Volcanic eruptions pose significant risks to lives and infrastructure in New Zealand. Traditional seismic networks, while effective at detecting deep magmatic movements, lack the sensitivity to monitor small magnitude earthquakes near volcanic vents, which are critical for predicting phreatic eruptions. These eruptions, driven by the rapid expansion of steam, can occur without warning and have historically caused substantial damage and loss of life.
This projected, funded by a Smart Ideas grant from the Ministry of Business, Innovation, and Employment, aims to enhance volcanic monitoring by leveraging Distributed Acoustic Sensing (DAS) technology. DAS transforms standard fibre optic cables into dense arrays of seismometers, capable of detecting ground deformations with high spatial resolution. This innovative approach can record 10-100 times more earthquakes, including smaller magnitude events, than conventional seismic networks.
Building on successful pilot studies at Ruapehu and Yasur volcanoes, this project will develop DAS from a research tool into an operational monitoring system. This project will focus on creating real-time data processing workflows using advanced machine learning algorithms and edge computing. These workflows will enable the rapid identification and localisation of seismic events, providing actionable information to improve volcanic hazard assessments.
We will conduct two field campaigns: one at Ruapehu to demonstrate the system's effectiveness in a real-world volcanic scenario, and another at a geyser field to refine our methods in a controlled setting. Geysers, with their frequent eruptions, offer a valuable analogue for volcanic activity, allowing us to gather extensive data and develop predictive models for phreatic eruptions.
Supervisors
Supervisor: Leighton Watson
Key qualifications and skills
The student will be based in Christchurch, New Zealand, in the School of Mathematics and Statistics (or potentially the School of Earth and Environment) at the University of Canterbury.
The three-years of scholarship funding includes tuition and enrolment fees and an annual stipend of $35,000 NZD along with support for travel for conference attendance and fieldwork. The successful candidate must have an Honours or Masters (with a research component) in geology, geophysics, data science, mathematics or related discipline. Programming experience is essential. Field experience and prior experience working with DAS or other geophysical data are advantages but not required.
The scholarship is open to both domestic and international students. The successful candidate will be enrolled full-time at the University of Canterbury and reside full-time in New Zealand for the duration of the PhD project. Candidates must meet the requirements for enrolling in a PhD at the University of Canterbury.
Does the project come with funding
Yes: Tuition and enrolment fees and an annual stipend of $35,000 NZD
How to apply
Interested candidates should apply via email with the subject line “DAS PhD Application” to Dr Leighton Watson leighton.watson@canterbury.ac.nz. Applications should include:
1. Curriculum vitae.
2. Academic transcript(s) (with a translation to English if required).
3. A cover letter outlining your motivation, experience, interest in this topic and which parts of the projects you are interested in.
4. Contact details for two references.
5. A writing sample. This could be a journal publication, report from a class project, blog post etc.
6. A max one-page discussion of your plans post-PhD. How does completing a PhD advance your career objectives.
Shortlisted candidates will proceed to the interview stage. Applications will be reviewed as they are received.
Final date for receiving applications
Ongoing
Keywords
Volcanology, Fibre Optic Sensing, Monitoring, Geophysics
