthq. Spectra 29, S341S368.
Given, D. D., E. S. Cochran, T. H. Heaton, E. Hauksson, R. M. Allen, P.
Hellweg, J. Vidale, and P. Bodin (2014). Technical implementation
plan for the ShakeAlert production systemAn Earthquake Early
Warning system for the West Coast of the United States, U.S. Geol.
Surv. Open-File Rept. 2014-1097, 25 pp, doi: 10.3133/ofr20141097.
Grapenthin, R., I. Johanson, and R. M. Allen (2014a). The 2014 Mw6.0
Napa earthquake, California: Observations from real-time GPS-en-
hanced earthquake early warning, Geophys. Res. Lett. 41, 82698276.
Seismological Research Letters Volume 87, Number 3 May/June 2016 771
Grapenthin, R., I. A. Johanson, and R. M. Allen (2014b). Operational
real-time GPS-enhanced earthquake early warning, J. Geophys. Res.
119, 79447965.
Hauksson, E., A. Guarino, K. Hutton, N. Scheckel, R. Graves, K. Hudnut,
L. Jones, and K. Feltzer (2014). CISN/SCSC Executive Summary,
http://www.scsn.org/2014lahabra.html (last accessed December 2014).
Heaton, T. H., N. Series, and N. May (1985). A model for a seismic
computerized alert network, Science 228, 987990.
Holden, R. (1989). Technical and Economic Feasibility of an Earthquake
Early Warning System in California, Special Publication: California
Division of Mines and Geology, Sacramento, California.
Horiuchi, Y. (2009). Earthquake early warning hospital applications,
J. Disast. Res. 4, 237241.
Hsiao, N.-C., Y.-M. Wu, T.-C. Shin, L. Zhao, and T.-L. Teng (2009).
Development of earthquake early warning system in Taiwan, Geo-
phys. Res. Lett. 36, L00B02, doi: 10.1029/2008GL036596.
Ionescu, C., M. Bose, F. Wenzel, A. Marmureanu, A. Grigore, and G. Mar-
mureanu (2007). Early warning system for deep Vrancea (Romania)
earthquakes, in Earthquake Early Warning Systems, P. Gasparini, G.
Manfredi, and J. Zschau (Editors), 343349.
Layne, R. (2011). Japan Quake: How Otis Rose to the Challenge, Bloom-
berg Business, 24 March, http://www.bloomberg.com/bw/magazine/
content/11_14/b4222020340761.htm (last accessed February 2016).
Motosaka, M., and M. Homma (2009). Earthquake early warning system
application for school disaster prevention, 4, no. 4, 229236.
Nakamura, Y. (2008). First actual P-wave alarm systems and examples of
disaster prevention by them, 14th World Conference on Earthquake
Engineering, Beijing, China, 1217 October 2008.
National Transportation Safety Board (2015). Preliminary Rept,http://
www.ntsb.gov/investigations/AccidentReports/Pages/DCA15MR010_
Preliminary.aspx (last accessed February 2016).
Pagano, L., and S. Sica (2012). Earthquake early warning for earth dams:
Concepts and objectives, Nat. Hazards 66, 303318.
Pittore, M., D. Bindi, J. Stankiewicz, A. Oth, M. Wieland, T. Boxberger,
and S. Parolai (2014). Toward a loss-driven earthquake early warn-
ing and rapid response system for Kyrgyzstan (central Asia), Seismol.
Res. Lett. 85, 13281340.
Porter, K., K. Shoaf, and H. Seligson (2006). Value of injuries in the
Northridge earthquake, Earthq. Spectra 22, 555563.
Scawthorn, C., J. M. Eidinger, and A. J. Schiff (Editors) (2005). Fire Fol-
lowing Earthquake, ASCE Publications, 352 pp.
Serdar Kuyuk, H., R. M. Allen, H. Brown, M. Hellweg, I. Henson, and
D. Neuhauser (2013). Designing a network-based earthquake early
warning algorithm for California: ElarmS-2, Bull. Seismol. Soc. Am.
104, 162173.
Shimamura, M., and T. Keyaki (2013). How Japans bullet trains survived
the 2011 Great Tohoku earthquake, Proc. Eastern Asia Soc. Trans-
port. Stud. 9, 49.
Shoaf, K. I., L. H. Nguyen, H. R. Sareen, and L. B. Bourque (1998).
