UN teams in Syria providing lifesaving assistance to affected children and families. PHOTO/UNICEF/AL-ASADI
By SPECIAL CORRESPONDENT
Just after 4 a.m. on February 6, residents near the town of Gaziantep, at the border of southern Turkey and Syria, awoke to the ground beginning to shake.
The magnitude-7.8 earthquake that would follow brought down buildings on either side of the border, and was responsible for over 47,000 deaths by the time the dust had settled, days later. Despite being located along known North and East Anatolian fault zones, geoscientists and seismologists had no way to predict when or how powerful this quake and its aftershocks would be.
According to a report by Popular Mechanics, even though science can’t predict these seismic energy eruptions, geophysicists like Srisharan Shreedharan are trying to make forecasts.
“Earthquakes are difficult to predict simply because the earth below our feet is very complex,” Shreedharan, an assistant professor at Utah State University, tells Popular Mechanics. “Scientists studying earthquakes will generally agree that this is impossible to do. Forecasting, on the other hand, is an achievable goal … [and] earthquake early warning systems are improving all the time, for example in Japan, California, Washington.”
These systems for anticipating earthquakes rely on both statistical and historical knowledge, as well as a strong understanding of earthquake mechanics, or the physics of earthquakes, which is Shreedharan’s focus. He examines the role friction plays in the movements of tectonic plates—the moving plates of rock under the earth responsible for earthquakes. Friction can mean the difference between plates holding in place, or slipping.
However, friction is not the only mechanic at hand during an earthquake event, Shreedharan says. Another consideration for scientists studying the movement of tectonic plates is “wave physics,” or the study of oscillations underneath the earth.
Similar to the way sound waves convey music to our ears by pushing and compressing the air around us, Earth’s crust and top soil are conduits for energy waves released during earthquake events.
These waves can move in three different directions: longitudinal (a compression through the medium), transverse (an up-and-down shear force), and surface level (which moves the ground perpendicular to the waves’ motion). Scientists who study these seismic waves—also known as seismologists—are interested in determining how these oscillations will impact everything from buildings to Earth’s crust. They use instruments like seismographs to measure the amplitude of the waves, and then determine how much the ground is moving.
Studying the wave mechanics of an earthquake can only happen once a quake is already occurring. Studying the friction of faults can help scientists better understand how these quakes happen in the first place.
Regaining frictional strength, or healing after a slip, would set up the fault to slip again in the future. To what degree a fault experiences frictional healing can depend on a variety of variables, such as the minerals in the earth, pressure, or temperature. If a fault cannot regain this frictional strength, then it won’t be able to slip again, because it has already released that energy, Shreedharan says.
“An inability to heal for a specific fault likely indicates that it inherently poses less seismic risk,” he adds, “but this does not eliminate the possibility that an earthquake could start elsewhere (a region with an ability to heal more) and rupture through this ‘zero-healing’ region.”
How to “predict” earthquakes
Nothing will send the hackles of a geophysicist up quite like asking whether it’s possible to predict when, where, and how strong a potential earthquake will be. While predicting these events in the same way we predict other natural disasters (such as hurricanes) isn’t possible, earthquake scientists are pursuing promising methods.
In addition to traditional forecasting and early-warning systems, one growing area of interest is using machine learning to help study the patterns of past earthquake events to better predict when another is likely to occur.
This approach has seen success in predicting earthquakes in retrospect using data; the algorithm was fed seismic data from the early 2000s, and was able to predict earthquakes that happened in the 2010s based on analysis of that data. The system proved it could plausibly demonstrate intelligence about future events. However, it does have limitations when it comes to fault zones with sparse recorded data. For events like earthquakes, which occur on a geological and not a human timescale, data is not always guaranteed.
Shreedharan’s recent work may also offer another avenue toward “prediction,” he says. In their paper, Shreedharan and colleagues found that materials like clay may have low frictional healing. As a result, shallow clay found around the world may contribute to so-called “slow slips,” an earthquake event that happens over a period of days to months.
“These findings could help better anticipate the behavior of shallow plate interfaces, which is important because shallow earthquakes are likely to result in tsunamis,” Shreedharan says.