Summary
Background microseismicity in subduction zones contains important information on the geometry, kinematics and dynamics of subduction systems. Low-magnitude earthquakes on the plate interface can outline highly locked asperities and thus define the locus of potential future large earthquakes. Rates of aseismic processes like creep or slow slip can be estimated using swarm-like seismicity and/or repeating events, thus complementing geodetic approaches. At depths beyond the megathrust, microseismicity can give important clues to the distribution and motion of fluids, ongoing mineral reactions, as well as the thermal and rheological structure of the downgoing slab.
In this project, I propose to use existing large seismic data sets from four subduction zone settings to systematically harvest microseismicity at an unprecedented scale through the use of an innovative automated approach that combines new machine learning approaches into a comprehensive earthquake detection and location framework. This effort will yield consistently picked and located microearthquake catalogs of superior event numbers and spatial resolution, which will be the base for several research avenues with the following outcomes:
- high-resolution seismicity catalogs and new 3D plate interface and slab surface geometry models
- a new generation of plate interface locking models from combining permanent GPS data inversion with seismicity constraints
- highly resolved regional-scale tomographic images of subduction zones
- new models of petrology, phase changes and thermal structure across several downgoing plates
- a framework for the comparison of seismicity features between different subduction zones
The results from the proposed project will be a big leap towards understanding the physics of subduction zone earthquakes as well as deep fluid circulation and mineral phase changes in downgoing lithosphere. They will also serve as valuable input for future models of earthquake and tsunami hazard.
In this project, I propose to use existing large seismic data sets from four subduction zone settings to systematically harvest microseismicity at an unprecedented scale through the use of an innovative automated approach that combines new machine learning approaches into a comprehensive earthquake detection and location framework. This effort will yield consistently picked and located microearthquake catalogs of superior event numbers and spatial resolution, which will be the base for several research avenues with the following outcomes:
- high-resolution seismicity catalogs and new 3D plate interface and slab surface geometry models
- a new generation of plate interface locking models from combining permanent GPS data inversion with seismicity constraints
- highly resolved regional-scale tomographic images of subduction zones
- new models of petrology, phase changes and thermal structure across several downgoing plates
- a framework for the comparison of seismicity features between different subduction zones
The results from the proposed project will be a big leap towards understanding the physics of subduction zone earthquakes as well as deep fluid circulation and mineral phase changes in downgoing lithosphere. They will also serve as valuable input for future models of earthquake and tsunami hazard.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/947856 |
| Start date: | 01-06-2021 |
| End date: | 31-05-2026 |
| Total budget - Public funding: | 1 311 480,00 Euro - 1 311 480,00 Euro |
Cordis data
Original description
Background microseismicity in subduction zones contains important information on the geometry, kinematics and dynamics of subduction systems. Low-magnitude earthquakes on the plate interface can outline highly locked asperities and thus define the locus of potential future large earthquakes. Rates of aseismic processes like creep or slow slip can be estimated using swarm-like seismicity and/or repeating events, thus complementing geodetic approaches. At depths beyond the megathrust, microseismicity can give important clues to the distribution and motion of fluids, ongoing mineral reactions, as well as the thermal and rheological structure of the downgoing slab.In this project, I propose to use existing large seismic data sets from four subduction zone settings to systematically harvest microseismicity at an unprecedented scale through the use of an innovative automated approach that combines new machine learning approaches into a comprehensive earthquake detection and location framework. This effort will yield consistently picked and located microearthquake catalogs of superior event numbers and spatial resolution, which will be the base for several research avenues with the following outcomes:
- high-resolution seismicity catalogs and new 3D plate interface and slab surface geometry models
- a new generation of plate interface locking models from combining permanent GPS data inversion with seismicity constraints
- highly resolved regional-scale tomographic images of subduction zones
- new models of petrology, phase changes and thermal structure across several downgoing plates
- a framework for the comparison of seismicity features between different subduction zones
The results from the proposed project will be a big leap towards understanding the physics of subduction zone earthquakes as well as deep fluid circulation and mineral phase changes in downgoing lithosphere. They will also serve as valuable input for future models of earthquake and tsunami hazard.
Status
SIGNEDCall topic
ERC-2020-STGUpdate Date
27-04-2024
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