Injuries as a result of California earthquakes in the past decade,
Disasters 22, 218235.
Suarez, G., D. Novelo, and E. Mansilla (2009). Performance evaluation of
the seismic alert system (SAS) in Mexico City: A seismological and a
social perspective, Seismol. Res. Lett. 80, 707716.
Zollo, A., G. Iannaccone, M. Lancieri, L. Cantore, V. Convertito, A.
Emolo, G. Festa, F. Gallovič, M. Vassallo, C. Martino, et al.
(2009). Earthquake early warning system in southern Italy: Method-
ologies and performance evaluation, Geophys. Res. Lett. 36, L00B07,
doi: 10.1029/2008GL036689.
Zschau, J., P. Gasparini, and G. Papadopoulos (2009). Seismic Early Warn-
ing for Europe Final Rept,http://www.amracenter.com/SAFER/doc/
dissemination/SAFER_Final_Report.pdf (last accessed February 2016).
Jennifer A. Strauss
Richard M. Allen
Berkeley Seismological Laboratory
University of California, Berkeley
215 McCone Hall, Number 4760
Berkeley, California 94720 U.S.A.
jastrauss@berkeley.edu
Published Online 23 March 2016
772 Seismological Research Letters Volume 87, Number 3 May/June 2016
... The hope is to reduce seismic risk by giving the public a valuable window (from few to dozens of seconds) to get to safety. PEEW systems could reduce the number of injuries from earthquakes by more than 50% if everyone received warnings and took protective action (Strauss and Allen, 2016). ...
... Over the past decade, PEEW systems have notably been set up at local or national levels in Japan, Taiwan, Mexico, South Korea, and the United States (Cremen and Galasso, 2020). PEEW systems have become a public expectation in many regions where earthquake risk is significant (Becker et al., 2020;Dallo and Marti, 2021), yet their development is hampered by the implementation and operating costs of such systems (Strauss and Allen, 2016). ...
... Even though it is a user demand, whether safety tips should be included in the warning-and in what format-is still an open debate. It is unclear if it will confuse the message or give an incentive to act, and recommendations may vary from country to country (Strauss and Allen, 2016;Fallou et al., 2019). ...
Article
Public earthquake early warning (PEEW) systems are intended to reduce individual risk by warning people ahead of shaking and allowing them to take protective action. Yet very few studies have assessed their actual efficacy from a risk-reduction perspective. Moreover, according to these studies, a majority of people do not undertake safety actions when receiving the warning. The spectrum of PEEW systems has expanded, with a greater diversity of actors (from citizens to private companies), increased independence from national authorities, and greater internationality. Beyond differences in warning and messaging strategies, systems’ characteristics may impact the way the public perceive, trust, understand, and respond to these warnings, which in turn will influence PEEW systems’ efficacy and perceived usefulness, enhancing the need for additional research. We take the example of earthquake network, an independent, voluntary, community-based and free system that offers a PEEW service. Through a quantitative survey (n = 2625), we studied users’ perception and reaction to a warning sent related to an M 8.0 earthquake in Peru (where no national system existed). We observed that even though only a minority of users actually took protective action, the system was appreciated and perceived as useful by the majority because it enabled mental preparation before the shaking. We found evidence for a tolerance for perceived late, missed, and false alerts. However, because it is a voluntary and independent system, the social dimension of the warning was incomplete because only a fringe of the population benefited from the warning. Therefore, many users’ first reaction was to warn their relatives. We discuss the need for partnerships between PEEW operators and national authorities to guarantee universal access to the service and maximize PEEW system efficacy.
... With increasing population and urbanisation across the globe, large earthquakes have become a significant threat to human life and infrastructure, especially for places closer to active earthquake faults [1]. In this context, interest in issuing earthquake early warnings (EEWs) is increasing globally, and research has found significant benefits of having EEW systems to warn the public [2]. ...
... Research revealed that even a 20-30 s warning lead-time could allow people to take simple protective actions such as drop-cover-hold and mentally prepare themselves for an impending earthquake [4][5][6]. Even a couple of seconds could be extremely useful, as they can provide enough time for automated systems to initiate precautionary emergency measures, such as stopping trains to minimise potential derailment, the appropriate shutting-off of gas distribution valves to reduce fire risk, and the orderly switching-off of large, heavy machinery to minimise potential losses [1]. ...
