Vulnerability of low-lying transportation networks to increasing extremes in coastal flooding under climate change


   School of Geography and Environmental Science

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  Dr E Lazarus, Dr Sien Van der Plank, Prof Simon Blainey  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

​​Road and railway networks are fundamental to societal functioning, but are systemically vulnerable to disruption by natural hazards, including floods. To explore how targeted climate adaptation of transportation infrastructure may reduce systemic vulnerability, this studentship will measure and model connectivity of UK transportation networks under increasing extremes in coastal flooding.​ 

This studentship will: (1) use network analysis and scenarios of climate change to quantify current and potential future transportation network vulnerability to coastal flooding; (2) model effects of targeted adaptation interventions into transportation network vulnerability; and (3) gain solutions-oriented insight into vulnerability and adaptation to coastal flood hazard in real transportation networks through collaborative knowledge exchange with a diverse group of expert partners. 

Overarching research questions may include: How do spatial patterns of network vulnerability to coastal flooding change with different metrics of network connectivity? How will nonlinear increases in coastal flood extremes affect spatial patterns of network vulnerability to functional failure? How might different targeted climate adaptation interventions redistribute patterns of vulnerability across a given network under current and future coastal flood extremes? 

The student recruited for this studentship will develop quantitative expertise in network analysis and extreme value analysis, and build a transferrable skill set in data-science techniques and writing open-source code. The student will lead research outputs, practice their communication skills, and grow their professional network by writing for publication, presenting at professional conferences, and participating in meetings with partners. The student and supervisory team will map out a training plan to identify and address particular skills gaps, and draw from the University's deep catalogue of resources for skills training and professional development. Based in the School of Geography & Environmental Science, the student will join a close-knit graduate-student cohort and supportive research culture, and benefit from the School's peer-mentoring programme and cohort-building activities.

Applications must have at least one of the following: a UK BSc or MSci First Class honours degree, or its international equivalent, in a relevant discipline, such as (but not limited to) Geography, Engineering, Physics, or Applied Mathematics; a UK MSc or MRes master's degree with Merit or Distinction (over 60%); evidence of significant and relevant professional experience, equivalent to master's level. 

Applicants need to evidence their demonstrated experience writing code in Python, and with quantitative data analysis. Skills in geospatial data analysis are advantageous but not required. 

The School of Geography and Environmental Science is committed to fostering a culture of equality, diversity and inclusion. We welcome applications from suitably qualified candidates, and particularly encourage applications from candidates belonging to groups who are under-represented within academic posts at the University, including, but not limited to: women, people from Black and minority ethnic groups, and disabled people. The School are committed to providing equal opportunities for all and offer a range of family friendly policies, flexi-time and flexible working. We are a Disability Confident employer and the School holds a bronze Athena SWAN award. ​ 


Architecture, Building & Planning (3) Computer Science (8) Engineering (12) Environmental Sciences (13) Geography (17) Mathematics (25) Physics (29)

Funding Notes

This is a fully-funded UK studentship (fees and stipend) for 3.5 years at standard UKRI base rates, supported by the Southampton Marine and Maritime Institute and the School of Geography and Environmental Science.

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Research output data provided by the Research Excellence Framework (REF)

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