Tectonic challenge. Many tools on the horizon to predict earthquakes

As the devastation caused by the Turkey-Syria earthquake, which has claimed over 40,000 lives, weighs heavily on everyone’s mind, we come back to the question that pops up after every earthquake: Is there a way to predict an earthquake and, thereby, minimise the toll on life and property?

The general consensus among experts is that earthquakes cannot be predicted. Dr Abhishek Kumar, Associate Professor, Department of Civil Engineering, Centre for Disaster Management and Research, IIT-Guwahati, tells Quantum that in-situ measurements of ground temperature and satellite-based measurements of ground displacement can help identify earthquake-prone regions. However, “the temporal occurrence of earthquakes in such regions is still an area of further study.”

At best you can build earthquake-resistant buildings, but you cannot tell when the earth will shake.

Recent research papers on earthquake prediction are more hopeful — perhaps an indication of growing confidence among scientists. In a paper titled ‘Artificial intelligence-based real-time earthquake prediction’, published in Engineering Applications of Artificial Intelligence, Munish Bhatia, et al, note that “with the technological revolution in data acquisition, communication networks, edge–cloud computing, the Internet of Things (IoT), and big data analysis, it is feasible to develop an intelligent earthquake prediction model for early warnings at vulnerable locations”.

Others are more emphatic, believing it is possible to foretell the magnitude, epicentre and time of occurrence of earthquakes. Among them are the scientists Manana Kachakhidze and Nino Kachakhidze-Murphy of Georgian Technical University, Natural Hazard Scientific Research Center in Tbilisi, Georgia. In a May 2022 (yet to be peer-reviewed) paper, they say: “To the question ‘is it possible to predict earthquakes?’ we may answer that moderate and strong earthquakes can be predicted.”

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Tuning into earth’s language

The earth speaks loud and clear before it shakes, albeit in its own language. It speaks in terms of very low frequency and low frequency (VLF/LF) electromagnetic emissions, altered intensity of electro-telluric currents (electric currents that move underground or undersea) in the focal area, perturbations of geomagnetic field in the form of irregular pulsations, perturbations of the atmospheric electric field, increased intensity of electromagnetic emissions in the upper ionosphere in several hours or tenths of minutes before an earthquake, and infrared radiation. Not all of these are necessarily observed before each earthquake, but there is one or the other of these precursors.

Manana and Nino set store by VLF/LF electromagnetic emissions, which they describe as “unique precursor. VLF/LF electromagnetic radiation frequency analysis offers the possibility to simultaneously determine the three characteristic parameters (magnitude, epicentre, and time of occurring) needed for incoming earthquake prediction.

It is shown that the prediction of moderate and strong earthquakes is possible with great precision. They stress that VLF/LF electromagnetic radiation “fully meets the guidelines for submission of earthquake precursor candidates”.

While Bhatia and the Kachakhidzes are looking into the physical parameters, other scientists are focusing on yet another source of precursors: data.

Each year witnesses about 500,000 earthquakes. We may sense only a few of these, but each event spews tons of data, out of which some pattern could be discerned. Tomokazu Konishi of the Graduate School of Bioresource Sciences, Akita Prefectural University in Akita City, Japan, believes that a tool known as ‘exploratory data analysis’ (EDA) can help in earthquake prediction. EDA involves manipulating data in order to find patterns or anomalies in it.

Konishi, in his paper on the use of EDA in predicting earthquakes, describes how he used the technique to analysis various parameters associated with the 2011 Tohoku earthquake and spotted three anomalies. Had these been spotted before the earthquake, lives could have been saved.

Locating the tipping point

In India, Prof RI Sujith at the Department of Aerospace Engineering, IIT-Madras (while stressing that he had never worked on earthquake prediction), says that a tool known as ‘critical transitions in complex systems’ might help.

Prof Sujith has been studying the behaviour of flames in the combustion chamber of aircraft engines. The heat of the flames releases sound waves, which reflect back and feed the flames in a ‘feedback loop’. At a certain tipping point, it could lead to an explosion. The study of this ‘thermo-acoustic instability’ took Sujith to ‘critical transitions in complex systems’, which is used to determine when a tipping point is likely in a complex system.

In simple terms, the tipping point is the proverbial ‘last straw on a camel’s back’ — the point when even a tiny change in input conditions causes a sudden and drastic shift in the state of the system. Nothing, including earthquakes, happens really suddenly — the suddenness is only at the tipping point. ‘Critical transitions in complex systems’ is an emerging area of study that is being applied to a range of problems, from epidemiology to financial markets. Why not earthquake prediction?

So, in future it will be possible to build a model that integrates multiple techniques to forewarn people about an oncoming earthquake.

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