Article
Full-text available
This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by-step guide to developing a unique EEW network architecture driven by a Software-Defined Wide Area Network (SD-WAN)-based hole-punching technology consisting of MEMS-based, low-cost accelerometers hosted by the general public. In contrast with most centralised cloud-based approaches, a node-level decentralised data-processing is used to generate warnings with the support of a modified Propagation of Local Undamped Motion (PLUM)-based EEW algorithm. With several hypothetical earthquake scenarios, experiments were conducted to evaluate the system latencies of the proposed decentralised EEW architecture and its performance was compared with traditional centralised EEW architecture. The results from sixty simulations show that the SD-WAN-based hole-punching architecture supported by the Transmission Control Protocol (TCP) creates the optimum alerting conditions. Furthermore, the results provide clear evidence to show that the decentralised EEW system architecture can outperform the centralised EEW architecture and can save valuable seconds when generating EEW, leading to a longer warning time for the end-user. This paper contributes to the EEW literature by proposing a novel EEW network architecture.
... An EEW system perceives the ground shaking soon after the earthquake happens and raises alarms to the target areas within the range of seconds to a minute before the strong ground motion arrives there. Although the warning time is short still it can minimize the earthquake impact on different areas of society (Strauss and Allen 2016). For instance, the "drop, cover and hold on" strategy, vacating unsafe buildings, shifting to a safer location inside a structure, automatic shutting down of nuclear plants, gas pipelines, and slowing down of a running train, etc., can reduce earthquake risks. ...
Article
Full-text available
Several natural hazards, including earthquakes, may trigger disasters and the presence of disaster drivers further lead to the massive loss of life and property, every year around the world. The earthquakes are unavoidable, as exact earthquake prediction in terms of date, and time is difficult. However, with the advancement in technology, earthquake early warning (EEW) has emerged as a life-saving guard in many earthquake-prone countries. Unlike other warning systems (where hours of warning are possible), only a few seconds of warning is possible in the EEW system, but this warning may be very helpful in saving human lives by taking the proper action. The concept of EEW relies on using the initial few seconds of information from nearby instruments, performing basic calculations, and issuing the warning to the farther areas. A dense network or enough network coverage is the backbone of an EEW system. Because of insufficient station coverage, the estimated earthquake location is error-prone, which in turn may cause problems for EEW in terms of estimating strong shaking for the affected areas. Seismic instrumentation for EEW has improved significantly in the last few years considering the station coverage, data quality, and related applications. Many countries including the USA, Mexico, Japan, Taiwan, and South Korea have developed EEW systems and are issuing a warning to the public and authorities. Several other countries, namely China, Turkey, Italy, and India are in process of developing and testing the EEW system. This article discusses the challenges and future EEW systems developed around the world along with different parameters used for EEW. Article Highlights This article aims to provide a comprehensive review related to the development The explicit emphasis is on the scientific development of EEW parameters The challenges and future scopes for the effective implementation of EEWS are discussed in terms of the correct location, the magnitude estimation, the region-specific use of ground motion prediction equations, communication technologies, and general public awareness
... The societal impact of a national Early Warning system in terms of risk preparedness and risk mitigation are expected to be extremely relevant. A survey in California from 2016 showed that 88% of the population agreed about the importance of a national Early Warning system for earthquakes [6], and another study showed how such a system on the United States West Coast could reduce the risk of injuries by 50% by enhancing the population preparedness to the event [7,8]. From a cost-benefit standpoint, while a rigorous analysis is required for each use case and it strongly depends on the frequency of the event and the ability of the system to avoid false alarms, employing an EW system can provide great damage reduction, especially when coupled with efficient infrastructures and complementary safety measures. ...
Article
Full-text available
Natural disasters cause enormous damage and losses every year, both economic and in terms of human lives. It is essential to develop systems to predict disasters and to generate and disseminate timely warnings. Recently, technologies such as the Internet of Things solutions have been integrated into alert systems to provide an effective method to gather environmental data and produce alerts. This work reviews the literature regarding Internet of Things solutions in the field of Early Warning for different natural disasters: floods, earthquakes, tsunamis, and landslides. The aim of the paper is to describe the adopted IoT architectures, define the constraints and the requirements of an Early Warning system, and systematically determine which are the most used solutions in the four use cases examined. This review also highlights the main gaps in literature and provides suggestions to satisfy the requirements for each use case based on the articles and solutions reviewed, particularly stressing the advantages of integrating a Fog/Edge layer in the developed IoT architectures.
