Model shakes up earthquakes forecasting

Findings by a Western-led international research team may mitigate hazard, damage, even loss of life by helping forecast the largest possible earthquake within a series of quakes, according to a study published today.

From April 14-16, 2016, the Kumamoto, Japan, earthquakes featured a magnitude 7.3 mainshock two days after a magnitude 6.5 foreshock. The two quakes killed at least 50 people and injured 3,000 others. Severe damage occurred in Kumamoto and Ōita Prefectures, with numerous structures collapsing and catching fire. More than 44,000 people were evacuated from their homes due to the disaster.

Researchers from Western, the Institute of Statistical Mathematics (Japan) and the University of Potsdam (Germany) studied those events and used them to create a new statistical approach that estimates the probabilities for such extreme earthquakes during a prolonged seismic sequence of events to be above certain magnitudes.

The findings were published today in the journal Nature Communications.

Historical data shows most earthquakes, like Kumamoto, occur unexpectedly and often trigger subsequent events far more powerful than the initial shock. Forecasting the largest expected earthquake within a series is critically important in mitigating hazard, damage and loss of life.

Earth Sciences professor Robert Shcherbakov, first author on the study, stresses it is important to differentiate between forecasting and predicting earthquakes.

“Predicting earthquakes means providing a narrow range of times and locations where large earthquakes are going to occur which is rather unrealistic at the moment,” he said.

The model, however, did allow Shcherbakov and his collaborators to estimate, retrospectively, the probabilities of having large subsequent earthquakes during several stages of the evolution of 2016 Kumamoto seismic event.

“The probabilities for large earthquakes proved rather low, but it is still very important to have such estimates,” Shcherbakov said.