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Smart new technology turns underwater cables into earthquake detectors

Smart new technology turns underwater cables into earthquake detectors


As part of a project that could greatly accelerate the detection of lethal tsunamis, seismologists at the California Institute of Technology and optics experts at Google have come up with a way to transform the operation of submarine communication cables into earthquake detectors without using special equipment.

Earthquakes and tsunamis are among the most devastating events humanity faces, and they are also unpredictable. With little or no warning, a crust shifting or subsea landslide can cause death and devastation on an appalling scale across the entire ocean basin.

For this reason, scientists and engineers are working on more advanced and comprehensive detection and early warning systems. A particularly attractive option would be to find a way to transform Earth’s vast network of submarine communications cables into a giant seismic network.

Although we live in a highly interconnected world where many people believe that it is all wireless and satellite internet, 99 percent of all external data transfers pass through undersea cables. With the exception of high polar regions, the oceans are criss-crossed by cables, and there are more snakes around the coasts.

In contrast, seismographs and ocean seismic networks such as the Depth Oceanic Tsunami Reporting and Reporting System (DART), operated by the US National Oceanic and Atmospheric Administration’s National Center for Data Buoys, can provide only incomplete and remote coverage of earthquakes. Oceanic events such as earthquakes and tsunamis.

The biggest problem is that shock waves can only move at the speed of sound, which means there is little warning in the event of a tsunami threatening the coast. If submarine cables can detect such events, they will be much closer to the source and warnings will flash ashore at the speed of light.

The idea of ​​using submarine cables is not new, but most technologies require the installation of special equipment, the use of broken cables, or both. The Caltech / Google method is based on the optical fiber cables that telecom companies have been laying in since the 1980s.

As part of their normal operation, the laser pulses used to transmit multiple channels of data are polarized. When these impulses reach the other extreme, they are routinely monitored. If the device is operating properly and the cable is not disturbed, the laser pulses will still be properly polarized. In the event of a malfunction or an annoyance of the cable, the polarization changes. Meaning that seismic events can be monitored on a live cable using standard equipment.

Working with Corrie Cable, which stretches along the western coast of North and South America from Los Angeles to Valparaiso, the team was able to analyze the polarization of pulses along the cable at a rate of up to 20 times per second. Most of the time, this was still normal, but if an earthquake or large ocean waves occurred, they caused a major and sudden change in polarization, which researchers were able to determine its source. Over a period of nine months, they detected 20 medium to large earthquakes along the cable, the largest of which was a 7.7 magnitude event off the coast of Jamaica.

The next step will be to develop a machine learning algorithm to allow cables to be monitored automatically, ignoring any disturbances caused by ships or crabs that move the cable.

“This new technology can really convert the majority of submarine cables into geophysical sensors thousands of kilometers long to detect earthquakes and possibly tsunamis in the future,” says Zhongwen Zhan, an associate professor of geophysics. “We believe this is the first solution for ocean floor seismic monitoring that can be implemented practically worldwide. It could complement the existing network of seismometers and tsunami monitoring buoys to make the detection of much-submerged earthquakes and tsunamis much faster in many cases.”

The research has been published in the journal Science.

Source: California Institute of Technology

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