Measuring earthquakes across the global continents from space and seismological observations
Dr John Elliott (SEE), Dr Tim Craig (SEE), Prof. Andy Hooper (SEE), Prof. Tim Wright (SEE)Contact email: email@example.com
The quantity and quality of satellite-geodetic measurements of tectonic deformation have increased dramatically over the past two decades improving our ability to observe active tectonic processes. Prior to this, the dominant constraint on earthquakes was from seismological observations. In addition, we now routinely respond to earthquakes using satellites, mapping surface ruptures and estimating the distribution of slip on faults at depth for most continental earthquakes. Studies directly linking earthquakes to their causative faults allow us to calculate how resulting changes in crustal stress can influence future seismic hazard. This revolution in space-based observation is driving advances in models that can explain the time-dependent surface deformation and the long-term evolution of fault zones and tectonic landscapes (Elliott et al., 2016). This project aims to harness both the spatial reach of space-based InSAR observations of earthquake deformation with the time sensitive information contained with seismological observations to better understand shallow continental earthquake locations, fault segmentation and ruptures, spread right across the global land masses.
Much of our understanding of active tectonics comes from the study of earthquake sources and relating them to the active fault structures seen at the surface. The sparseness of seismological stations reporting to the international seismological bulletins (GCMT, USGS NEIC) in certain parts of the world and the crustal heterogeneity of various regions, can result in the mislocation of earthquakes in these catalogues due to unmodelled bias in the seismic wave paths. The technique of InSAR allows the accurate positioning of events for moderately sized (Mw 5.5+) and relatively shallow (
A number of small and shallow earthquakes have occurred beneath the continents in the window of Sentinel-1 radar imaging (Oct 2014-present). It is not clear whether these earthquakes are readily visible in interferograms produced over the epicentral areas or not, as the ground deformation can be masked by atmospheric noise for these small events. This project aims to detect the location of these events by examining an existing automated catalogue of processed interferograms, and also process past data for older earthquakes using the Sentinel-1 spacecraft data to make interferogram observations of the epicentre. In the case that sufficient signal is found, the student will model the signal to improve the source location and depth, as well as potentially constrain the fault geometry (Bagnardi & Hooper, 2018). Potential processes to improve signal to noise ratios could also be implemented including stacking of multiple InSAR images, or more advanced time series analysis.
Once a catalogue of well-constrained InSAR derived locations of moderate-magnitude earthquakes has been compiled, the student will then work on comparing these locations to those derived using a range of seismological techniques, estimating both generic and regional specific uncertainties and biases. As these data allow (or require), it may be possible to use events with well-located InSAR locations to calibrate seismological location routines, allowing the correction and relocation of a more complete seismic dataset.
For a subset of larger or more interesting earthquake ruptures, it will be possible to advance the modelling analysis to the distribution of earthquake slip (Figure 2) using inversion approaches (Amey et al., 2018). The aim would be to constrain the depth extent of faulting and examine the relationship between slip asperities and fault segmentation. There will also be the potential to examine the seismologically constrained time variability of rupture and compare this to the InSAR constrained distributions of slip.
Related undergraduate subjects:
- Biodiversity conservation
- Earth science
- Geological science
- Geophysical science
- Remote sensing