SOURCE-LINKED INTELLIGENCE
Intraplate Earthquakes: the signature of the static fatigue of continents
ve earthquakes are the result of the static fatigue of continents under stress left by previous phases of deformation in the geological history of a region. I will leverage the latest developments in artificial intelligence to grow the densest and largest global catalog of earthquakes in SCRs from seismological and InSAR data (WP1). I will develop a tool to predict realistic time series of surface loads affecting the crust (WP2). I will implement static fatigue in the form of brittle creep in a numerical model (WP3) to test whether continents are effectively failing today under paleo-stress left by fossil plate boundaries perturbed by todays' modulations of crustal stress, comparing model outcomes with data collected in WP1. This interdisciplinary project combining seismology, geodesy, machine learning and numerical modeling will allow to (1) grow a physical understanding of the seismogenic behavior of SCRs, (2) tune estimates of seismogenic potential (and eventually hazard) for any given SCR (3) test whether a changing climate will affect the seismogenic potential of SCRs in the f
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 1999434
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.