... Inspiring by the developments of the EEW systems, and also the benefit from them, in the other regions worldwide (Allen et al., 2009;Satriano et al., 2011a;Strauss & Allen, 2016;Allen & Melgar, 2019;Allen & Stogaitis, 2022), Mainland China has been continuously developing and evolving EEW systems at city/infrastructure and regional/provincial scales in order to improve their capability for earthquake risk mitigation in the past three decades (e.g., Li et al., 2004;Peng et al., 2011;Li, 2014;Zhang et al., 2016;Peng et al., 2020; configurations and concluded that the performance of the planned EEW system will be significantly improved. The network-based method for calculating the radii of blind zones proposed by Kuyuk and Allen (2013) can be used to predict the spatial distribution of blind zones for the planned EEW system with the advantages of fewer assumptions compared with Pan et al. (2019). ...
Preprint
Full-text available
The China Earthquake Administration (CEA) has launched an ambitious nationwide earthquake early warning (EEW) system project that is currently under development, which will consist of approximately 15,000 seismic stations and be the largest EEW system in the world. The new EEW system is planned to go online by the end of 2022. In 23% and 3% of Mainland China, the inter-station distance will soon be smaller than 50 km and 25 km, respectively. The effectiveness of the EEW system expected inside Mainland China can be quantified via the metric given by the radius of the blind zone (no-warning zone). Using theoretical network-based method, we generate the spatial distribution of the blind zone radii predicted for the new seismic network based on its configuration. The densified new seismic network is expected to have excellent EEW performance from the perspective of blind zone. The area covered by blind zones that are smaller than 30 km will soon rise from 1.6% to 24.3% inside Mainland China, which means that the area will increase by 2.6 million km 2 (almost the size of Kazakhstan). We claim that every 1,000,000 RMB (158,000 USD) invested to densifying the planned network will increase the area where the blind zone radius is smaller than 30 km by 3,000 km 2. Continuing to increase the density of stations in some key regions with the blind zone radii ranging from 20 to 40 km is still necessary to control the unexpected expansion of blind zones due to the possible (and common) stations failure. Our investigation provides a useful reference for the real functioning and further optimization of the EEW system in Mainland China.
... Because most of an earthquake's energy is carried by the damaging S waves and surface waves, which arrive after the faster and lower-amplitude P waves, EEW is possible because both waves travel far more slowly than the electromagnetic waves used to transfer information (Cremen and Galasso, 2020). Although the potential warning time may only be seconds to minutes, this time is precious so that individuals and institutions (e.g., airports, trains, manufacturing, and energy facilities) can take action to save lives and mitigate the potential damage from earthquakes (Strauss and Allen, 2016). ...
Article
Full-text available
The earthquake early warning systems (EEWSs) in China have achieved great progress, with warning alerts being successfully delivered to the public in some regions. We examined the performance of the EEWS in China's Sichuan Province during the 2019 Changning earthquake. Although its technical effectiveness was tested with the first alert released 10 s after the earthquake, we found that a big gap existed between the EEWS's message and the public's response. We highlight the importance of EEWS alert effectiveness and public participation for long-term resiliency, such as delivering useful alert messages through appropriate communication channels and training people to understand and properly respond.
Article
Fast and accurate magnitude prediction is the key to the success of earthquake early warning (EEW). However, it is difficult to significantly improve the performance of magnitude prediction by empirically defined characteristic parameters. In this study, we have proposed a new approach (EEWNet) based on deep learning to predict magnitude for EEW. The initial few seconds of P-wave recorded by a single station without any preprocessing is used as the input to EEWNet, and the maximum displacement for the whole record is predicted and by which the magnitude is calculated. A large number of borehole underground strong motion records are used to train, validate and test the proposed EEWNet, and the predicted results are compared against those by empirical peak displacement Pd method. The comparison demonstrates that EEWNet produces better and quicker results than those by Pd, and EEWNet can predict magnitude between 4.0 and 5.9 as early as the first 0.5 s P-wave arrives. EEWNet is therefore expected to significantly enhance the accuracy and speed of magnitude estimation in practical regional EEW systems.
