Earthquake Count in Yellowstone Estimated at 8,600 by Humans; AI counterclaims Underestimation
In a groundbreaking study published earlier this month in the journal Science Advances, researchers from the University of Western Ontario, the Industrial University of Santander in Colombia, and the U.S. Geological Survey have significantly improved the detection and analysis of earthquakes in the Yellowstone caldera. By applying machine learning techniques to 15 years of seismic data (2008–2022) from the caldera, they have uncovered over 86,000 earthquakes—about 10 times more than previously recorded using conventional methods.
The increased catalog of seismic activity has allowed for the application of statistical methods to quantify and find new swarms of earthquakes. These swarms, clusters of small, interconnected quakes occurring in bursts over short periods, appear to be triggered by fluid movements underground interacting with faults.
The study reveals that over half of Yellowstone's earthquakes are part of swarms, sequences of earthquakes that don't follow the mainshock-aftershock seismic pattern. The detailed high-resolution earthquake record from AI analysis reveals chaotic swarming behavior especially concentrated along underdeveloped or immature fault lines beneath the caldera.
Bing Li, a Western University engineer and expert in fluid-induced earthquakes and rock mechanics, stated that the old method of manually analyzing seismic data for earthquakes is not scalable. Li also explained that the retroactive identification of these earthquakes was accomplished using artificial intelligence and deep learning algorithms.
The increased understanding of volcanic and seismic systems gained from this study strengthens seismologists' understanding of these systems. Li stated that understanding patterns of seismicity can improve safety measures, inform the public about potential risks, and guide geothermal energy development.
Calderas, like Yellowstone's, are ancient volcanoes that erupt and then collapse into their emptied magma chamber, leaving a large depression in the land. Many features related to volcanoes can cause earthquakes, and most of the ones at Yellowstone are brittle-failure events, which occur when stress in the crust causes rocks to break.
This study provides a more comprehensive and precise spatiotemporal picture of seismicity in the Yellowstone caldera, improving monitoring capabilities and potentially informing hazard assessment for this supervolcano region. The new insights into earthquake swarms and the activity of immature fault structures will undoubtedly contribute to a deeper understanding of Yellowstone’s seismic and volcanic behavior.
- As the study published in Science Advances by researchers from various institutions enhances our understanding of earthquakes in the Yellowstone caldera, Earth-science and seismology fields may benefit from technology advancements and artificial intelligence applications, such as those demonstrated by Gizmodo.
- By employing machine learning techniques to environmental-science data, future research in this area could lead to even more accurate earthquake detection and analysis, potentially shedding light on seismic patterns within other geographical locations.
- The augmented catalog of seismic activity uncovered in the study highlights the importance of technology integration in the exploration of earthquake swarms, which holds valuable insights for the improvement of safety measures and risk assessment, especially in supervolcano regions like Yellowstone.
- The application of artificial intelligence and deep learning algorithms, as exemplified in this research, underscores the significance of maintaining an interdisciplinary approach to earth-science and technology, with the potential to revolutionize our understanding of geological phenomena like earthquakes and volcanic behavior.
