The Pacific Northwest boasts an extensive network of more than 600 seismic monitoring stations that help researchers track tectonic and volcanic phenomena, including earthquakes.
The Pacific Northwest boasts an extensive network of more than 600 seismic monitoring stations that help researchers track tectonic and volcanic phenomena, including earthquakes. This data provides key insights into regional faults and feeds into early warning systems, which can give a community precious moments to prepare before a natural disaster strikes. A significant threat to this region, however, sits miles offshore, where the Juan de Fuca plate is subducting beneath the North American plate, forming the Cascadia Subduction Zone.
Monitoring activity at ocean floor faults is challenging, and the existing methods don’t often yield enough data for detailed analyses. To overcome this hurdle, researchers are experimenting with a technique called Distributed Acoustic Sensing, or DAS, that involves measuring ocean bottom vibrations with fiber optic cables, which line the ocean floor for global telecommunications. Recent advances enable researchers to collect data from live cables and use artificial intelligence to capture distant earthquakes that would otherwise escape notice.
In a recent study, University of Washington researchers tapped into the Ocean Observatory Initiative’s Regional Cabled Array, which spans the offshore plate boundary and transmits data via fiber optic cable. Unlike previous experiments that relied on offline or “dark fibers” for data collection, this new study demonstrates that DAS technology can operate without interfering with the OOI network.
The researchers published these findings February 28 in Seismological Research Letters.
Read More: University of Washington
Image: This aerial photo shows the Homer Spit in Alaska, which is just south of the Cook Inlet. Although they are not visible in the photo, fiber optic cables beneath the water on the top left of the image provided data for these experiments. (Credit: Qibin Shi via University of Washington)