Thesis
Full-text available
作为一种在秒级尺度下发挥作用的地震灾害风险控制策略,地震早期预警(以下简称地震预警)的研究不仅对提升我国城乡抗御地震灾害风险的韧性,而且对地震学相关基础理论的发展都具有重要意义。深入地研究现代地震学视野下基于有限震源模型的地震预警问题,一方面将克服点源模型假设下地震预警的一系列不足,另一方面也有望对进一步了解震源物理及其运动学过程提供实时地震学方面的思路。 将有限震源模型应用到地震预警中,合适的有限震源简化模型的选取及其近实时刻画是一个关键问题。本文选取FinDer(Finite-Fault Rupture Detector)算法作为研究手段,考察了其线源模型假设作为有限震源实时刻画依据的理论基础,并进一步对其在中国川滇地区三个大地震(2008年汶川MW7.9/MS8.0地震、2013年芦山MW6.6/MS7.0地震和2017年九寨沟MW6.5/MS7.0地震)预警假设情景(scenario)中的应用进行了系统分析。 本文试图以现代地震学为背景开展讨论,并得出以下结论和认识: 1)用较小自由度的简化(甚至是解析)模型描述地震破裂产生的复杂位错分布是地震学中一个同时具有理论和实际意义的基础问题。为研究目前提出的简化模型哪个最符合反演得到的“实际”位错分布,本文利用赤池信息准则(AIC)评估了均匀位错模型、三角形位错模型、k-2模型、尖锥位错模型和限制性随机位错模型,并以2011年东土耳其凡湖MW7.1地震为例,考虑了六个反演的位错分布。结果显示,整体而言,具有3个自由度的k-2模型似乎与“实际”的位错分布最一致,而自由度最小(为1)的均匀位错模型在表现上仅次于k-2模型和三角形位错模型。作为均匀位错模型特例(在宽度上积分)的线源模型正是FinDer算法的震源模型基础。 2)大地震(M > 6.0)为地震预警提供了一个独特的研究视角,因为地震造成的许多重灾区距离震中较远(~50 km),因此可获得的预警时间(也称前导时间)可能足够长(≥ 5 s),故可以在强地面运动开始前采取有效的预防措施。另一方面,由于震源尺度的有限性,估计M > 6.5地震的潜在地面运动对地震预警来说也是一个巨大的挑战。FinDer是一种能够从强地面运动和/或宽频带地震记录中快速识别有限断层(线源)破裂尺度的方法。本文利用2008年汶川地震、2013年芦山地震和2017年九寨沟九寨沟地震时记录的强震记录,讨论了基于国家强震动台网当前台站布局下FinDer的表现。总体来看,FinDer检索的地震线源模型与观测到的余震空间分布、由波形反演得到的有限断层模型、极震区烈度分布和震源机制解吻合较好。 3)FinDer可根据实时输入的地面运动空间分布检索并持续输出线源模型。对FinDer用于地震预警的效果预评估显示,如果上述所使用的数据能够实时输入FinDer,那么在破坏性的横波到达前,50~80%的烈度IV~VII度区和30%的VIII~IX度区可以分别获得~10s和~5s的预警时间。然而,根据地震预警的需要,FinDer震源模型通常被用来表征高频强地面运动而不是具体的震源参数,因此对于辐射高频成分较丰富的地震事件,破裂长度可能会被高估(如2013年芦山地震)。此外,通过与点源算法进行对比,FinDer不仅在可获得的预警时间和盲区大小方面表现理想,而且也有效压制了系统发生误报漏报的情况。 长期以来,在传统点源模型基础上认为地震预警系统缺乏足够的理论基础且在大地震中表现欠佳,甚至直接因此认为地震预警系统一无是处(或者说是高成本效益)的观点一直存在。可以预料,本文将为此带来一些别样的曙光。本文旨在将合适的有限震源模型引入到中国震例的地震预警研究中,并分析一些在现代地震学新视野下的实时地震学问题。
Article
Full-text available
We determine an optimal alerting configuration for the propagation of local undamped motion (PLUM) earthquake early warning (EEW) algorithm for use by the U.S. ShakeAlert system covering California, Oregon, and Washington. All EEW systems should balance the primary goal of providing timely alerts for impactful or potentially damaging shaking while limiting alerts for shaking that is too low to be of concern (precautionary alerts). The PLUM EEW algorithm forward predicts observed ground motions to nearby sites within a defined radius without accounting for attenuation, avoiding the earthquake source parameter estimation step of most EEW algorithms. PLUM was originally developed in Japan where the alert regions and ground motions for which alerts are issued differ from those implemented by ShakeAlert. We compare predicted ground motions from PLUM to ShakeMap-reported ground motions for a set of 22 U.S. West Coast earthquakes of magnitude 4.4–7.2 and evaluate available warning times. We examine a range of prediction radii (20–100 km), thresholds used to issue an alert (alert threshold), and levels of impactful or potentially damaging shaking (target threshold). We find optimal performance when the alert threshold is close to the target threshold, although higher target ground motions benefit from somewhat lower alert thresholds to ensure timely alerts. We also find that performance, measured as the cost reduction that a user can achieve, depends on the user’s tolerance for precautionary alerts. Users with a low target threshold and high tolerance for precautionary alerts achieve optimal performance when larger prediction radii (60–100 km) are used. In contrast, users with high target thresholds and low tolerance for precautionary alerts achieve better performance for smaller prediction radii (30–60 km). Therefore, setting the PLUM prediction radius to 60 km balances the needs of many users and provides warning times of up to ∼20 s.
