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Earthquakes, the natural disasters that cause immense damage to life and property on Global scale, Scientists are trying to predict them

Earthquakes are one of the most devastating natural disasters that occur across the globe. They can strike without warning and cause immense damage to life and property. According to the United States Geological Survey (USGS), there are about 20,000 earthquakes annually, and around 16 of them are of magnitude 7 or higher. They not only leave thousands of people homeless, but also ruin the lives of millions across the globe. Earthquakes affect many parts of the world every year. Also, earthquakes further lead to tsunamis and volcanic eruptions causing even more damage.


Yellowstone National Park houses a supervolcano, which has the potential to cause global devastation in case of a supereruption. The United States Geological Survey (USGS) constantly monitors the area for signs of an eruption. Bryan Walsh’s book, ‘End Times: A Brief Guide to the End of the World,’ details how a supereruption could begin with a swarm of earthquakes and continue for days, burying Yellowstone in lava.


The eruption could produce a plume of ash, lava, and volcanic gases, which would reach a height of at least 15 miles and make its way across North America, causing hospitals to be choked with victims coughing up blood as the ash slashed at their lungs. The ash could poison crops and create a worldwide volcanic winter, potentially leading to a global starvation event. In case of a Yellowstone supervolcano eruption, no part of the continental US would be exempt from the effects, and the total damage could amount to $3 trillion, or 16 percent of the country’s GDP, according to a FEMA estimate.


There is no natural disaster sneakier than an earthquake. Hurricanes can be predicted and tracked weeks in advance, and even tornados, monsoons and blizzards at least have seasons. But earthquakes strike entirely without warning.  In the United States, the scientific experts on all things geology are at the US Geological Survey. Their webpage on earthquake prediction starts: “Neither the USGS nor any other scientists have ever predicted a major earthquake. We do not know how, and we do not expect to know how any time in the foreseeable future.” Well, that is pretty clear!


Earthquake Prediction

Earthquake warnings could save thousands of lives each year, however earthquakes have very low predictability in short term, i.e. in most cases, there is no warning – even a few minutes before an earthquake. However, in most cases, a much higher degree of predictability exists in long term – in the sense that if a certain area is sitting on a fault line, it can be said that over a long period of time, there is a high risk of earthquake. However, whether the earthquake occurs within the next few minutes, few years, few decades – or, maybe a few centuries might not be predicted.


Earthquakes occur when two tectonic plates move against each other, creating a fault line. When the stress builds up along the fault line, the rocks on either side deform, and eventually, they reach a point where they can no longer hold the strain, causing the rocks to break and release energy in the form of seismic waves. These waves move through the ground, causing the earth to shake violently.


Predicting earthquakes is a critical area of research because it allows us to prepare and respond appropriately. Scientists use various methods to predict earthquakes, such as studying the history of earthquakes in a particular region, monitoring changes in seismic activity, and using satellite and GPS data to track the movement of the Earth’s crust.


One of the most commonly used methods for predicting earthquakes is seismic monitoring. Seismologists use seismometers to detect and measure seismic waves. By analyzing the data from these instruments, scientists can identify patterns in seismic activity that may indicate an imminent earthquake. They can also track the changes in the earth’s crust by analyzing the frequency and intensity of seismic waves.


Another approach that scientists use is to monitor changes in the Earth’s magnetic field. The buildup of stress in the Earth’s crust can cause changes in the magnetic field, which can be detected by sensitive magnetometers. These changes can provide a warning sign of an impending earthquake.


Scientists have attempted to link multiple natural factors that have preceded earthquakes in the past with the earthquake itself, including increased amounts of radon in local water sources, rising levels of ground water, changes in electromagnetic activity, and even odd animal behavior.


Prediction Challenges

However, predicting earthquakes remains a challenging task. There are still many unknowns about how earthquakes occur and the factors that contribute to them. While scientists have made progress in earthquake prediction, they are yet to develop a foolproof method that can accurately predict earthquakes.


