Earthquakes are one of the most destructive natural hazard on Earth and, despite tremendous progress on both fundamental aspects of the physics of earthquakes and on hazard mitigation, earthquakes remain unpredictable and pose a significant threat for a large part of the world population. One way to advance toward a more resilient society against earthquakes is to grow our understanding of tectonic faulting in order to better characterize the associated hazard.
In the past 20 years, tremendous efforts have been made in the development of ground deformation measurements in tectonically active regions, including ground- and space-based measurements such as GNSS or satellite imagery. Plate tectonics stress active faults by bending the crust until faults fail abruptly during an earthquake, radiating devastating seismic waves. However, recent observations actually revealed that faults can slip slowly, without radiating seismic waves, gently releasing stress. In parallel to these observations, our understanding of the mechanics of faulting made giant leaps toward more and more realistic models of loading and release of stress by slip on faults. We now know slow slip and earthquakes interact and both participate in the release of stress along faults, but the interplay between these and the underlying mechanisms controlling the mode of slip along faults are not understood.
In short, what are the physical mechanisms controlling whether a fault will generate slow harmless slip or a devastating earthquake? And more importantly, what are the most important data we should collect in order to grow our understanding and to improve the predictive ability of our models?
In Geo4D we have built tools to feed measurements of ground deformation into physics-based models of faulting, toward a data assimilation approach of ground deformation and earthquakes models. Similarly to what meteorologists do everyday, the question is whether we can build physics-based models that will be trained by incoming data. After an intense phase of data collection in the field in Turkiye and of processing of global data base of satellite imagery, we have produced a wealth of observations of slow slip on continental settings in various places, including in the Himalayas, Pakistan, Turkiye and the Philippines. Our data base has allowed us to describe the finest possible scales of fault slip along several faults in the world and to test data assimilation methods to see whether we can, or not, forecast slow slip. This task is a never ending one and while the objectives of the Geo4D project were met, we aim to pursue this endeavor.
