Geophysicist’s method could give months of warning of major earthquakes

The public could be warned days or months before a major earthquake by identifying previous, low-level tectonic disturbances over large areas, according to a study by a University of Alaska Fairbanks scientist who analyzed two major earthquakes in Alaska and California.

The work was led by research assistant professor Társilo Girona of the UAF Institute of Geophysics.

Girona, a geophysicist and data scientist, studies precursor activity to volcanic eruptions and earthquakes. Geologist Kyriaki Drymoni of Ludwig-Maximilians-University of Munich, Germany, is a co-author.

The detection method, based on machine learning, was published on August 28 in Nature Communications.

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

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

They focused on two major earthquakes: the 2018 magnitude 7.1 Anchorage earthquake and the 2019 sequence of magnitude 6.4 to 7.1 Ridgecrest, California earthquakes.

They found that about three months of anomalous low-magnitude regional seismicity occurred across about 15 to 25 percent of south-central Alaska and southern California before each of the two earthquakes studied.

Their research shows that the unrest that precedes major earthquakes is mainly represented by seismic activity of magnitude less than 1.5.

The Anchorage earthquake occurred on November 30, 2018 at 8:29 a.m., with an epicenter located about 11 miles (17 km) north of the city. It caused significant damage to some roads and highways, and several buildings were damaged.

Using their data-learning program, Girona and Drymoni found that, in the case of the Anchorage earthquake, the probability of a major earthquake occurring within 30 days or less had increased sharply to about 80 percent about three months before the November 30 earthquake. The probability jumped to about 85 percent just days before it occurred.

They obtained similar probability results for the Ridgecrest earthquake sequence for a period beginning about 40 days before the onset of the earthquake sequence.

Girona and Drymoni propose a geological cause for the low-magnitude precursor activity: a significant increase in pore fluid pressure within a fault.

Pore ​​pressure refers to the fluid pressure within a rock. High pore pressures can potentially lead to fault slip if the pressure is sufficient to overcome the frictional resistance between the rock blocks on either side of the fault.

“Increased pore fluid pressure in faults that drive major earthquakes changes the mechanical properties of the faults, which in turn leads to uneven variations in the regional stress field,” Drymoni said. “We suggest that these uneven variations … control the anomalous and precursory low-magnitude seismicity.”

Machine learning has a major positive impact on earthquake research, Girona said.

“Modern seismic networks produce huge datasets that, when properly analyzed, can provide valuable insights into the precursors to seismic events,” he said. “This is where advances in machine learning and high-performance computing can play a transformative role, allowing researchers to identify meaningful patterns that could signal an impending earthquake.”

The authors say their algorithm will be tested in near real time to identify and address potential problems with earthquake prediction. The method should not be used in new regions without training the algorithm with the historical seismicity of that area, they add.

Producing reliable earthquake forecasts has a “deeply important and often controversial dimension,” Girona said.

“Accurate forecasts can save lives and reduce economic losses by providing early warnings that enable timely evacuation and preparation,” he said. “However, the uncertainty inherent in earthquake forecasts also raises important ethical and practical questions.”

“False alarms can lead to unnecessary panic, economic disruption and loss of public confidence, while missed forecasts can have catastrophic consequences,” he said.