Our understanding of what makes an earthquake happen is based on the theory of plate tectonics, which states  that Earth’s outer shell is divided into several plates that glide over the mantle, the rocky inner layer above the core. The plates act like a hard and rigid shell compared to Earth’s mantle. This strong outer layer is called the lithosphere, which is 100 km (60 miles) thick, according to Encyclopedia Britannica. The lithosphere includes the crust and outer part of the mantle. Below the lithosphere is the asthenosphere, which is malleable or partially malleable, allowing the lithosphere to move around. How it moves around is an evolving idea.


Sometimes during their relative shifting, these tectonic plates bump into one another as they attempt to slide past. The jagged boundary edges of these plates get stuck, while the rest of the plate continues to move, storing up energy along the plate boundary in the process. Once the inner portion of the plate has moved enough to force the edges to overcome the friction holding them together to become unstuck, that stored energy radiates away in waves rippling through the Earth’s rocky surface. These waves shake the ground as they move through it, and an earthquake occurs.


Predicting earthquakes is challenging due to the difficulty in studying how rocks and minerals behave at the increased temperatures and pressures toward the Earth’s core. Small earthquakes and larger earthquakes are thought to start the same way, making it difficult to decipher whether an early warning sign is an omen of a major, more destructive quake or a tiny tremble.


Many countries monitor the seismic activity below the earth. Since there are a lot of seismic activities below the earth on a continuous basis, these countries are not necessarily interested in these low-intensity activities. However, their interest is to see if there is a sudden increase in seismic activities. An increase in seismic activity could imply an impending earthquake in the near-future. However, how close (in “time”) might still not be predictable.

For deeper understanding about Earthquakes and their prediction please visit: Unpredictable Tremors: The Quest for Earthquake Prediction and Mitigation

Predicting earthquakes is a complex and challenging task due to a variety of factors. Some of the major challenges include:

  1. Lack of reliable precursors: Despite decades of research, no reliable precursors have been found that can consistently predict earthquakes with high accuracy. Many different types of precursors have been studied, including changes in electromagnetic activity, ground water levels, and animal behavior, but none have proven to be reliable predictors.
  2. Limited understanding of fault behavior: Faults are complex and dynamic systems, and scientists still have a limited understanding of how they behave. Predicting earthquakes requires understanding how stresses and strains accumulate and release within the Earth’s crust, but this is a complex process that is not yet fully understood.
  3. Limited data: There are still many areas around the world where seismic activity is poorly monitored or not monitored at all, making it difficult to get a complete picture of earthquake activity. Additionally, there are still many aspects of earthquake behavior that are not fully understood, and more data is needed to improve models and predictions.
  4. Lack of computational power: Modeling earthquakes requires a tremendous amount of computational power, and even with the most powerful supercomputers, it can still take days or weeks to simulate the behavior of a single fault. This limits the ability of scientists to run large-scale simulations and explore different scenarios.
  5. Political and economic considerations: In many cases, the areas that are most at risk of earthquakes are also the most densely populated and economically important. Predicting earthquakes and issuing warnings can have significant political and economic implications, and there may be pressure to downplay the risks or delay issuing warnings in order to avoid causing panic or disrupting economic activity.



Advances in Earthquake prediction technologies

Earthquake prediction is the science of seismology concerned with specifying the time, location, and magnitude of future earthquakes within stated limits. Earthquake prediction is different from earthquake forecasting, which can be defined as the probabilistic assessment of general earthquake hazard, including the frequency and magnitude of damaging earthquakes in a given area over years or decades. Prediction can be further distinguished from earthquake warning systems, which provide a real-time warning of seconds to neighboring regions that might be affected upon detection of an earthquake.


