How powerful Myanmar earthquake is shedding light on the behavior of the San Andreas Fault

PASADENA, Calif. (KABC) -- A powerful earthquake in Myanmar earlier this year is leading scientists to rethink how we predict future earthquakes.

A new study from CalTech sheds light on the behavior of the Sagaing Fault, which is very similar to the San Andreas Fault.

In March, a devastating, 7.7 magnitude earthquake in Myanmar killed thousands and caused significant widespread damage. CalTech's new study using satellite images is revealing how the fault moved, and the big implications for places like California.

"We take images before and after the earthquake and we match very accurately those images and we can measure the ground displacement," said Jean-Philippe Avouac, a professor of geology and mechanical and civil engineering at CalTech.

Researchers at CalTech found that the Sagaing Fault shifted more than 500 km, far beyond what they thought was possible. This is a major finding as it suggests faults like the San Andreas could produce larger and more complex quakes.

"So this area was identified as a seismic gap, and they're prone to producing a large earthquake," said Avouac. "It did happen, but it's much longer than we expected. So what's surprising is that the earthquake was able to re-rupture segments that ruptured in the '30s."

The research also challenges existing models used to predict earthquakes, which are based on past events. Instead, this study suggests that earthquakes might not just repeat what's happened before, they could actually release much more energy, or be comprised of smaller clusters of quakes.

"Maybe the earthquake would rupture over a larger distance and could rupture the southern portion that hasn't ruptured in a long time, so you had plenty of time to build up stress," said Avouac. "The message is that maybe the next earthquake would rupture the whole thing, or a sequence of smaller earthquakes, and it's hard to tell."

The study is already reshaping how scientists think about earthquake risks and could lead to not only more accurate forecasting models, but how we can better prepare our infrastructure as well.