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Details of Award

NERC Reference : NE/N012496/1

Advancing the degree of implementation of Natural Flood Management

Fellowship Award

Fellow:
Dr P Quinn, Newcastle University, Civil Engineering and Geosciences
Science Area:
Atmospheric
Earth
Freshwater
Terrestrial
Overall Classification:
Unknown
ENRIs:
Biodiversity
Environmental Risks and Hazards
Global Change
Natural Resource Management
Pollution and Waste
Science Topics:
Coastal & Waterway Engineering
Environmental Planning
Earth Surface Processes
Soil science
Water Quality
Abstract:
There is great potential to work with natural processes to substantially reduce flood impacts on villages and towns and potentially on our larger cities. Examples have now been shown at several locations that show at the local scale (10km2) that soft engineered structures can slow, store and buffer runoff whilst giving multiple benefits to sediment losses and pollution control. The space created for NFM feature such as ponds, modified ditches, woody debris dams and swales are also sites of improved ecological status and new habitats. The fundamental manipulation of hydrological runoff pathways and the modification of the local hydraulic and energy regimes during flood flow, can have tangible benefits downstream and could form the basis of a broader catchment based approach to catchment management. Projects such as the Belford Project (led by Newcastle and the EA) and other NFM demonstration sites have had high impact in terms shaping government thinking on the NFM potential. NFM is now encouraged by the EA as a viable approach to lower cost flood management, especially for locations that would be expensive to resolve using traditional methods. Newcastle is already working with the EA as part of the Working with Natural Processes Initiative which is seeking to improve NFM uptake in the UK. However, several barriers to NFM uptake remain and it is hoped that this project will help resolve these issues. The funding structure for NFM and catchment management is piecemeal and fragmented and it is spread across many agencies. The contrast between traditional hard engineering and soft engineering (or nature-based solutions) is still high and a reconciliation between NFM work on local farms and the traditional flood management professionals is needed. The evidence base for NFM, although growing slowly, needs to be accelerated and captured in a compelling manner by using KE strategies that will encourage NFM uptake. Better understanding of River Restoration schemes methods and funding (which is already an ARUP specialism) is needed. How can the established river restoration methods be evolved and moved upstream to smaller streams to look at runoff management at source? Evidence that NFM works at the scale of single features is also strong, hence the need to upscale these approaches is vital. The scaling up issue will be best achieved by using sound scientific arguments based on scaling theory, new models and improved monitoring methods. To this end ARUP and Newcastle University will create a realistic technological and cost effective funding model to show that NFM can be carried out across larger scales, with tangible benefits, which is quicker, cheaper and easier to deliver. The aim is to show the scientific basis for NFM and how the multiple benefits can be achieved and why. There is potential to further extend the NFM scientific basis into Catchment System Science to show that NFM can play a major role in catchment management in the future. The project team will continue to influence government policy on NFM methods and will attempt to create a new generation of NFM scientists and practitioners in the UK through our CPD courses and high profile publications.
Period of Award:
1 Nov 2015 - 30 Apr 2016
Value:
£28,807
Authorised funds only
NERC Reference:
NE/N012496/1
Grant Stage:
Completed
Scheme:
Knowledge Exchange Fellowships
Grant Status:
Closed

This fellowship award has a total value of £28,807  

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FDAB - Financial Details (Award breakdown by headings)

Exception - StaffException - T&S
£27,690£1,117

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