With the gloom of the Turkey-Syria earthquake that has left over 40,000 dead weighing heavily on our minds, the question, which always pops up after every earthquake, is popping up again: why can’t these earthquakes be predicted?
The narrative always veers around the behavior of birds and animals, which seem to sense the oncoming disaster. If there is something that these creatures sense, why can’t we sense that too?
The general consensus among experts still is that earthquakes cannot be predicted. Dr. Abhishek Kumar, Associate Professor, Department of Civil Engineering, Centre for Disaster Management and Research (CDMR), IIT Guwahati, tells Quantum that parameters such as 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 in such areas, but you can’t tell when the earth will shake.
Recent research papers on predicting earthquakes 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.”
Unique precursor
Some are more emphatic, believing that it is possible to foretell the magnitude, epicenter and time of occurrence of earthquakes. Two such scientists are Manana Kachakhidze and Nino Kachakhidze-Murphy of the Georgian Technical University, Natural Hazard Scientific‐Research Center, 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.”
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, changes in the intensity of electro-telluric currents (electric currents that move underground or undersea) in the focal area, perturbations of the geomagnetic field in the forms 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 Kachakhidzes set store by VLF/LF electromagnetic emissions, which they describe as a “unique precursor”, because “it gives the promising possibility of simultaneous determination of moderate and strong, inland incoming earthquake magnitude, epicenter, and time of occurrence.”
VLF/LF electromagnetic radiation frequency analysis gives the possibility simultaneously to determine all three characteristic parameters necessary for incoming earthquake prediction (magnitude, epicenter, and time of occurring). It is shown that the prediction of moderate and strong earthquakes is possible with great precision. They stress tht VLF/ LF EM radiation “fully meets the Guidelines for Submission of Earthquake Precursor Candidates.”
Looking at data
While Bhatia and the Kachakidzes are looking into physical parameters, other scientists dunk their dipsticks into another source of precursors: data. But each year, about 500,000 earthquakes happen. We may feel only a very few of them, 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, Japan, believes that a tool called ‘exploratory data analysis’ (EDA) can help in earthquake prediction. EDA is a method of manipulating data in order to find patterns or anomalies in it.
Konishi, in his paper on the use of EDA for predicting earthquakes, describes how he used the technique on data on various parameters before the 2011 Tohoku earthquake and spotted three anomalies. These could have been spotted before the earthquake and lives saved.
Tipping point
In India, Prof R I Sujith at the Department of Aerospace Engineering, IIT Madras (while stressing that he had never worked on predicting earthquakes), says that a tool called ‘critical transitions in complex systems’ might help.
Prof Sujit has been studying the behaviour of flames in the combustion chamber of an aircraft engine. The heat of flames releases sound waves which reflect back and feed the flames, making it a ‘feedback loop’. At a certain tipping point, it could lead to an explosion. The study of this ‘thermo-acoustic instability’ took Sujit to ‘critical transitions in complex systems’, which is a technique to figure out when a tipping point would occur in a complex system.
In simple terms, the tipping point is the proverbial ‘last straw on the camel’s back’ - the point when 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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