PhD Studentship: Monitoring Morphological Variability of Different Gravel Barrier Typologies

DoS: Dr. Nieves G. Valiente (Email: nieves.garciavaliente@plymouth.ac.uk)

2^nd Supervisor: Dr. Chris Blenkinsopp (University of Bath)

3^rd Supervisor: Dr. Mark Davidson (Email: M.Davidson@plymouth.ac.uk)

Applications are invited for a 3.5 years PhD studentship within the Environmental Intelligence doctoral training programme at the University of Plymouth, starting on 01 October 2024.

Project Description

Scientific background:

Gravel barriers constitute a large proportion of the UK coastline. These systems represent critical natural capital as they act as a natural defence for coastal flooding and erosion. The most significant changes to gravel barrier morphology are likely to occur in response to large waves and high-water levels . There are gravel-specific tools, equations (longshore sediment transport and wave runup), and numerical approaches for predicting gravel barrier response to storms. However, these are specific to pure gravel settings, and there are at least three different gravel beach typologies with potentially three distinctive dynamic responses and resilience to environmental conditions.

While some studies have focused on the decadal behaviour of different gravel embayments, fundamental hydrodynamic processes leading to rapid changes in the beachface of these environments are still poorly understood. A major challenge is to identify how the different gravel barrier typologies respond to the high-frequency swash/overwash processes during storms. The goal of this PhD is to better understand how beach morphodynamics differ in the different barrier typologies. This work will contribute to enhancing our knowledge of gravel barriers, and ultimately, help support coastal managers and stakeholders.

Research methodology:

The project will involve using novel and multidisciplinary approaches to combine remote sensing observations, data science techniques and numerical modelling for different UK gravel beaches. The student will deploy an emerging observational technology such as 2D LiDAR to monitor high-frequency beachface morphological change and hydrodynamics at six different sites during winter periods and will use open-source water level and wave hindcast data to provide boundary conditions. Tasks will include (i) analysis of the event-scale beachface morphological variability and swash/ overwash processes derived from the 2D LiDAR data using novel analysis techniques, (ii) numerical modelling, and (iii) investigate the linkages between offshore wave climate and runup processes.

Training:

This multidisciplinary project will provide the student with training in: (i) field data collection, (ii) remote sensing; (iii) morphology and hydrodynamic data analysis; and (iv) numerical modelling. The student will become an active member of the internationally recognised University of Plymouth Coastal Processes Research Group (https://www.plymouth.ac.uk/research/coastal-processes) and will be directly involved in the acquisition of coastal field observations. This PhD is integrated within the multi-institutional #gravelbeach project. The student will have the opportunity to participate in a research placement at the University of Bath and collaborate with scientists from a range of international institutions. The PhD project will equip the student for a career in coastal and climate research, data science and consultancy.

Person specification:

This project is interdisciplinary and collaborative and will involve a combination of fieldwork, data analysis and numerical modelling. We seek an enthusiastic student with a good degree in a relevant physical, engineering or environmental science.

If you wish to discuss this project further informally, please contact Dr. Nieves G. Valiente, email nieves.garciavaliente@plymouth.ac.uk

For information on Eligibility & Funding, please click on the links below: 

• Eligibility
• Funding

To apply, please click the 'Apply' button, above.

The closing date for applications on 26 April 2024.

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