Seismologists Can’t Predict the ‘Big One’ But Can Issue Warnings in Seconds
When seismologists noticed a swarm of about 200 small earthquakes a few weeks ago near the Salton Sea, a lake located at the end of the San Andreas Fault, a rare warning was issued. And Californians quickly took notice.
The swarm data was collected in Caltech’s Seismology Lab in Pasadena in collaboration with the U.S. Geological Survey office located on campus. It’s in this same lab that an innovative technology is being developed for an earthquake early warning system throughout the West Coast.
The system collects digital data from hundreds of sensors placed at various locations in California, Oregon and Washington and sends it back to processing sites like Caltech. And 53 of these sensors are currently located at substations throughout Southern California Edison’s 50,000-square-miles of service territory.
“We’ve made tremendous progress,” said Dr. Egill Hauksson, a seismologist at Caltech. “The early warning notifications are made with very little data as the earthquake begins, but we want to ensure the data is accurate. Most of the time it is accurate, but we are still trying to work out the kinks.”
Caltech seismologist Dr. Egill Hauksson explains a map of a moderate earthquake.
That accuracy is being analyzed with various Beta testers, including engineers at SCE. Currently, the system is able to provide an earthquake early warning within five seconds of sensing a tremor. In comparison, the final epicenter’s magnitude can be determined within two minutes by the old system. A ShakeMap that shows the affected area is available in five minutes.
The numbers are astounding when compared to the data that was available during the Northridge earthquake in 1994. At that time, it would take up to an hour to get data on the magnitude and the earthquake’s epicenter. It took one month to determine the affected geographic area.
One major hurdle for the early warning system is being able to send out the warning to millions of people within seconds. Systems currently available take several minutes. And computers are not seismologists and errors can still be made, such as mistaking a couple of rumbling trucks along a gravel road for a small earthquake. For now, humans are sometimes better able to interpret the data.
“It’s hard to get computers to tell the difference,” said Doug Given, USGS early earthquake warning coordinator. “The new algorithms are getting better at reading the data.”
The early warning sensors look like cylindrical canisters that are placed about 9 feet underground at SCE’s various substations. The sensors then track ground motions both large and small and also determine the direction of a shake. The data is then sent back to Caltech where computers track the information every second for 24/7.
Although the technology is still a couple of years from being fully implemented, SCE sees a major use for this system in protecting its personnel. If an employee is in an underground vault inspecting equipment or climbing a power pole, the early warning would allow them to get out of harm’s way. The data would also determine the affected area, aiding efforts to reroute power.
“The big one is our people … being able to warn our employees to take cover,” said Dr. Matthew Muto, an SCE senior engineer who has been working with Caltech and USGS on seismic issues. “To be able to get them out of very exposed areas.”
“Personally, I think this technology is pretty cool,” added Muto, a former graduate student and research scientist at Caltech. Some of his classmates worked on the algorithms in the system and “it’s been interesting to see it get close to implementation.”
Over the next three years, Caltech and USGS plan to add 60 more of the early earthquake warning sensors.
And although Californians would love to know when the “Big One” will happen, seismologists say this is the “Holy Grail” of seismology. What they can do is track individual earthquakes and whether a certain area has had more earthquakes compared to previous years. And the early warning system is playing a large role.
“We are trying to do things in seconds and seconds go by very fast,” said Hauksson.
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