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Forecasting and understanding the seIsmic cycle through b-value

Objective

Seismology is a branch of science with many open questions, and predicting earthquakes is still a utopia. We know earthquakes interact with each other by changing the state of stress in their surroundings. Strong earthquakes are, for example, followed by countless smaller events, a posteriori called aftershocks, whose number decays with time. We have shown that aftershock sequences are systematically associated with changes in the average earthquake size distribution, an increase in the so-called b-value, unless a second large mainshock is still coming, in which case the b-value decreases. This exciting finding allows the use of the b-value for real-time discrimination between foreshocks and aftershocks, answering the most asked question following a moderate/big quake: Was this the mainshock or a bigger event has yet to come? The observation also aligns with the concept that the b-value can be used as an indirect stress meter in the earth’s crust.

Building on these findings, I propose here now to develop and test a general model of the evolution of the b-value through the seismic cycle, building on the following hypothesis: 1) a stable background or gradual decreasing b-value during inter-seismic times, 2) occasionally a pre-mainshock decrease, 3) an increase after the mainshock and 4) recovery to the background value. According to my hypothesis, monitoring b-values in real-time allows us to understand and monitor for the first where a fault is in the seismic cycle. This would represent a major breakthrough in Earth science, with profound implications for understanding earthquake processes, seismic hazard assessment and risk mitigation. To achieve this ambitious goal, FARIA comprises a set of closely coordinated activities in data analytics, computational modeling, laboratory experiments, and formal testing. If successful, FARIA will represent transformative progress in earthquake predictability.

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(opens in new window) ERC-2024-ADG

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Host institution

UNIVERSITA DI PISA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 180 831,00
Address
LUNGARNO PACINOTTI 43/44
56126 PISA
Italy

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Region
Centro (IT) Toscana Pisa
Activity type
Higher or Secondary Education Establishments
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Total cost

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Beneficiaries (1)

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