Quick quake calcs: GNSS data speed up assessment

Global satellite navigation systems (GNSS) can be used to help quickly characterize damaging earthquakes when seismic sensors aren’t available, according to new research. GNSS data especially help in areas where broadband seismometers are sparse.
 

By Jeng Hann Chong, Ph.D. Candidate, University of New Mexico (@Chong_Javier)
 

Citation: Chong, J. H., 2023, Quick quake calcs: GNSS data speed up assessment, Temblor, http://doi.org/10.32858/temblor.314
 

Earthquakes generate body waves that travel through Earth. They can be used to study Earth’s internal structure, just like a CT scan that images your body. These seismic waves also reveal properties of the event, such as location, depth, ground motion and magnitude. These parameters are crucial for quickly characterizing an earthquake, especially if the event has the potential to produce damaging shaking, tsunamis or other associated hazards, says Revathy Parameswaran, a Research Associate at the University of Alaska Fairbanks and the lead author of a new study.
 

This GNSS station and seismic station are considered closely located at a distance of about 2 kilometers (about 1.2 miles) apart. Both stations collected data during the 2021 magnitude-8.2 Chignik earthquake in Alaska. They’re located about 121 kilometers (about 75 miles) away from the hypocenter. Credit: Parameswaran et al. (2023)
This GNSS station and seismic station are considered closely located at a distance of about 2 kilometers (about 1.2 miles) apart. Both stations collected data during the 2021 magnitude-8.2 Chignik earthquake in Alaska. They’re located about 121 kilometers (about 75 miles) away from the hypocenter. Credit: Parameswaran et al. (2023)

 

For highly energetic, large-magnitude earthquakes, researchers use strong-motion sensors to estimate earthquake magnitude, shaking intensity, and the area likely to experience that shaking. But not all places around the world have dense distributions of these strong-motion sensors, leading to gaps in ground motion information.

Much in the same way that the blue dot on your smartphone’s map app can tell where you are or if you’ve moved, Global Navigation Satellite Systems (GNSS) stations detect signals from satellites orbiting Earth and can measure how much the ground moved after an earthquake. Parameswaran and a team of researchers wanted to test if the existing ground-based GNSS stations in Alaska can also be used to quickly deliver the same earthquake information as strong-motion sensors.
 

Quick quake characterization

Characterizing an earthquake quickly requires calculating its magnitude and ground motion. To do so, scientists use peak ground velocity — the maximum speed at which the ground moved. This information can potentially be used to create shaking intensity maps like ShakeMap, Parameswaran says. ShakeMaps are produced by the U.S. Geological Survey’s Earthquake Hazards Program and provide maps of ground motion and shaking intensity after significant earthquakes.

Strong-motion sensors are typically used to extract peak ground motion, especially when seismic stations experience significant shaking from either large-magnitude or nearby earthquakes. These sensors measure ground acceleration (they’re the same sensors in your smartphone that help rotate the screen), and a quick calculation converts acceleration into velocity. However, not all seismic stations have these types of sensors, and instead have broadband seismic sensors that measure ground velocity directly. However, large or nearby earthquakes shake the ground at scales far larger than the range that broadband sensors can record. This is where GNSS-derived peak ground velocity might help.

To test this idea, Parameswaran and her colleagues used data from the 2021 magnitude-8.2 Chignik earthquake in Alaska. They selected this earthquake because the large ground motion was recorded by multiple seismic stations and could be compared to the data collected by GNSS stations located nearby.
 

Seward, Alaska, was evacuated after the Chignik earthquake in the Aleutians for fear of a tsunami. Credit: Diego Delso, CC BY-SA 4.0
Seward, Alaska, was evacuated after the Chignik earthquake in the Aleutians for fear of a tsunami. Credit: Diego Delso, CC BY-SA 4.0

 

Alternative and additional

The researchers compared three pairs of instruments, each consisting of strong motion stations coupled with either collocated or closely located GNSS stations. All pairs recorded the Chignik earthquake. The magnitude of the earthquake and the presence of these paired stations facilitated the comparison between the two types of datasets for the same earthquake, Parameswaran says.

