About the project
Gravel barrier shorelines offer widespread, critically important natural flood protection to many coastal communities. Their management, creation and enhancement are increasingly seen as sustainable, while providing nature-based adaptation options that boost natural capital. But these assets must be well managed to ensure they continue serving such functions in the face of increased risk of coastal erosion and flooding.
This project aims to identify the controls on gravel barrier overwash at a national scale to develop a framework of indicators that support the development of adaptation pathways and monitor performance over time.
The objectives are to:
- Schematise all gravel beaches around the UK using numerical simulations to create a classification dataset for training Machine Learning tools.
- Apply the new tools to identify trigger thresholds in geomorphic and environmental conditions that cause a state change in gravel beach response to forcing.
- Develop an approach to process long-term coastal monitoring data into the tools to provide early warning of a shift in state.
This project will apply Machine learning (ML) to forecast gravel-beach overwash vulnerability in a changing climate. Working alongside the NERC highlight topic research project #gravelbeach it will deliver new tools for the National Network of Regional Coastal Monitoring Programmes.
Please contact the lead supervisor if you require further information about the project.
