Bayesian inference of earthquake source parameters: kinematic and dynamic finite fault models

• Applicant: Dr. Alice-Agnes Gabriel
• Subject Area: Geophysics
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 391058966

• Final Report Year: 2024

Final Report Abstract

Key outcomes of our collaborative efforts include the development of innovative Bayesian frameworks for earthquake source inversion, integration of advanced high-performance computing (HPC) techniques, and large-scale 3D dynamic rupture simulations. The project enhanced the earthquake simulation software SeisSol to incorporate dynamic modeling constraints and support reproducible, data-driven seismic hazard assessment. Novel applications included physics-based simulations of large earthquakes such as the 2016 Mw 7.8 Kaikōura and 2019 Ridgecrest events, yielding insights into fault dynamics and ground motion characteristics critical for seismic risk mitigation. The project led to a total of 30 peer-reviewed publications, including publications in Nature, Geophysical Research Letters and Nature Communications. Despite challenges from the COVID-19 pandemic, the project successfully fostered the training of young scientists, with outcomes such as PhD graduations and technical contributions to open-source software. Through this work, BAIES has set a foundation for future explorations of earthquake dynamics and advanced HPC applications in seismology, with broader implications for both scientific understanding and societal resilience to seismic hazards.

Publications

• Bayesian Dynamic Finite‐Fault Inversion: 1. Method and Synthetic Test. Journal of Geophysical Research: Solid Earth, 124(7), 6949-6969.
  Gallovič, F.; Valentová, Ľ.; Ampuero, J.‐P. & Gabriel, A.‐A.
  
• Bayesian Dynamic Finite‐Fault Inversion: 2. Application to the 2016 Mw 6.2 Amatrice, Italy, Earthquake. Journal of Geophysical Research: Solid Earth, 124(7), 6970-6988.
  Gallovič, F.; Valentová, Ľ.; Ampuero, J.‐P. & Gabriel, A.‐A.
  
• Dynamic viability of the 2016 Mw 7.8 Kaikōura earthquake cascade on weak crustal faults. Nature Communications, 10(1).
  Ulrich, Thomas; Gabriel, Alice-Agnes; Ampuero, Jean-Paul & Xu, Wenbin
  
• Landers 1992 “Reloaded”: Integrative Dynamic Earthquake Rupture Modeling. Journal of Geophysical Research: Solid Earth, 124(7), 6666-6702.
  Wollherr, Stephanie; Gabriel, Alice‐Agnes & Mai, P. Martin
  
• FD3D_TSN: A Fast and Simple Code for Dynamic Rupture Simulations with GPU Acceleration. Seismological Research Letters, 91(5), 2881-2889.
  Premus, Jan; Gallovič, František; Hanyk, Ladislav & Gabriel, Alice-Agnes
  
• Constraining families of dynamic models using geological, geodetic and strong ground motion data: The Mw 6.5, October 30th, 2016, Norcia earthquake, Italy. Earth and Planetary Science Letters, 576, 117237.
  Tinti, Elisa; Casarotti, Emanuele; Ulrich, Thomas; Taufiqurrahman, Taufiq; Li, Duo & Gabriel, Alice-Agnes
  
• Broadband Dynamic Rupture Modeling With Fractal Fault Roughness, Frictional Heterogeneity, Viscoelasticity and Topography: The 2016 Mw 6.2 Amatrice, Italy Earthquake. Geophysical Research Letters, 49(22).
  Taufiqurrahman, T., Gabriel, A. ‐A., Ulrich, T., Valentová, L. & Gallovič, F.
  
• Dynamics, interactions and delays of the 2019 Ridgecrest rupture sequence. Nature, 618(7964), 308-315.
  Taufiqurrahman, Taufiq; Gabriel, Alice-Agnes; Li, Duo; Ulrich, Thomas; Li, Bo; Carena, Sara; Verdecchia, Alessandro & Gallovič, František