New method could predict earthquakes months before they happen

Scientists have developed a new method that can accurately predict earthquakes months before they occur.

Developed by a scientist at the University of Alaska Fairbanks, the method looks to identify past low-level tectonic disturbances across large areas.

The study is based on the precursor activity of volcanic eruptions and earthquakes and uses machine learning to predict any such event.

Led by research assistant professor Tarsilio Girona of the University of Alaska Fairbanks' Institute of Geophysics, the study analyzed two large earthquakes in Alaska and California (the 2018 magnitude 7.1 Anchorage earthquake and the 2019 magnitude 6.4 to 7.1 Ridgecrest, California earthquake series).

Scientists detect abnormal, low-magnitude regional seismic activity

Prior to each of the two earthquakes studied, the researchers found that nearly three months of abnormally low-magnitude regional earthquakes occurred in about 15% to 25% of south-central Alaska and southern California.

Their research found that disturbances that precede major earthquakes are mostly caused by seismic activity of magnitude less than 1.5.

The Anchorage earthquake struck at 8:29 a.m. on Nov. 30, 2018, with its epicenter about 10.5 miles north of the city. The quake caused significant damage to some roads and highways, and damaged several buildings, according to the study.

Machine learning may be able to identify early signs of large earthquakes

“Our paper shows that advanced statistical techniques, especially machine learning, have the potential to identify early indicators of large-magnitude earthquakes by analyzing datasets derived from earthquake catalogs,” Girona said.

The authors wrote a computer algorithm, a set of computer instructions that teaches a program how to interpret the data, learn from it, and make informed predictions or decisions, to search the data for abnormal seismic activity.

Using their data-trained program, Girona and Kyriaki-Draymoni, a co-author of the study, found that with the Anchorage earthquake, the probability of a major earthquake occurring within 30 days or less suddenly rose to about 80 percent about three months before the Nov. 30 quake.

The probability of the earthquake occurring rose to about 85 percent a few days before it struck. The researchers found similar odds for the Ridgecrest earthquakes that occurred during a period beginning about 40 days before the earthquakes, according to a news release from the University of Alabama at Arkansas.

Researchers propose a geological cause for the low-volume ancestral activity: a significant increase in pore fluid pressure within the fault.

Pore ​​fluid pressure refers to the pressure of fluid within a rock. High pore fluid pressure can cause a fault to slip if the pressure is enough to overcome the frictional resistance between rock masses on either side of the fault, according to the study published in Nature Communications.

“Increased pore fluid pressure in faults that lead to major earthquakes changes the mechanical properties of the faults, which in turn leads to uneven variations in the regional stress field,” Draimoni said.

“We propose that these unequal variations…control the abnormal low-magnitude seismic activity.”

Scientists claim that machine learning has a significant positive impact on earthquake research.

Modern seismic networks produce massive data sets.

Modern seismic networks produce massive data sets that, when properly analyzed, can provide valuable insights into the causes of seismic events, Girona added.

“This is where advances in machine learning and high-performance computing can play a transformative role, enabling researchers to identify meaningful patterns that could indicate an impending earthquake,” Girona noted.

The algorithm developed by the researchers will soon be tested in near-real-world situations in an attempt to address potential challenges in earthquake prediction.

The researchers stressed that the method should not be used in new areas without training the algorithm on historical earthquakes in that area. They also claimed that producing reliable earthquake forecasts has a “critical and often controversial dimension.”

“Accurate forecasting has the potential to save lives and reduce economic losses by providing early warnings that allow for timely evacuation and preparedness. However, the inherent uncertainty in earthquake forecasting also raises significant ethical and practical questions,” Girona concluded.

“False alarms can lead to unnecessary panic, economic disruption, and loss of public confidence, while wrong forecasts can have dire consequences.”

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About the Editor

Prabhat Ranjan Mishra Prabhat, an alumnus of the Indian Institute of Mass Communication, is a technology and defence journalist. While he enjoys writing about modern weapons and emerging technology, he has also reported on global politics and business. He has been previously associated with well-known media houses including International Business Times (Singapore edition) and ANI.

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