The expected working pace was strongly influenced by the COVID-19. Most of the PhD students and post-docs began their work just a few months before the pandemic struck. During this critical initial phase of research, they found themselves in a new country, confined to their homes, with only video interactions with me and among themselves. This situation significantly affected their morale and limited opportunities for discussing how to advance and perform practical analyses. Despite these challenges, we focused on the development and preliminary application of methodologies to advance the project during the first part:
Development of Coherence Analysis and Clustering: We implemented and successfully applied coherence analysis and clustering of resuming features with unsupervised machine learning to the region of the L'Aquila 2009 magnitude 6.1 earthquake (Shi et al., 2020, JGR).
Algorithm for Seismological Data Analysis: We developed an algorithm to extend the analysis of seismological data related to the fault generating the L'Aquila earthquake, enabling the reconstruction of seismological observations from 1990 to 2021. This 31-year dataset will help infer the state of stress in the crust before and after the 2009 earthquake. Methodology development issues were addressed, and results have been published (Majstorovic et al., 2021, 2023).
High-Resolution Seismic Catalog: We created a high-resolution catalog of seismic signals for the six months preceding the L'Aquila earthquake to track stress evolution leading up to the main earthquake (Cabrera et al., JGR, 2022, Cabrera & Poli, GRL, 2023).
Study of Nucleation of Small Magnitude Earthquakes: Using the methodology from (3), we studied the nucleation of a small magnitude 4 normal fault earthquake, highlighting the complex nature of pre- and post-seismic processes (Sanchez-Reyes, 2020, SRL).
High-Resolution Seismic Catalog for Alto Tiberina Fault: We completed an unprecedented high-resolution seismic catalog containing over 400,000 events spanning four years of data in the Alto Tiberina low-angle normal fault. We are beginning to use this information to derive insights about physical processes and the state of stress in this fault system (Essing et al., JGR, 2022, 2024).
Characterization of Velocity Variations: We characterized velocity variations in the region of the L'Aquila 2009 earthquakes using ambient seismic noise. This study focused on the susceptibility of velocity changes to different stress forcing (e.g. periodic deformation, earthquakes), providing important information about the layering of physical properties in the crust for this fault system (Poli et al., 2020, JGR). The same method was applied to the seismic region in southern Apennines (Mikhael et al., 2024).
This project has made substantial progress in understanding the dynamics of the Earth's crust in seismically active regions. By focusing on the central Apennines, a region of both high seismic risk and significant potential for new discoveries, we have developed methodologies that offer deeper insights into fault mechanics and stress states. This research represents a crucial step towards a more effective understanding of the earthquake cycle in slowly deforming regions. The results obtained have been disseminated through scientific publications, conferences, and collaboration with other research institutions, ensuring that the findings are utilized to advance the field of seismology and earthquake hazard mitigation. The research of this project also brought to the new definition of the preparation of earthquakes published in Martinez-Garcon & Poli (2024).