Article
Full-text available
Online Material: Movie of wave propagation, GPS coseismic displacements, rupture velocity, waveform comparisons, geologic and 3D seismic structure, and moment rate functions. On 24 August 2014 at 10:20:44.06 UTC, a large earthquake struck the north San Francisco Bay region, approximately 10 km south‐southwest of Napa, California, causing local damage in older wood frame and masonry buildings, road surfaces, sidewalks, and masonry wall structures (Bray et al. , 2014). Using long‐period (50–20 s) three‐component, complete displacement records, the Berkeley Seismological Laboratory (BSL) estimated the scalar seismic moment at 1.32×1018 N·m for a depth of 11 km, corresponding to a moment magnitude of M w 6.0. The strike/dip/rake from the seismic moment tensor solution was 155°/82°/−172°, which is in overall agreement with the trends of structures comprising the West Napa fault system (Fig. 1). Geologic mapping revealed an approximately 14 km long surface rupture with 40–45 cm maximum observed slip on a complex multibranched fault system (Bray et al. , 2014; Earthquake Engineering Research Institute [EERI], 2014; Mike Oskin and Alex Morelan, written comm., 2014). The largest surface offsets were found on a northwest‐striking trend located approximately 1.8 km west of the mapped West Napa fault. Aftershocks are generally located west of the western branch of the surface fault, which had the largest offsets, and indicate a westward dip of the primary fault plane (Fig. 2). Figure 1. Locations of Berkeley Digital Seismic Network (BDSN) stations are shown as labeled squares. Plate Boundary Observatory (PBO) Global Positioning System (GPS) sites are shown as circles, and the positions of Interferometric Synthetic Aperture Radar (InSAR) returns are small gray squares. San Francisco and Napa Valley are indicated by SF and NV. The Berkeley Seismological Laboratory focal mechanism is shown, and the thick line shows the mapped surface trace (EERI, 2014). Figure 2. (a) Coseismic fault‐slip model based on the joint inversion of …
Article
Full-text available
A well-developed public earthquake early warning (EEW) system has been operating in Japan since October 2007. At the time of the 2011 Tohoku-oki earthquake and tsunami (also known as 3.11), several million people near the epicenter received theEEWabout 15 to 20 seconds before the most severe shaking occurred, and many more people in surrounding districts had greater lead time before less severe shaking started. Some 90% of these people were able to take advance actions to save their own lives and those of family members or to take other actions according to prior planning. Some actions were taken based on intuitive responses to the alerts. This high rate of effectiveness is assured to be the result of education regarding the EEW system, both in schools and in society at large. In spite of some shortcomings, the proven effectiveness of EEW has led Japan to strengthen the already extensive seismic- and tsunami-monitoring networks offshore, east of the Japan island arc at 150 sites, and to provide a special terminal for advanced uses of EEW in schools with more than 53,000 students. Efforts are also underway to improve analysis and dissemination schemes.
Article
Full-text available
Recently, progress has been made to demonstrate feasibility and benefits of including real-time GPS (rtGPS) in earthquake early warning and rapid response systems. Most concepts, however, have yet to be integrated into operational environments. The Berkeley Seismological Laboratory runs an rtGPS based finite fault inversion scheme in real-time. This system (G-larmS) detected the 2014 Mw 6.0 South Napa earthquake in California. We review G-larmS’ performance during this event and 13 aftershocks and present rtGPS observations and real-time modeling results for the main shock. The first distributed slip model and magnitude estimates were available 24 s after the event origin time, which, after optimizations, was reduced to 14 s (≈8 s S-wave travel time, ≈6 s data latency). G-larmS’ solutions for the aftershocks (that had no measurable surface displacements) demonstrate that, in combination with the seismic early warning magnitude, Mw 6.0 is our current resolution limit.