While predicting earthquakes with absolute certainty remains elusive, advances in technology have allowed scientists to improve their understanding of the underlying processes and potentially provide earlier warning signs of an impending earthquake. Here are a few examples:

  1. Seismic Monitoring: Seismometers are instruments that detect and measure ground motion caused by seismic waves. By analyzing the data from these sensors, seismologists can locate the epicenter of an earthquake, determine its magnitude, and even identify the fault that caused it. The development of more sophisticated and sensitive seismometers has enabled researchers to detect smaller and more subtle tremors, which could indicate the potential for a larger earthquake.
  2. GPS and Satellite Imaging: Satellites equipped with radar and other sensors can detect ground deformation caused by tectonic plate movement. By comparing images taken at different times, scientists can measure the displacement and strain in the Earth’s crust, providing important information about where the buildup of energy is occurring.
  3. Machine Learning and AI: With the large amounts of data being collected from various sources, machine learning and artificial intelligence algorithms can be trained to identify patterns and correlations that might be missed by human analysts. These methods have been used to identify precursors to earthquakes, such as changes in electromagnetic activity or animal behavior.
  4. Early Warning Systems: While not a prediction technology, early warning systems can provide critical seconds or minutes of advance notice before seismic waves reach a populated area. These systems use real-time data from seismometers to estimate the size and location of an earthquake and issue warnings via text message or other means to people in affected areas.
  5. Virtual Earthquake Simulators: These simulations use computer models to simulate how an earthquake might occur and spread through the Earth’s crust. Researchers can adjust various parameters to see how different factors, such as fault geometry or material properties, affect the resulting earthquake. These simulations can help scientists better understand the physics of earthquakes and potentially identify ways to mitigate their impact.



NASA’s technology

NASA’s Jet Propulsion Laboratory has developed radar-based mapping technology that uses airborne pictures to create interferograms, which depict the size of motions which have occurred over a period of time underneath the ground. This technology can improve hazard map outlooks from 30 years to somewhere between five and ten years.

In a recent study presented at the Geological Society of America’s annual meeting, geologists tracked the incidence of magnitude 7 or greater earthquakes worldwide since 1900 and found that it takes five to six years for the energy sent out by the Earth’s core to radiate to the upper layers of the planet where quakes occur.

Friedemann Freund, a NASA researcher, is using conductivity sensors to monitor air molecules along fault lines in Alaska and on the San Andreas Fault in California to detect changes in ionization that could help predict earthquakes up to 24 hours in advance.

Freund’s theory revolves around the concept that pressurized rock under the Earth’s surface emits an electrical current that ionizes air molecules, something that could be monitored and measured in earthquake-prone regions.


Machine learning can predict time to earthquake

Machine learning and AI can help us predict earthquakes by analyzing seismic data and identifying patterns that precede earthquake events. For example, researchers have used machine learning algorithms to analyze seismic signals in the Cascadia fault and found a highly predictable sound pattern that indicates slippage and fault failure. The loudness of the fault’s acoustic signal is also directly related to its physical changes. This can help scientists more accurately predict when and where a megaquake might occur.

Another company, One Concern, uses machine learning to predict and mitigate the impact of natural disasters such as earthquakes, fires, and floods. Their AI model, Seismic Concern, is trained with information about building structural integrity and seismic activity to predict the impact of an earthquake down to individual city blocks and buildings. Real-time information input during an earthquake improves how the system responds.

In general, machine learning and AI can analyze vast amounts of data more quickly and accurately than humans can, helping us identify patterns and make predictions that could potentially save lives and mitigate damage from natural disasters like earthquakes.


Machine-learning research published in two related papers published in Nature Geoscience in Dec 2018,  reports the detection of seismic signals accurately predicting the Cascadia fault’s slow slippage, a type of failure observed to precede large earthquakes in other subduction zones.


