Technology Used to Warn People about Earthquakes
Advances in technology used to warn people about earthquakes ensure timely responses to phenomena such as earthquakes, tsunamis, and other natural disasters. Recent developments in earthquake warning technology, including mass notification capabilities and smart systems, have become more effective than ever in saving lives and protecting critical infrastructure.
How Earthquake Early Warning Systems Work
Countries across the globe have implemented earthquake early warning (EEW) systems, and more are in various stages of development. The success of EEW systems is measured by the amount of time it takes to detect a seismic wave through Internet of Things (IoT)-connected sensors and transmit the data. Current EEW systems only detect earthquakes occurring in real-time rather than provide predictions.
How Earthquake Early Warning Systems Detect Ground Motion
Earthquake early warning systems monitor the seismic waves and vibrations through various sensors located in specific geographic locations. When the earthquake begins, compressional (P) waves and transverse (S) waves travel from the hypocenter and set off the sensors located at a seismic station. Seismographs detect P waves first because they travel significantly faster than S waves.
A computer analyzes the data transmitted from the sensors to determine the epicenter location, magnitude, and potential ground shaking hazards of the earthquake. If the seismic data transmitted exceeds a determined safety threshold and the earthquake poses a severe risk, an alert is sent, and communities can prepare accordingly.
How Far in Advance Earthquake Early Warning Systems Detect Possible Earthquakes
Wireless emergency alert (WEA) systems and emerging algorithms help detect earthquakes anywhere from seconds to minutes. The time between an earthquake detection and an emergency alert depends on how close the sensors are to the hypocenter of the earthquake in comparison to the location of the community. For example, Mexico City uses sensors located at a subduction zone hundreds of miles from the city. Therefore, after the detection of an earthquake, citizens living in Mexico City have sixty seconds or more to prepare.
Algorithms such as the Earthquake Point-Source Integrated Code (EPIC), used to develop the United States west coast’s ShakeAlert system, are continuously tested and improved.
Advances in EEW systems, such as seismic wavefield imaging, have the potential to predict seismic wave propagation, not just after it occurs. The seismic full-waveform inversion takes 3D imaging of Earth’s interior, such as subduction zones, to provide a holistic approach to understanding how the Earth operates under the surface.
Examples of Earthquake Early Warning Systems
Areas with high seismic activity, known as “red zones,” frequently utilize EEW systems. Examples of red zones can be found in Japan, Mexico, New Zealand, Australia, Turkey, China, Italy, Taiwan, and Romania.
ShakeAlert, developed by the United States Geological Survey (USGS) and other partners for the west coast of the United States, is the only EEW system in the country. As previously mentioned, ShakeAlert is a product of the EPIC algorithm, which uses seismometers to detect ground motion.
Japan features another successful example of an EEW system, which is considered to be one of the most advanced early warning systems in the world. Japan has implemented a two-step process to detect earthquakes and predict damage. The Japanese Meteorological Agency installed approximately one thousand seismographs across the country as well as seismic intensity meters. While seismographs detect the presence of waves themselves (P-waves or S-waves), seismic intensity meters detect the overall strength of a wave and the potential damage it could cause.
Recent Advancements in Earthquake Warning Technology
Earthquake warning technology advances not only in terms of real-time warning systems but also in terms of predictive capabilities. The IoT connectivity platform and developments in both software and hardware systems in smartphones collectively monitor and store measurements to understand seismic activity better than before. Other advances include the ever-expanding use of deep learning, artificial intelligence, and machine learning in modeling and predicting earthquakes.
How the Advent of Mass Notification Capability Changed Earthquake Warning Technology
Mass notification systems (MNS) broadcast emergency alerts to notify first responders, emergency management organizations, and the community to prepare for an oncoming emergency. WEA systems and radio and TV broadcasts as well as local sirens produce these alerts.
Technological advances in MNS means countless numbers of lives rescued and saved. For example, in 2010, an 8.0-magnitude earthquake hit Chile and claimed approximately 560 lives. Four years later, an even larger earthquake hit the Chilean coast. However, because of the newly established MNS, eVigilo, only five people lost their lives.
How Smart Systems Have Changed Earthquake Warning Technology
Earthquake early warning systems have advanced with the development of mobile computing power. For example, the various motion-detecting sensors found within smartphones, such as GPS and accelerometers, possess the potential to detect seismic activity. This would make smartphones into individual seismographs and create smartphone-based networks across the world. This high-impact use of global connectivity would expand seismic networks and enhance overall safety and security.
Scientists seek to delineate between human activity and earthquake activity collected by sensors in a smartphone. The creation of a fixed-smartphone network requires more investments in research.
How Advancements in IoT Have Changed Earthquake Warning Technology
The Internet of Things has produced a connectivity platform of continuous data that researchers use to analyze patterns that contribute to seismic activity. Advancements in IoT ,such as artificial intelligence (AI) and the expansion of low-power, wide-area networks, creates even more opportunities for scientists and researchers. These advancements allow scientists to transition from real-time emergency alerts to proactive and predictive measurements.
Data collected from IoT over a span of years creates a critical resource of historical measurements that are helpful to scientists. These historical measurements allow scientists to compare the conditions of past earthquake activity and how those conditions compare to today.
