DoctorLeighton Watson

Geophysical sensing (infrasound, seismic, fibre optic sensing/distributed acoustic sensing) and mathematical modelling of natural hazards (volcanoes, avalanches, earthquakes, flooding, landslides). 

Parametric insurance. Designing triggers for parametric insurance programmes for natural catastrophes. Able to provide advice to businesses

around parametric insurance. 

Geospatial data science. Spatial distribution of natural hazards and infrastructure, exposure of ethnic groups to natural hazards. 

Mathematical modelling about social and economic issues. 

Epidemological data analysis, especially about wastewater data for disease surveillance. 

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My research focuses on how geophysical data (seismic and acoustic) can be combined with physics-based computational simulations to better monitor and understand natural hazards, with a particular emphasis on infrasound (low frequency acoustic waves that are below the frequency limit of human hearing) and volcanic eruptions. Motivated by interesting observations of natural activity, a desire to reduce risk, and a strong scientific curiosity, I develop numerical models that are derived from fundamental physics. I validate these models by acquiring my own data, or by comparing with existing geophysical data and visual observations, and then use the validated models to learn about the behaviour of complex volcanic systems in order to improve monitoring efforts and hazard assessment. 

My current areas of research include detecting and characterizing snow avalanches with infrasound, simulating geophysical signals from pyroclastic density currents, and infrasonic precursors to lava fountaining at open vent volcanoes. Over the past several years, I have also been working on modeling the spread of COVID-19 in New Zealand (Aotearoa).

I am interested in recruiting Honours, Masters, and PhD students for research projects related to computational geoscience, natural hazards, climate change, and generally in applied maths and mathematical modelling. Please see below for some project ideas. Feel free to contact me with your own ideas as well.

DISTRIBUTED ACOUSTIC SENSING (DAS) AT VOLCANOES:
Volcanic eruptions are fascinating but dangerous natural phenomena. Phreatic eruptions, which are steam driven eruptions, are particularly hazardous because they can occur suddenly with no warning. Typically, these eruptions are relatively small, with their impacts largely contained to the area surrounding the vent. Despite this, phreatic eruptions have often led to injuries and deaths due volcano visitors being near the vent at the time of eruption. Phreatic eruptions are caused by a range of mechanisms that produce small magnitude seismic signals and variations in seismicity and seismic tremor may precede eruptions. These signals, however, may only be observable in the near vent region or challenging to distinguish from background volcanic noise, and can be missed by
conventional monitoring networks. Distributed acoustic sensing (DAS) is a novel technology that measures strain along fibre optic
cables in unprecedented spatial and temporal resolution and can be used in hazardous environments. This project would involve analysing previously recorded DAS data using signal processing, computer vision, and machine learning techniques to identify small amplitude seismic signals and potential eruption precursors.

TRACKING PYROCLASTIC FLOWS
Pyroclastic flows are fast-moving clouds of hot gas and ash that pose a major hazard at volcanoes. Pyroclastic flows are characterised by a dense basal flow surrounded by a dilute suspended cloud. The dense basal flow pushes on the Earth generating seismic signals in the ground while the dilute suspended cloud displaces atmospheric air generating infrasound signals in the air. These signals can be used to detect and track the flow in real-time while also providing insight into the complex internal dynamics. This project could involve geophysical data analysis, optimisation, and computational modelling of flow dynamics.

ECONOMIC AND SOCIAL MODELLING
I am interested in applying mathematical modelling to a plethora of economic and social issues. Examples include:
-- Teachers and nurses pay student fees to universities while on placements. How does this differ from tradespeople doing apprenticeships? What are the long-term economic impacts for an individual due to this reduced earning capacity/increased expenses early on in their career?
-- What is the economic cost of being sick or having a sick whanau member? What is the economic impact of having a dependent in a hospital for an extended time? Are there inequalities in this impact across ethnicities and socio-economic groups?

WASTEWATER MODELLING
We have developed a model that estimates the reproduction number and case ascertainment rate at a national level for Covid-19. How could this model be applied on a regional scale? Or to different infectious diseases?