One Concern, an AI startup, has secured $20 million in funding to expand its use of machine learning in predicting and mitigating the impact of natural disasters. Its predictive AI, called Seismic Concern, focuses on earthquake preparedness and response by deploying AI models trained with information about building structural integrity and seismic activity to help cities know where to dispatch emergency workers after an earthquake. The company plans to launch a similar program for floods and eventually other natural disasters. One Concern aims to provide insights across the entire time horizon, from days before a flood to forward-looking policy and planning.  The mapping company Esri has built rapid-response software that shows expected damage from disasters like earthquakes, wildfires and hurricanes.


Researchers at The University of Texas at Austin have achieved noteworthy progress in earthquake prediction using artificial intelligence (AI).

In a seven-month trial in China, their AI algorithm successfully predicted 70% of earthquakes a week in advance by identifying statistical anomalies in real-time seismic data combined with historical earthquake information. The AI’s weekly forecasts accurately predicted 14 earthquakes within approximately 200 miles of estimated locations, nearly matching their expected magnitudes. While the system missed one earthquake and issued eight false warnings, this breakthrough offers promise for earthquake preparedness and forecasting worldwide, demonstrating that earthquake prediction is a solvable problem.

The AI’s methodology involved a relatively straightforward machine-learning approach, receiving statistical features based on earthquake physics knowledge and self-training using a five-year database of seismic recordings. The researchers, led by Professor Sergey Fomel, expressed optimism about the AI’s potential to enhance earthquake preparedness and reduce economic and human losses. While global predictions are not yet within reach, the researchers believe the AI could perform even better in areas with robust seismic monitoring networks, paving the way for a versatile prediction system applicable worldwide and marking a significant milestone in AI-driven earthquake forecasting.


Quantum Technology for Earthquake Prediction

High-accuracy gravity measurements can be used to identify faults under stress and most likely to be active, providing a medium-term outlook on areas most likely to be affected by the next earthquake. Instantaneous gravity signals caused by the shifting of mass in the ground can be detected before the first seismic waves, offering the potential for earlier earthquake warnings by overcoming the limitations of seismic wave propagation speed.


While an alert triggered by a gravity signal might only give a few additional seconds, such a warning can provide extra time to allow the public to take preventative action, such as ensuring fire station doors are opened before they may be disabled. It could also allow the shutdown of public transit to avoid derailment, as well as power, gas and other networks which may be damaged or provide secondary risks such as fire, saving lives.


According to a recent article by the University of Birmingham, quantum technology has the potential to improve earthquake detection. Currently, seismologists use networks of sensors to detect and locate earthquakes, but these sensors are limited by background noise, which can reduce the accuracy of earthquake detection.


However, quantum technology may provide a solution to this problem. By using quantum sensors, which are highly sensitive to tiny changes in magnetic and electric fields, seismologists could more accurately detect the vibrations and movements associated with earthquakes. This would allow them to detect smaller earthquakes and improve the accuracy of earthquake location and magnitude measurements.

The article also mentions that researchers are exploring the use of quantum entanglement, a phenomenon where two particles become linked in such a way that the state of one particle is dependent on the state of the other. By using entangled particles to create highly precise measurements, researchers may be able to improve the accuracy of earthquake detection even further.

Overall, quantum technology has the potential to revolutionize earthquake detection and improve our understanding of earthquakes. However, more research and development are needed before these technologies can be widely implemented in seismology.


Conclusion and Final Thoughts

However, predicting earthquakes remains a challenging task. There are still many unknowns about how earthquakes occur and the factors that contribute to them. While scientists have made progress in earthquake prediction, they are yet to develop a foolproof method that can accurately predict earthquakes.


Despite this, the work of scientists in predicting earthquakes is critical in helping communities prepare for earthquakes. Early warning systems can provide valuable time for people to evacuate, move to safer areas, and take necessary precautions to protect themselves and their property.


In conclusion, earthquakes are a natural disaster that continues to pose a significant threat to life and property across the globe. Although scientists are making progress in predicting earthquakes, much more research is needed to develop a reliable and accurate prediction method. The work of these scientists remains critical in helping communities prepare for and mitigate the impact of these devastating events.


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