Author: Carolyn Gramling / Source: Science News
A new artificial intelligence is turning its big brain to mapping earthquake aftershocks.
Scientists trained an artificial neural network to study the spatial relationships between more than 130,000 main earthquakes and their aftershocks. In tests, the AI was much better at predicting the locations of aftershocks than traditional methods that many seismologists use, the team reports in the Aug. 30 Nature.
Although it’s not possible to predict where and when an earthquake will happen, seismologists do know a few things about aftershocks. “We’ve known for a long time that they will cluster spatially and decay over time,” says geophysicist Susan Hough of the U.S. Geological Survey in Pasadena, Calif., who was not an author on the new study.
Then, in 1992, a series of temblors prompted a flurry of interest in trying to map out where exactly an aftershock might occur, based on how a mainshock might shift stresses on other faults. First, a magnitude 7.3 earthquake shook the Southern California town of Landers and other nearby desert communities. Three hours later, a magnitude 6.5 aftershock struck the more populous area of Big Bear, about 35 kilometers away. The next day, a magnitude 5.7 aftershock struck near Yucca Mountain, Nev., nearly 300 kilometers away.
“After 1992, people were looking to understand [aftershock] patterns in more detail,” Hough says. Researchers began trying to distill the complicated stress change patterns using different criteria. The most used criterion, the “Coulomb failure stress change,” depends on fault orientations.
But fault orientations in the subsurface can be as complicated as a three-dimensional crazy quilt, and stresses can push on the faults from many different directions at…
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