For example, researchers in the red zone of New Zealand are using IoT to monitor the conditions of tectonic plates and water levels in the ocean to predict tsunamis as well as earthquakes.
Effectiveness of Earthquake Warning Systems
The effectiveness of an EEW system is dependent on the amount of data collected and stored by (AI) seismic signals. The more seismic data stored within a computer, the more accurately the algorithms and models can monitor and predict earthquake activity.
How Technological Advancements Improve the Effectiveness of Earthquake Warning Systems
Technological advancements in earthquake warning systems help scientists pivot from a real-time approach of disaster risk reduction to a proactive approach.
For example, the development of more advanced ground motion sensors has greatly reduced the frequency of false alarms. Additionally, the thousands of hours of data collected by AI seismic signals and the IoT platform have created measurements and historical patterns to help predict natural disasters.
Research continues as technology advances to make earthquake warning systems more effective. Recent research surrounding high-speed computation powers and quantum communication is currently underway as well as the development of more geographically distributed information centers. The ability to store information more securely through quantum communication networks and enhanced data access will ultimately make EEW systems more effective.
Factors Impacting the Effectiveness of Earthquake Warning Systems
Despite recent progress with early warning systems, challenges and obstacles must still be overcome. For example, an earthquake strong enough to produce damage to critical infrastructure might disable mobile towers for hours or even days. Therefore, WEA systems will be rendered useless. It is important to not just rely on ground communications but to also have alternate mechanisms in place, such as satellites.
Network latency presents another challenge due to the amount of computational hours that are needed to monitor and store data. The magnitude of information creates extremely complex data, which takes time to analyze.
The Limitations of Earthquake Warning Systems
Research improves the overall effectiveness of early warning systems; however, scientists can only work within the limitations of already existing infrastructures. For example, broadband access is not uniform worldwide, presenting serious challenges to monitoring and predicting natural disasters.
The distribution of seismic sensors and devices in more geographically remote places provides another limitation. It is important that earthquake warning systems do not rely solely on the data collected from populated places but also from uninhabited islands and bodies of water. However, these seismic devices must rely on a wireless network not always prevalent in remote locations.
Lastly, early warning systems are dependent on the tectonic environment and the proximity of communities to the various fault lines across the world. Therefore, limitations on the potential warning times and responding mitigation efforts will vary.
How Advancements in Seismology Tech Are Helping Save Citizen Lives
The United Nations reports that roughly 90 percent of natural disasters worldwide are weather related. With this statistic in mind, scientists have dedicated years of data-driven research to advance seismology tech.
How Seismology and Tech Have Been Used in Earthquake Early Warning Systems in Recent Times
Scientists have invested in earthquake fault imaging research around the deployment of underwater sensing devices, floating sensing devices, and unmanned air vehicles to detect and monitor seismic activity. These devices provide measurements based on geodetic and topographic imaging to better understand fault zones and earthquakes in general. This multi-angle imaging approach can potentially save lives and billions of dollars in critical infrastructure damages.
How Seismology and Tech in Earthquake Warning Systems Has Been Used to Prevent Casualties
The 8.0-magnitude 2008 Sichuan Earthquake in China claimed approximately 84,000 lives and cost an estimated $85 billion in damages. At the time of this earthquake, the buildings in Sichuan (a very rural part of China) were not seismic-resistant, and there was no early warning system in place.
After the devastation this earthquake caused, Chinese government officials established an EEW system and implemented a disaster risk management program to help educate citizens on how to respond to early warnings. Since China’s EEW development, there has still been loss of life and property due to earthquakes, though nowhere near the devastation from 2008.
Countless examples from around the world, similar to China, can be examined to analyze how far technology has come to save citizen lives. For example, South Korea invested roughly $7 billion on a high-speed, seismic-resistant railway project. Engineers placed sensors throughout the rail infrastructure to monitor seismic activity as well as structural adjustments. Similarly, seismic-resistant buildings, such as airports, hospitals, arenas, and residential buildings, are proliferating in red zones across the world.
How Seismology and Tech in Earthquake Warning Systems Have Been Used to Prevent the Loss of Property and Infrastructure
The United States Federal Emergency Management Agency (FEMA) published a report that compares the cost of maintaining an EEW system to the loss of lives and the economic loss of property. The report compares injuries and monetary losses utilizing statistics from large-scale earthquakes across the world.
In the report, FEMA found that approximately 50 percent of the injuries sustained from the Loma Prieta and Northridge earthquakes in California were the result of “non-structural elements” (furniture, ceiling tiles, etc.). These injuries were deemed preventable if the individuals had been alerted of the earthquake even seconds before. FEMA calculated the economic cost of these injuries between $1.8 billion to $2.9 billion.
Regarding infrastructure, Japanese officials estimated that the 1995 Kobe earthquake produced roughly $100 billion losses related to an interruption in local business and $147 billion in direct property losses. Similarly, the Loma Prieta earthquake permanently shut down approximately 50 percent of local business, and job loss severely impacted the San Francisco Bay Area’s economy.
If EEW systems were in place prior to the earthquakes’ occurrence, they would have saved billions of dollars. Comparatively, the cost of maintaining the ShakeAlert EEW system on the west coast for one year is approximately $16 million. For perspective, every dollar spent on earthquake mitigation saves approximately ten dollars in costs when a disaster occurs.
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