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Assessing the potential to create nature-based upstream storage features to manage flood risk

   Postgraduate Training

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  Dr M Wilkinson, Dr Paul Quinn, Dr I Pohle  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

About the Project


Over the past decade many European catchments have experienced an unusually high number of flood events. In the UK, the role of Natural Flood Management (NFM) and the catchment based approach are now at the forefront of the flooding and environmental management debates after the winter 2015/16 floods. There is great potential to store and slow storm runoff upstream. The recently published House of Commons Environment, Food and Rural Affairs Committee "Future of Flood prevention" report has suggested catchment measures need to be adopted on a much wider scale and that farmland in some places should be used to store flood water. However, there is currently little confidence or evidence to support that NFM schemes can provide the amount of storage to radically reduce the impact of flooding. Also, many current case studies are only partially proven and are at a small scale (50km2 or less - hence the "future of flooding" report has called for a catchment scale trail to test NFM methods).

There are two ends to the flood risk management measures spectrum ranging from natural approaches (e.g. woodland restoration) to traditional engineering (e.g. flood walls). Offline ponds and storage reservoirs (i.e. upstream storage) generally fall in the middle ground of this spectrum. The scale of these storage ponds can vary; as the size of storage increases then planning and legislation become more pertinent (e.g. Reservoirs Act). However, it remains a challenge to calculate the amount of storage needed in a catchment in order to mitigate to a certain standard of protection. Coupled with this, there is uncertainty about what type or size of storage is needed (e.g. storage scenarios - lots of small ponds or one large offline pond), the feasibility of implementation, how this varies with scale and other Natural Flood Management measures.

Aim and Objectives:

The overall aim of this project is to develop a modelling and management framework using hydraulic and hydrological modelling approaches to eventually i) understand how much storage is needed in a large scale catchment (>50km2) to mitigate to a certain flood protection standard, and ii) assess which combination of approaches and size/number of storage pond(s) are needed appropriately for the catchment scale. The specific objectives to this are to: a) Collate and analyse data from two case study catchments, b) implement linked modelling methods (Hydraulic and Hydrological) that incorporate these data c) develop a range of scenarios that compare and contrast flood risk management strategies indicating what degree of storage is needed and how this compares to traditional and other NFM methods, d) develop a conceptual management framework that assesses the advantages and difficulties of implementing the identified approaches. This will eventually lead to a decision support framework for the potential of implementing NFM approaches at larger scales.

The study will focus on two large scale catchments in England (the River Eden/Lake District) and Scotland (the Tweed Catchment) which have at least two densely instrumented sub-catchments (>50km2). These catchments cover a range of land uses, soil types, climatic conditions and topographies.

This PhD research will be carried out at the James Hutton Institute, Aberdeen (Supervisors Dr Mark Wilkinson [email: [Email Address Removed]] and Dr Ina Pohle) and the School of Civil Engineering and Geosciences, Newcastle University (Supervisor Dr Paul Quinn [email: [Email Address Removed]]).

Informal inquiries can be made to Dr Mark Wilkinson (email: [Email Address Removed]).

Funding Notes

The studentship is funded under the James Hutton Institute/University Joint PhD programme, in this case with Newcastle University. The successful candidate should have, or expect to receive a 2.1 Honours Degree (or equivalent) in Earth and Environmental Sciences (e.g. Hydrology, Geosciences, Environmental Sciences, Geography, or any other relevant numerate, scientific discipline). Knowledge of modelling (calibration, testing) and programming/coding would be advantageous.

Shortlisted candidates will be interviewed in Jan/Feb 2017. A more detailed plan of the studentship is available to candidates upon application. Funding is available for European applications, but Worldwide applicants who possess suitable self-funding are also invited to apply.


Hewett, C. J., Quinn, P. F., & Wilkinson, M. E. (2016). The decision support matrix (DSM) approach to reducing environmental risk in farmed landscapes. Agricultural Water Management, 172, 74-82.

Wilkinson, M.E., Mackay E, Quinn P.F., Stutter M., Beven K.J., MacLeod C.J.A., Macklin M.G., Elkhatib Y., Percy B., Vitolo C., Haygarth P.M. (2015). A cloud based tool for knowledge exchange on local scale flood risk. Journal of Environmental Management, 161, p38-50.

Wilkinson, M. E., Quinn, P. F., Barber, N. J., & Jonczyk, J. (2014). A framework for managing runoff and pollution in the rural landscape using a Catchment Systems Engineering approach. Science of The Total Environment, 468, 1245-1254.

Wilkinson, M. E., Quinn, P. F., & Hewett, C. J. (2013). The Floods and Agriculture Risk Matrix: a decision support tool for effectively communicating flood risk from farmed landscapes. International Journal of River Basin Management, 11(3), 237-25
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