Article
Full-text available
Over the last decade, increasing attention has been paid by the international community to the topic of earthquake early warning (EEW) systems, as a viable solution to protect specific hazard‐prone targets (major cities or critical infrastructure) against harmful seismic events. The aim of the EEW system is to detect the occurrence of an earthquake and to determine its relevant characteristics (such as location and magnitude) early enough to predict the ground shaking at the target site before the S ‐wave arrival. Possible emergency protocols that can be activated upon event detection range from slowing down or stopping rail traffic (Nakamura, 2004; Horiuchi et al. , 2005; Espinosa‐Aranda et al. , 2011), safely shutting down or activating protective measure of critical infrastructures such as nuclear power plants (Saita et al. , 2008), to broadcasting alerts to the general public (Wenzel and Lungu, 2000; Lee and Espinosa‐Aranda, 2002; Allen and Kanamori, 2003; Horiuchi et al. , 2005; Wu et al. , 2007). Only few systems have been actually implemented and are currently operational. Examples of regional applications are the systems operating in California, Japan, and Taiwan, whereas targeted systems have been developed, for instance, in Mexico, Irpinia (Italy), and Vrancea (Romania). We refer the interested readers to the comprehensive references in Wenzel and Zschau (2014). Despite the potential benefits of EEW system, several factors so far hindered their widespread application especially in economically developing countries. When the distance between the seismic sources and the exposed target is too short for instance, or there is no technological infrastructure supporting real‐time, automatic operations, the information provided by the EEW system cannot be exploited for pre‐event actions. In these cases, which occur remarkably often in many seismic regions, the level of ground shaking predicted by the system can still be used as input …
Article
Full-text available
Moment magnitudes for large earthquakes (Mw≥7.0) derived in real-time from near field seismic data can be underestimated due to instrument limitations, ground tilting, and saturation of frequency/amplitude-magnitude relationships. Real-time high-rate GPS resolves the build-up of static surface displacements with the S-Wave arrival (assuming non-supershear rupture), thus enabling the estimation of slip on a finite fault and the event's geodetic moment. Recently, a range of high-rate GPS strategies has been demonstrated on off-line data. Here, we present the first operational system for real-time GPS-enhanced earthquake early warning as implemented at the Berkeley Seismological Laboratory (BSL) and currently analyzing real-time data for Northern California. The BSL generates real-time position estimates operationally using data from 62 GPS stations in Northern California. A fully triangulated network defines 170+ station pairs processed with the software trackRT. The BSL uses G-larmS, the Geodetic Alarm System, to analyze these positioning time series, and determine static offsets and pre-event quality parameters. G-larmS derives and broadcasts finite fault and magnitude information through least-squares inversion of the static offsets for slip based on a-priori fault orientation and location information. This system tightly integrates seismic alarm systems (CISN-ShakeAlert, ElarmS-2) as it uses their P-wave detections to trigger its processing; quality control runs continuously. We use a synthetic Hayward Fault earthquake scenario on real-time streams to demonstrate recovery of slip and magnitude. Re-analysis of the Mw7.2 El Mayor-Cucapah earthquake tests the impact of dynamic motions on offset estimation. Using these test cases, we explore sensitivities to disturbances of a-priori constraints (origin time, location, fault strike/dip).
Article
Full-text available
The California Integrated Seismic Network (CISN) is developing an earthquake early warning (EEW) demonstration system for the state of California. Within this CISN ShakeAlert project, three algorithms are being tested, one of which is the network-based Earthquake Alarm Systems (ElarmS) EEW system. Over the last three years, the ElarmS algorithms have undergone a large-scale reassessment and have been recoded to solve technological and methodological challenges. The improved algorithms in the new production-grade version of the ElarmS version 2 (referred to as ElarmS-2 or E2) code maximize the current seismic network's configuration, hardware, and software performance capabilities, improving both the speed of the early warning processing and the accuracy of the warnings. E2 is designed as a modular code and consists of a new event monitor module with an improved associator that allows for more rapid association with fewer triggers, while also adding several new alert filter checks that help minimize false alarms. Here, we outline the methodology and summarize the performance of this new online real-time system. The online performance from 2 October 2012 to 15 February 2013 shows, on average, ElarmS currently issues an alert 8: 68 +/- 3: 73 s after the first P-wave detection for all events across California. This time is reduced by 2 s in regions with dense station instrumentation. Standard deviations of magnitude, origin time are 0.4 magnitude units, 1.2 s, and the median location errors is 3.8 km. E2 successfully detected 26 of 29 earthquakes (M-ANSS > 3: 5) across California, while issuing two false alarms. E2 is now delivering alerts to ShakeAlert, which in turn distributes warnings to test users.
