UH scientists propose new tools to understand, predict large earthquakes

A dense network of GPS sites and a new algorithm significantly increases our knowledge

0
2415
SOEST GPS
Jonathan Weiss while monitoring GPS-Ground Motion sensors in the Andean Highlands. (Photo credit: J. Weiss)

Earth scientists from the University of Hawaiʻi at Mānoa say they have uncovered a new piece of the puzzle that may aid scientists in determining when and where the next destructive earthquake will occur.

The team, led by Jonathan Weiss, an alumni of the UH Mānoa School of Ocean and Earth Science and Technology (SOEST), probed the Earth’s structure beneath a portion of the southern Andes. They recently co-authored a study in Science Advances that investigated the characteristic surface motion that occurs in the weeks to months to years after very large earthquakes, combining Global Positioning System (GPS) measurements with a new numerical modeling method.

The GPS instruments are similar to but much more precise than those in mobile phones or automobile satellite navigation systems.

Weiss, SOEST researcher James Foster, graduate student Jonathan Avery, and international colleagues used a network consisting of hundreds of permanent GPS stations installed across South America—from the Chilean coastline in the west to the rainforests of Brazil in the east—to measure horizontal and vertical ground motions as small as a few millimeters per year. Studying these motions can reveal detailed information about numerous processes ranging from the forces responsible for mountain building over long timescales, the short-term behavior of rocks in response to large, earthquake-induced changes in stress, and even seasonal cycles of rainfall in the Amazon basin.

Chilean earthquake provides opportunity for investigation

The team analyzed continuously recorded GPS data from after the 2010 magnitude 8.8 Maule earthquake in Chile, which was the largest event to occur in that region in 50 years, using a novel geophysical data inversion technique. Their modeling approach used surface motion measurements from GPS data to reveal details of the physical properties of the rock in the crust and mantle, and how it responded to the stresses generated by the earthquake.

The newly published results of their study confirm that the combination of a dense network of GPS sites with the new inversion algorithm can significantly increase our knowledge of subduction zone and deep crustal and upper mantle structure, which ultimately controls the distribution and frequency of large earthquakes and volcanic activity.

Leave a Reply