Quantifying the likely magnitude of nature-based flood mitigation effects across large catchments (Q-NFM)

Lead Research Organisation: Lancaster University
Department Name: Lancaster Environment Centre


The 2007 floods prompted the UK Government's "Pitt review", which came up with the idea that we need to start to deal with the causes of flooding upstream of the affected communities, rather than rely solely on the downstream engineering solutions. This stimulated a range of organisations to introduce "natural" features into the landscape that may have benefits in terms of reducing flooding (so called "Natural Flood Management, NFM"). Having introduced features these organisations, and local stakeholders working with them, are increasingly asking "Are these features working?" This has highlighted to funders, those implementing the features and scientists alike that there are gaps in the evidence of how individual features (e.g. a single farm pond or a small area of tree planting) work and what are potential downstream benefits for communities at risk of flooding. Stakeholders want both questions answered at the same time, making this one of the most important academic challenges for hydrological scientists in recent years. The only way to quantify the effects of many individual features at larger scales is to use computer models. To be credible, these models also need to produce believable results at individual feature scales. Meeting this challenge is the focus of this research project.

Consequently, our primary objective is to quantify the likely effectiveness of these NFM features for mitigating flood risk at large catchment scales in the most credible way. In this context, credibility means being transparent and rigorous in the way that we deal with what we do know and what we don't know when addressing this problem using models. In doing this we need to address particular scientific challenges in the following ways:

* We need to show that our models are capable of reproducing downstream floods while at the same time matching observed local hydrological phenomena, such as patterns of soil saturation. Integral to our methodology are observations of these local phenomena to further strengthen the credibility of the modelling.

* We use the same models to predict NFM effects by changing key model components. These changes to the components are made in a rigorous way, initially based upon the current evidence.

* As evidence of change is so critical, our project necessarily includes targeted experimental work to address some of the serious evidence gaps, to significantly improve the confidence in the model results.

* This rigorous strategy provides us with a platform for quantifying the magnitude of benefit that can be offered by different spatial extents of NFM implementation across large areas.

By addressing these scientific goals we believe that we can deliver a step change in the confidence of our quantification of the likely effectiveness of NFM measure for mitigating flood risk at large catchment scales.

Planned Impact

The most important impact from this project will be to support the appropriate use of NFM in large catchments. This will involve building an understanding of the benefits of NFM shared between flood risk engineers, catchment management professionals and communities at risk of flooding. Decisions about committing to NFM in flood risk management are made difficult by uncertainty about the flood risk mitigation benefits. This difficulty can be exacerbated by overly optimistic claims of the catchment management community who understand that the multiple benefits of NFM make it a key component of most catchment plans. Affected communities need progress towards reducing flood risk, and need confidence that NFM will make a difference if implemented. This project has been designed to build shared understanding, and consequently trust, between these groups. Credible, scientifically robust estimates of the benefits of NFM, co-designed with the affected communities using local knowledge, will support the appropriate use of NFM in large catchments. Quantifying the inherent uncertainties about NFM explicitly within this process strengthens this shared understanding.

Building the technical capacity within the catchment management community to deliver and maintain NFM will allow the appropriate level of NFM to be delivered. While there is excellent localised experience of delivering NFM to provide local flood risk benefits, experience of delivery in large catchments is a long term endeavour which requires new skills and knowledge to be developed and tested. This project is designed to build the scientific evidence required to strengthen knowledge, capacity and skills across the all the partner organisations involved in the Cumbrian catchments, and beyond. The engagement work-package (Task 7) is designed as a two way process: at the catchment scale the engagement revolves around the co-design of NFM interventions and the development of shared understanding between the partners. At a national scale the engagement is focused on sharing the knowledge gained with other groups who are implementing NFM and providing the opportunity for debate around this knowledge and emerging learning and experience from across the country to flourish.

Overcoming policy barriers to the appropriate implementation of NFM in large catchments will have a significant impact. Some of the barriers are based on knowledge gaps which will be filled in this research call. However, a number of barriers are based on the fact that NFM delivery requires disparate technical disciplines and organisations to work together in partnership at a catchment scale. Policy makers already accept the benefits of this type of approach and have implemented it in the policy framework which gave rise to the Catchment Based Approach (CaBA). The flood risk community have to date remained separate from CaBA, however, one of the aims of the Defra Cumbria Catchment Pioneers is to unite flood risk, water resources and water quality to deliver a genuinely integrated catchment based approach as part of the 25 Year Environment Plan. This project is focused on the Cumbrian catchment Pioneers and will provide policy makers with a case study for this multi sector working which can feed directly into the 25 YEP.