The team found that the peak ground velocity values obtained from the strong-motion sensors and calculated from GNSS were very similar. The estimated magnitude from using only GNSS versus GNSS and seismic data together differs only by a 0.4 magnitude, according to a press release. This difference is within the accepted uncertainty limits in this type of analysis, according to Parameswaran.

For GNSS, Parameswaran said in a press release, “data is largely sampled once or five times every second — 1 to 5 hertz — while strong-motion instruments record data 50 to 100 times a second, or 50 to 100 hertz.” This results in some variation in the magnitude of the peak ground motions recorded by the different sensors.

By swapping out strong-motion sensor data with GNSS information, the team found little change to the maps of peak ground velocity. This suggests that GNSS can be used when seismic sensors are unavailable, or the datasets can be combined. However, if an earthquake produces weaker ground motions at a given GNSS station (either due to smaller magnitude, or greater distance between earthquake and station), that movement would not necessarily be recorded.
 

Each panel shows the different tests of peak ground velocity from Parameswaran et al., (2023). Panel (a) includes only the three GNSS stations that were either closely located or collocated with strong-motion sensors. Panel (b) includes their strong-motion counterparts in the three chosen station pairs. Panel (c) includes all operational GNSS stations less than about 700 kilometers from the epicenter. In panel (d), the GNSS stations from (a) have been swapped with the corresponding strong-motion sensor data in (b). Triangles denote the GNSS stations and squares are the co-located strong-motion sensors. Contour lines show peak ground velocity derived from the different methods. Credit: Parameswaran et al. (2023).
Each panel shows the different tests of peak ground velocity from Parameswaran et al., (2023). Panel (a) includes only the three GNSS stations that were either closely located or collocated with strong-motion sensors. Panel (b) includes their strong-motion counterparts in the three chosen station pairs. Panel (c) includes all operational GNSS stations less than about 700 kilometers from the epicenter. In panel (d), the GNSS stations from (a) have been swapped with the corresponding strong-motion sensor data in (b). Triangles denote the GNSS stations and squares are the co-located strong-motion sensors. Contour lines show peak ground velocity derived from the different methods. Credit: Parameswaran et al. (2023).

 

Future hazard assessments

Broadband seismometers can “clip” the recorded seismic signal if the motions are so big that they are beyond the recording capabilities. “GNSS velocities do not clip,” says Brendan Crowell, a research assistant professor at the University of Washington who was not involved in the new study. Strong-motion sensors are used to overcome clipping, but processing the sensor’s data could result in some loss of data, Crowell says. “With strong-motion sensors, when you integrate them to velocity or displacement, if the motions are large, the integration will blow up due to the rotations and tilts experienced,” he explains. As a result, seismologists must filter the data. GNSS provides a direct measurement of ground velocity that could provide that missing information, he adds.

Parameswaran says that GNSS can be integrated with strong-motion sensors in places like California to improve rapid earthquake characterization. Crowell has done similar work in the Intermountain Western United States (Crowell et al., 2023) and says this region would benefit from the GNSS-derived peak ground velocity, as there are not many strong-motion sensors in the region.

Despite the successful test on the Alaskan earthquake, Crowell says that more research is needed to determine how to incorporate GNSS data into intensity maps such as ShakeMap.
 

References

Parameswaran, R. M., Grapenthin, R., West, M. E., and Fozkos, A., (2023), Interchangeable Use of GNSS and Seismic Data for Rapid Earthquake Characterization: 2021 Chignik, Alaska, Earthquake, Seis. Res. Lett., doi:10.1785/0220220357
 

Further Reading

Crowell, B., DeGrande, J., Dittmann, T., & Ghent, J. (2023). Validation of Peak Ground Velocities Recorded on Very-high rate GNSS Against NGA-West2 Ground Motion Models. Seismica, 2(1). https://doi.org/10.26443/seismica.v2i1.239
 

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