Article
Full-text available
We propose a new algorithm to rapidly determine earthquake source and ground-motion parameters for earthquake early warning (EEW). This algorithm uses the acceleration, velocity, and displacement waveforms of a single three-component broadband (BB) or strong-motion (SM) sensor to perform real-time earthquake/noise discrimination and near/far source classification. When an earthquake is detected, the algorithm estimates the moment magnitude M, epicentral distance Δ, and peak ground velocity (PGV) at the site of observation. The algorithm was constructed by using an artificial neural network (ANN) approach. Our training and test datasets consist of 2431 three-component SM and BB records of 161 crustal earthquakes in California, Japan, and Taiwan with 3:1 ≤ M ≤ 7:6 at Δ≤ 115 km. First estimates be-come available at t 0 ˆ 0:25 s after the P pick and are regularly updated. We find that displacement and velocity waveforms are most relevant for the estimation of M and PGV, while acceleration is important for earthquake/noise discrimination. Including site corrections reduces the errors up to 10%. The estimates improve by an additional 10% if we use both the vertical and horizontal components of recorded ground motions. The uncertainties of the predicted parameters decrease with increasing time window length t 0 ; larger magnitude events show a slower decay of these uncertainties than small earthquakes. We compare our approach with the τ c algorithm and find that our prediction errors are around 60% smaller. However, in general there is a limitation to the prediction accuracy an EEW system can provide if based on single-sensor observations.
Article
Nowadays natural disasters phenomena as hurricanes, volcanic eruptions, tsunamis or earthquakes, are still difficult to prevent. Based on signaling of the phenomenon appearance in the destructive area, important human losses and material damages are avoided. For that reason, WARNING turns into a key objective, both in theoretical and practical research. For the earthquakes, warning intervals are nevertheless very short — seconds to maximum one minute (Mexico City case). Even if the time window is reduced, automated decision measures are possible in case of a well organized system like important facilities. In Romania, the major seismic risk zone is located in Vrancea region. The earthquakes occurring in this area are the main sources for the seismic hazard on Romanian territory. Seismotectonic characteristics of the Vrancea region offers the opportunity to create and develop a rapid seismic warning system. This system is simple, reasonably low-priced, robust and allows warning in an approximately 25 seconds time window for Bucharest. Warning signal obtained is sent to the responsible factors and specific users in order to control automated blocking of the installations and to carry out the required protection actions.
Article
The 11 March 2011 Tohoku-oki earthquake and tsunami that devastated coastal communities in three Japanese prefectures resulted in tremendous loss of life, loss of property, and community disruption. Yet research on the disaster pointed to differential impacts for people with disabilities compared to the rest of the population. Reconnaissance fieldwork took place in Miyagi and Iwate Prefectures 3, 10, and 17 months after the disaster. Interviews and observations point to situated access as a contributor to how and to what extent people with disabilities (PWD) received resources and services. That is, the ability of evacuees to acquire and utilize information, material resources, or services was based both on the physical location of the individual or group (including shelter type to where they evacuated) and the social standpoint or circumstances of the individual or group within that physical location. We offer a close examination of the effect of situational access for people with disabilities in particular. Where limitations were present, they often led to additional disparities.
Article
This paper describes the use of Flex Hose for use by water and fire departments to address the Fire Following Earthquake issue. This paper starts with a history of the 1923 fire that destroyed part of the City of Berkeley. The paper describes how the water system infrastructure was insufficient to control this fire. This paper then discusses the pipe replacement and flex hose options that water utilities and fire departments can use to limit this kind of threat in modern cities for both urban-interface fires and fire following earthquake threats. For a comprehensive examination of Fire Following Earthquake and urban conflagration issues, see FFE (2004), a 350 page report edited by Charles Scawthorn, John Eidinger and Anshel Schiff.