Groundbreaking Research on Popocatépetl Volcano
For the first time, a Mexican scientific team has successfully constructed a detailed 3D model of the interior of the Popocatépetl volcano, thanks to an innovative combination of artificial intelligence, advanced seismology, and fieldwork at high altitudes, according to an article published in the UNAM Gaceta.
Led by experts from the Instituto de Geofísica (IGf) at UNAM, this research marks a milestone in the study of active volcanoes and opens new possibilities for disaster prevention. “The model is like a 3D X-ray that allows us to observe how seismic waves propagate within the volcano,” explained Marco Calò, principal investigator of the project.
Identifying Key Volcanic Structures
This visualization enables the identification of internal structures such as magma chambers, ascension conduits, and magma accumulation zones, which are crucial for understanding the Popocatépetl’s dynamics.
High-Risk Expeditions and Cutting-Edge Science
Developing the model involved high-risk expeditions on foot up to 20 kilometers at altitudes above 4,200 meters in extreme conditions typical of an active volcano. Researchers carried backpacks weighing over 20 kilograms to install and maintain seismic stations at strategic points.
Since 2019, 18 seismic stations have been deployed in the area, with eight installed by the UNAM team itself. These instruments capture over 100 measurements per second, generating a massive volume of data that is automatically processed using artificial intelligence algorithms.
Key Contributions from Team Members
Karina Bernal, a graduate student in Earth Sciences, developed a system that classifies different types of seismic signals, such as those generated by fractured rocks or moving gas bubbles. This automation significantly reduces analysis time, completing what once took months in just three hours.
Leonarda Isabel Esquivel, another graduate, used surface wave velocities to generate a seismic tomography that refines the Popocatépetl model. Meanwhile, Nizar Karim Uribe, an engineering student, participates in technical tasks to extract and store data from on-ground stations.
From Science to Civil Protection
One of the most significant contributions of the model is its utility for volcanic risk management. By better understanding magma routes and speeds, researchers can anticipate movements implying increased volcanic activity, such as magma migration towards the surface.
“The model does not make decisions, but it provides critical information that can influence the activation of alerts, expansion of evacuation zones, or delineation of danger areas,” emphasized Calò.
While similar projects exist for volcanoes in other countries, this is the first of its kind conducted on Popocatépetl using an integral methodology, supported by artificial intelligence. The UNAM team thus establishes itself as an international reference in using advanced technologies for volcanic surveillance.
The researchers plan to build 4D models next – 3D representations incorporating the time variable. This would enable real-time monitoring of the volcano’s internal evolution and further enhance response capabilities in case of emergencies.
- Q: What is the significance of this 3D model of Popocatépetl? A: This model provides a detailed understanding of the volcano’s internal structure, enabling better prediction of eruptions and identification of high-risk zones.
- Q: How was this 3D model created? A: The model was developed through a combination of advanced seismology, high-altitude fieldwork, and artificial intelligence algorithms.
- Q: What makes this research unique? A: This is the first comprehensive 3D model of Popocatépetl, created using an integral methodology supported by artificial intelligence.
- Q: How will this model benefit civil protection? A: The model will help anticipate volcanic activity, define danger zones, and support decision-making for evacuation and alert activation.
- Q: What are the future plans for this project? A: Researchers aim to create 4D models, incorporating the time variable for real-time monitoring of the volcano’s internal evolution.
