One of the key questions in fault mechanics is how earthquakes begin. This is central to our understanding of earthquakes, including the long and controversial issue of their predictability. Much of what we know about earthquake nucleation comes from the observation of foreshock events before large earthquakes. Yet, one major challenge is the inherent difficulty of identifying earthquakes as foreshocks before the mainshock occurs.
Two competing models have been proposed to explain foreshock sequences. The first is the “cascading model”, where successive stress changes from foreshocks lead to a cascade of random failures, ultimately triggering the mainshock. The second is the “nucleation model”, where foreshocks are driven by an aseismic nucleation phase involving gradual fault slip that accelerates into a dynamic rupture. These models have crucial implications for seismic hazard assessment. In the cascading model, foreshocks occur randomly and cannot be used for prediction. Conversely, the nucleation model suggests a causal relationship between aseismic slip and foreshocks, offering potential for forecasting large earthquakes.
The PRESEISMIC project aimed to address key limitations in our understanding of earthquake nucleation, namely the difficulty in quantifying the proportion of seismic versus aseismic slip during rupture initiation and the challenges of detecting and characterizing small microearthquakes (M<2). By leveraging the explosion of near-fault observations and combining seismic and geodetic datasets, the project aimed to clarify the contributions of seismic and aseismic processes during foreshock sequences.
The main conclusion of the project is that the “nucleation model” cannot explain most foreshock observations. Instead, the “cascading model” appears to play a dominant role, with foreshocks often triggering each other randomly. However, our research also revealed that some foreshock sequences deviate from this pattern, likely driven by slow-slip events that load nearby fault areas, enhancing seismic activity and increasing the likelihood of a larger rupture. While this “slow-slip event loading model” does not offer strong predictive power, the rapid detection of transient aseismic slip remains valuable for anticipating an increased level of seismic activity.
This project has advanced our understanding of the processes leading to earthquakes and highlighted the limitations of using foreshock sequences for short-term earthquake prediction. Its findings underscore the need for seismic hazard preparedness through robust engineering standards and long-term risk mitigation strategies. Another key outcome of the project is the development of methods to produce and analyze high-resolution seismicity catalogs. These tools can be applied in environments beyond tectonic faults and are particularly valuable for gaining new insights into magma migration, improving eruption forecasting on active volcanoes.
