Researchers are developing new algorithms to enhance earthquake prediction

New research published in Seismological Research Letters provides new information about precession (PSI), a phenomenon characterized by a sudden increase in the rate and magnitude of earthquakes in a local area before a larger seismic event occurs.

“Our research is essential to advance our understanding of how seismic activity escalates in the lead-up to a major earthquake,” said lead author Dr Anne-Marie Christofferson, hazard and risk scientist at GNS Science.

The study proposes two new techniques for automatic detection of PSI in earthquake catalogs. By studying real and simulated data, researchers discovered that large earthquakes can have several PSI definitions.

They discovered a link between the size of the prior zone and the time before a major earthquake: smaller zones correspond to longer prior times, and vice versa.

This is an important step forward in understanding how seismic activity builds up before major earthquakes, with immediate implications for improving medium-term earthquake prediction.

These forecasts are important to the public because they allow for improved preparedness and more effective risk management techniques.

The study was conducted mostly in Aotearoa, New Zealand, a country known for high seismic activity due to its location on the Pacific Ring of Fire, where tectonic plates frequently collide.

This geographical background underscores the importance of the findings, as New Zealand has been hit by several severe earthquakes in the past, including the terrible 2011 Christchurch earthquake which was a 6.3 magnitude earthquake and caused widespread damage to infrastructure in the region.

By improving understanding of PSI, the research hopes to strengthen New Zealand's national seismic risk model, which is critical in estimating seismic risk across the country.

The results were published on October 11, 2024, and were part of ongoing earthquake prediction research, expanding on previous work that attempted to examine and understand the seismic sequences that trigger large earthquakes.

Historically, PSI detection has relied on manual and time-consuming methods, which has limited the analysis of these events.

Researchers aim to better understand how the size of primary seismic zones and the time before a major earthquake are related.

Dr. Christophersen and her team created two algorithms to automatically detect PSI in earthquake catalogs, representing a major departure from previous manual identification methods.

These methods have been used on both real earthquake data and simulated datasets based on the known physics of earthquake events.

Their findings indicated that most large earthquakes had multiple PSI realizations, each with a different time, area, and magnitude precedent.

The algorithms showed a balanced relationship between the time before an earthquake and the area where previous earthquakes occur. This means that as the time gets closer to a large earthquake, smaller areas experience greater seismic activity.

This finding supports the original principles of the EEPAS (Each Earthquake Precursor According to Scale) model, which predicts how small earthquakes can signal the likelihood of a larger earthquake.

“Our next step is to incorporate our findings into the EEPAS model to improve medium-term earthquake prediction, which is a direct input into the overall earthquake prediction and national seismic hazard model,” Christoffersen said.

“These resources help us make better decisions about where to build and prioritize strengthening existing infrastructure to make New Zealand more resilient to large earthquakes.”

References:

1 Algorithmic identification of the ex-scaling phenomenon of increasing phenomenon in earthquake catalogs – Anne-Marie Christoffersen, David A. Rhodes, Sebastian Henzel Earthquake Research Letters 2024 – October 8, 2024 – https://doi.org/10.1785/0220240233

2 New research enhances understanding of increased seismic activity before large earthquakes – GNS Science – October 11, 2024

3 Christchurch, New Zealand – Britannica – accessed 13 October 2024

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