Dr Jessica Johnson (School of Environmental Sciences, University of East Anglia)
Dr Irene Manzella (School of Geography, Earth and Environmental Sciences, University of Plymouth)
Professor Mark Anderson (School of Geography, Earth and Environmental Sciences, University of Plymouth)
This project will investigate how tectonic stress in a fault system varies over time and whether it affects the location, timing and magnitude of a sequence of damaging earthquakes. This will have implications for understanding why earthquake sequences happen and how the hazard and risk varies.
Earthquake sequences, where several damaging events occur over a few weeks in the same area, are difficult to incorporate into seismic hazard calculations because the driving factors behind why they happen are poorly understood. For the 2016 central Italy earthquake sequence, it’s been suggested that the state of stress before the beginning of the earthquake sequence may affect the timing and location of large (M>6.0) earthquakes (1). Measuring the in-situ stress state of the crust is challenging experimentally, but prior studies have shown this is possible by studying localised microseismicity and seismic anisotropy (2). In addition, features of the microseismicity may change throughout a sequence, such as the magnitude, temporal/spatial clustering or the b-value (describes the ratio of large to small earthquakes). These changes are poorly understood but could be used to quantify potential pre-cursors for large and damaging events, and ultimately understand why earthquake sequence occur.
The candidate will learn to use a variety of computer-based modelling and analysis, including waveform picking, analysing crustal anisotropy, modelling stress transfer, and applying machine learning to geological data. The candidate will spend time at UEA throughout the PhD to learn from the co-supervisor.
The candidate will learn to utilise, develop and write code to locate earthquakes, calculate seismic anisotropy and model stress evolution. Machine learning will be utilised which has applications to several different fields in academia and industry. All training will be provided by the supervisory team.
We are looking for applicants with a degree in Geology, Geophysics or Physics and an interest in understanding earthquake hazard. The candidate should be numerically literate, experience of using Matlab or Python and familiarity with Linux is desirable but not essential.