Self-funded PhD students only

Project code



School of Earth and Environmental Sciences

Start dates

Closing date

Applications accepted all year round

Landslides are a persistent threat to human lives, activities and infrastructure.

On September 18, 2017, Category 5 Hurricane Maria’s eye crossed the small island of Dominica in the Caribbean, leaving unprecedented destruction on its path: 100% crop loss, 90% damage to dwellings and all utilities severed. Crucially, although the main airport was still operational, the delivery of emergency aid was jeopardised by the collapse and burial of the roads connecting it to the rest of the island by landslides.

A pre-Maria detailed landslide susceptibility map existed for Dominica but either: 1) failed to identified high risk areas, 2) did not convey the information in an efficient, easily understandable manner or 3) the authorities did not act upon the information.

With this project, we propose to investigate the worldwide, persistent problem of managing rainfall induced landslides in vulnerable small island states, using the case study of Dominica, WI. 

This will be achieved by:

  • Assessing the accuracy of the published landslide map- through a comparison of predicted highly unstable areas with actual failures after both, 2015 TS Erica and 2017 Cat 5 Maria. This will utilise field mapping as well as freely available satellite remote sensing data and ground truthing techniques.
  • Testing of low cost sensors and techniques to monitor slope movement.
  • Evaluation of local stakeholders’ understanding of the information provided by landslide hazard maps as well as its usefulness- through interviews and questionnaires with local emergency managers, planners, NGOs and other stakeholders.

The project will generate good practice guidelines for improved response to landslides and will be published and disseminated as OA Research Papers and also as an online manual freely available through the departmental website. The results will set the basis for a larger project evaluating the understanding and usefulness of maps on Disaster Risk Reduction in different countries.


PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

2019/2020 entry

Home/EU/CI full-time students: £4,327 p/a*

Home/EU/CI part-time students: £2,164 p/a*

International full-time students: £15,900 p/a*

International part-time students: £7,950 p/a*

By Publication Fees 2019/2020

Members of staff: £1,610 p/a*

External candidates: £4,327 p/a*

*All fees are subject to annual increase

2020/2021 entry

Home/EU/CI full-time students: £4,327 p/a**

Home/EU/CI part-time students: £2,164 p/a**

International full-time students: £16,400 p/a*

International part-time students: £8,200 p/a*

By Publication Fees 2020/2021

Members of staff: £1,680 p/a**

External candidates: £4,327 p/a*

*All fees are subject to annual increase
**This is the 2019/20 UK Research and Innovation (UKRI) maximum studentship fee; this fee will increase to the 2020/21 UKRI maximum studentship fee when UKRI announces this rate in Spring 2020.  

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in a relevant subject area. In exceptional cases, we may consider equivalent professional experience and/or Qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

  • For this project we seek to recruit a EU/UK student with a Geohazards/Earth Sciences/Physical Geography background.
  • Knowledge of remote sensing techniques and with a commitment to Disaster Risk Reduction.

How to apply

We’d encourage you to contact Dr Carmen Solana ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our online application form and select ‘Geography, Earth and Environmental Sciences’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please note, to be considered for this funded PhD opportunity you must quote project code SEES4471018 when applying.

Apply now

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