The aim of this project is to improve our ability to anticipate coastal erosion events by developing a system for real-time monitoring and continuous forecasting of short-term (storm-driven) coastal erosion events. This will be achieved through a coupled observational and numerical modelling approach.
Coastal erosion threatens nearshore infrastructure, individual properties, and people’s livelihoods. Risks associated with coastal erosion are expected to increase in severity in the coming decades due to anticipated sea level rise, and the increased intensity and frequency of storm events (UKCP18). Despite these risks, coastal regions remain a focus for development and thus there is need for an evidence base to establish which assets within which coastlines are most vulnerable to erosion for strategic planning purposes. Erosion of coasts around the UK is already an environmental problem requiring management strategies. For example, the Dynamic Coast project assessed past erosion extent around the entire coast of Scotland, identified the most at risk sections of coast to future erosion and assessed the vulnerability of the coast in terms of social, economic and cultural heritage assets (Fitton et al., 2016). There is a clear management need to better monitor the significance of the latest changes against future anticipated change, thresholds and the critical points for management intervention and adaptation.
Our ability to make reliable predictions of future coastal change is dependent on a solid theoretical understanding of coastal processes coupled with records of past coastal change under known forcing conditions. Future coastal erosion around the coast of Scotland has focused at the national scale by extrapolation of historical recession rates. However, historical observations of shoreline changes are temporally sparse. Furthermore, predictions of future erosion do not account explicitly for the processes of erosion and sediment transport (Hansom et al., 2017).
Prediction of future coastal erosion requires the use of process-based numerical models that are calibrated and validated by observational data (e.g. Vitousek et al., 2017). The modelling approach used depends on the time and space scale of interest. For decadal-scale predictions over large spatial scales, simplifications in the representation of sediment transport processes and driving wave conditions are required to make simulations manageable (e.g. Vitousek et al., 2017). Alternatively, short term beach erosion in response to storms can be simulated by coupled morphodynamic hydrodynamic models such as XBEACH (Roelvink et al., 2010), but such models require high resolution, high frequency topographic data that are labour intensive to collect and are thus not tractable for longer timescale simulations.
This project aims to couple real time monitoring and modelling to develop a continuous early warning system for storm-induced coastal erosion events in response to extreme environmental conditions. The specific objectives will be to:
• Automate the extraction of shoreline morphology from satellite and ground-based images to build real-time timeseries of shoreline change.
• Develop a nested modelling approach to predict shoreline change from national to local scale using known environmental forcing conditions and forecast data
• Validate and refine the modelling approaches across scales in response to real erosion events occurring during the project.
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IMG_8411.JPG Example of coastal erosion protection/management on the Scottish Coast
This project will take a nested approach to monitoring and simulating coastal erosion at different spatial and temporal scales. Numerical modelling inevitably involves a trade off between fidelity and resolution/scale, such that we can make coarse predictions at larger spatial and temporal scales and finer predictions at more local scales.
Real time monitoring will be achieved via a combination of citizen science approaches and automated analysis of satellite images. Real time ground based photographs will be solicited by establishing a CoastSnap site at a location of known erosion risk in Scotland. High-resolution satellite images (0.7-3 m resolution) are available for free under a research licence via Planet Labs. The student will develop routines for automating the extraction of shorelines (e.g. vegetation edge) and nearshore bathymetry in order to build timeseries of coastal change.
Meso-scale (kms and decades) modelling of coastal change will be conducted using the CoSMoS-Coast model developed by Vitousek et al. (2017). The model will be trained with mapped historical shoreline position data from Hansom et al. (2017). Future wave conditions and sea levels will be developed from UKCP18 forecasts and probabilistic computation of wave run up. Erosion in response to storms will be forecast using a short-term morphodynamic model (such as those developed by Roelvink et al., 2009) however these are typically limited in their ability to simulate recovery and their suitability over these timescales. To provide continuous forecasts in real time an integrated approach to estimate pre-storm conditions will be developed through satellite imagery and simpler parametric modelling approaches (e.g. Davidson et al. 2013). Extreme wave and water conditions provided based on the Met Office UK Coastal Monitoring and Forecasting (UKCMF) service.
Finally, the project will develop a framework for integrating monitoring and modelling data in real time, to continually refine projections as new data and boundary condition forecasts become available.
Year 1 (October 2019 start): Initial training in techniques, processes and research methods. The student will develop and refine the initial scientific problem informed by reviewing existing literature on coastal monitoring and coastal erosion, as training in the preparation of a research paper. The student will learn how to download, manipulate and analyse satellite imagery to extract information about coastal change. The student will develop skills in numerical modelling using long time coastal behaviour and short-term morphodynamic models, initially through application of existing worked examples. Student will attend a training course for morphodynamic modelling using XBeach. Attendance at the BSG Windsor workshop.
Year 2: Development and application of procedures for monitoring and modelling coastal change at a local and a national scale. Learn how to perform validation and calibration of numerical models using known external forcing and observed changes at the coast. Design ensemble numerical modelling experiments. Attendance and presentation of preliminary results at a UK conference (e.g. British Society for Geomorphology).
Year 3: Develop framework for continuous modelling of coastal change for a forecasting application. Finalise results and prepare papers for publication. Attendance and presentation at an international conference (e.g. EGU or AGU), writing up results as drafts for academic publications
Year 3.5: Finalise results, prepare papers for publication, write and submit thesis.
The student will be trained by leading experts in coastal erosion modelling and automated image analysis. The student will receive training in customising and automating GIS and appropriate computer programming languages (e.g. Python, C++, Matlab) required to develop and deploy algorithms to analyse satellite data and ground-based photography, and perform numerical modelling. They will learn how to handle and analyse large environmental datasets. The student will be trained in running coastal evolution models. The student will also receive training in project management academic writing, writing funding proposals. The student will also gain training and experience in sharing their results with government agencies and local authorities. The student will benefit from gaining exposure to the extensive non-academic networks the supervisory team has through the Dynamic Coast project, to assist with sharing the implications of their results for coastal managers.
The student will emerge from the PhD process with skills making them highly suited to a career in the Environmental Sciences, including the ability to manipulate and interpret large datasets, and conduct numerical modelling. There are obvious career paths in natural hazards and land management, for example, as well as research.
References & further reading
Davidson, M. A., Splinter, K. D., & Turner, I. L. (2013). A simple equilibrium model for predicting shoreline change. Coastal Engineering, 73, 191-202.
Fitton, J. M. et al. (2016) A national coastal erosion susceptibility model for Scotland, Ocean & Coastal Management 132, 80-89.
Gouldby, B. P., et al. (2017) Multivariate extreme value modelling of sea conditions around the coast of England.” In Proceedings of the Institution of Civil Engineers-Maritime Engineering 170, 3-20.
Hansom, J.D. et al. (2017) Dynamic Coast – National Coastal Change Assessment: National Overview. Documentation. CREW.
Roelvink JA, et al. (2009) Modelling storm impacts on beaches, dunes and barrier islands. Coast. Eng. 56, 1133-1152.
Vitousek, S., et al. (2017), Can beaches survive climate change?, J. Geophys. Res. Earth Surf., 122, 1060-1067.
Applications: to apply for this PhD please use the url: https://www.gla.ac.uk/study/applyonline/?CAREER=PGR&PLAN_CODES=CF18-7316
For more details contact Martin Hurst, School of Geographical and Earth Sciences, University of Glasgow, University Avenue, Glasgow, G12 8QQ. Tel: +44 (0)141 330 2326; Email: email@example.com.