Natural Flood Management (NFM), or working with natural processes through a catchment based approach, is increasingly viewed as a viable option for mitigating downstream flood risks (Fig. 1). However, there are still huge uncertainties associated with the evidence for NFM reducing river flows at the catchment scale.

A significant component of NFM is determining where in the catchment changes will have the desired effect downstream. The spatial and temporal dependence of NFM measures (Pattison and Lane, 2012) means that the same land use in two parts of the catchment will have different catchment scale impacts, along with the same location having different effects in different storm events.

Agriculture is a dominant part of the UK landscape, composing 70% of the UK land area. The period of agricultural intensification (post-1945), including increased stock densities and heavier machinery, has coincided with an increase in flood frequency and severity. Another significant change has been an increase in field size and the loss of field boundaries e.g.  hedgerows and stonewalls. It is hypothesised that these have had a significant effect on the flows of water through the landscape. Previous work has shown that hedgerows modify the hydrological cycle in terms of soil saturation and throughflow, and evapotranspiration and interception.

The aim of this PhD is to contribute to this evidence base through developing our process based understanding (localised runoff pathways and catchment scale connectivity) of how changes to the rural agricultural landscape post-Brexit will impact catchment scale flood risk and other ecosystem services. This will be achieved through a combination of field monitoring at the local scale, and numerical modelling to upscale these impacts to the catchment scale.

The specific objectives of the research are likely to include those listed below, but we also encourage the PhD student to develop his/her own ideas:

1) Co-produce with policy stakeholders and farmers how the future of our agricultural landscape might look in the future.

2) Determine the field scale impacts of likely future scenarios through monitoring of the hydrological cycle stores and processes (field trials).

3) Upscale these impacts to the catchment scale to determine the cumulative effect on floods, droughts, sediment delivery etc.

4) Optimise the locations of these features in the landscape for downstream flood risk reduction.


How can the rural landscape be managed to reduce downstream flooding?


A combination of field monitoring, hydrological modelling and stakeholder engagement will be employed.

Firstly, knowledge will be co-produced with the Soar Catchment Partnership (East Midlands) to think about future scenarios for how the landscape might change with Brexit and other agricultural pressures.

Second, fieldwork through monitoring and experimentation will quantify soil and vegetation characteristics, along with impacts on river flow for different types of agricultural rural landscapes. Instrumentation might include soil moisture probes, rain gauges, while experimentation includes infiltration tests and soil sample collection for further laboratory characterisation.

Finally, hydrological modelling using CRUM3 (Lane et al., 2009) to test the catchment scale impact of different “What if” scenarios on flood risk. Furthermore, optimisation techniques will be utilised to determine the best locations to put different rural infrastructure.

Training and Skills

CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to CENTA research themes. 

Individual support will be given by the team of supervisors with frequent meetings to discuss ideas, plans and progress. Furthermore, project specific training will be provided on software (such as Matlab, hydrological and hydraulic models). Presenting work at national and international conferences will build confidence and communication skills throughout the PhD.


Year 1: Conduct a comprehensive literature review, identify research gaps and specific project aims and objectives. The input of the student is really valued in this process. This will be done in collaboration with the Soar Catchment Partnership. There will be general and subject specific training.  You will gain familiarity with the software that will be used throughout the project. Field monitoring and experiments will be designed and preliminary data collected.

Year 2: Field data collection will continue. The hydrological model would be set up and scenario testing started.

Year 3: Data analysis of fieldwork results and thesis writing. Dissemination at international conferences.


Partners and collaboration (including CASE)

This project will work with the Soar Catchment Partnership, which includes organisations such as the Environment Agency, Severn Trent, Natural England, Trent Rivers Trust. It is likely that CASE support will be gained for this studentship.

Further Details

For informal discussion about this project, please contact Dr Ian Pattison, i.pattison@lboro.ac.uk

http://www.lboro.ac.uk/departments/civil-building/staff/pattisonian/ @GoWithTheF1ow

For enquiries about the application process, please contact Berkeley Young b.k.d.young@lboro.ac.uk, School of Civil and Building Engineering, Loughborough University.