10 25 50
Description The key findings arising from the first 24-months of the 42-month research programme of the Q-NFM project are as follows:

1/ A strong theoretical basis for high rates of wet-canopy evaporation (interception loss) during large storm events in western UK has been developed (Page et al., in submission). The effects of tree planting on this process may deliver credible flood peak mitigation in certain areas of Cumbria (notably leeward slopes) in the western UK. Magnitudes of effect across three large Cumbrian catchments being determined through modelling, supported by new experimental work on wet-canopy evaporation during storms.

2/ Eighteen rated stream gauging stations (see e.g., https://dashboard.hobolink.com/public/West%20Cumbria%20and%20South%20Cumbria and https://dashboard.hobolink.com/public/Eden%20and%20Lune%20headwater) have been installed at critical sites across Cumbria (many above flood-affected communities where Defra NFM pilot interventions are to take place). It is already clear that groundwater contributions from the solid geology are making a significant contribution to local flood response. The type of groundwater response is very varied across the network. For example, fracture flow dominate rapid flood responses at Grange-over-Sands; mine shaft discharges dominate flood responses upstream of the Flimby community; residence times of flood response are delayed by one day due to fractures above the Sedbergh community.

3/ Using a research grant from the Environment Agency, the Q-NFM team have been able to add direct monitoring of NFM storage features, to quantify when and how well they their function with respect of flows monitored by our stream gauging stations. One of the ways we model the functioning of these storage features we presented in Magliano et al. (2019 Hydrol Res 50: 1596-1608). Other NFM features associated with our micro-basins we monitor their effect on topsoil permeability, topsoil moisture content and overland flow incidence. Some of this work has been presented in Wallace and Chappell (2019 J Environ Qual 48: 1766-1774). Effects on surface roughness and effective channel storage we are quantifying in 2020 with an ADZ-fluorimetry method.

4/ The distributed rainfall-runoff modelling used for simulating catchment-wide effects of Natural Flood Management (NFM) within Q-NFM is based on the 'Dynamic-Topmodel' approach, known to capture the complexity of subsurface flow routing (in soils and rock-groundwater systems) parsimoniously. We have found that the representation of in-channel processes and floodplain inundation processes did need significant improvement to capture the effects of NFM storage in these two areas. The ways that we now represent individual leaky dams is presented in Metcalfe et al. (2018 Hydrol. Earth Syst. Sci., 22, 2589-2605). Furthermore, we now use 'Dynamic-Topmodel' only to represent the subsurface and hillslope-surface routing, with all channel and floodplain routing newly represented within HEC-RAS routines (Hankin et al., Hydrol Res 50: 1535-1548). These models are equally parsimonious (and fast running) but with more accurate 2D hydraulics. Despite parsimony in the representation of subsurface flood-flows in 'Dynamic-Topmodel' there remains many challenges in the accurate spatial representation of the flood-flows in the subsurface while still constraining model complexity (and hence predictive uncertainty). We have, therefore been developing ways of better parameterising and evaluating our models. This has been in the form of new conceptual approaches (Beven 2019 Proc. R. Soc. A 475: 20180862 and Beven 2019 Hydrol. Res., 50: 1481-1494), and in new code development to increase simulation speed (https://waternumbers.github.io/dynatop)
Exploitation Route Full details to follow - only 24-months into a 42-month programme.
Sectors Agriculture, Food and Drink,Communities and Social Services/Policy,Environment,Government, Democracy and Justice

URL https://www.lancaster.ac.uk/lec/sites/qnfm
Description The primary goal of the Q-NFM project (for three Cumbrian basins) and the NERC NFM research programme nationally is to quantify the potential effects of numerous local NFM interventions (of many types) at the scale of small to large catchments. This key end-user deliverable will necessarily come towards the end of the 42-month research programme following detailed development of the various research components. To help deliver end-user impact of our research, interactions with end-users of the science are now fully embedded in our Q-NFM research programme. In particular we work very closely with the teams delivering the Defra NFM pilots in Cumbria. Monitoring of these pilots now closely follows the 'evidence of hydrological change' strategy developed for Q-NFM. This has also greatly benefited Q-NFM, as the Q-NFM monitoring network has been greatly expanded by adding compatible monitoring associated with Defra NFM pilot projects in Cumbria. The Environment Agency manages the Defra NFM pilots, but local environmental NGOs are often the scheme developers and implementers for the Agency. As a result, we have also supported the environmental NGOs with advice on monitoring and what types of intervention might be more effective at particular localities. The monitoring installed on streams upstream of flood-affected communities in Cumbria is visible on a public website, real-time: e.g., https://dashboard.hobolink.com/public/West%20Cumbria%20and%20South%20Cumbria and is promoted by the NGOs. The Agency's national flood warning network does not currently include discharge data for such small streams. Q-NFM has enabled such data to be made available to flood-affected communities for their flood warning and those coordinated the Agency and Cumbria County Council.
First Year Of Impact 2017
Sector Agriculture, Food and Drink,Communities and Social Services/Policy,Environment,Government, Democracy and Justice
Impact Types Societal,Policy & public services