LANDWISE: LAND management in loWland catchments for Integrated flood riSk rEduction

Lead Research Organisation: University of Reading
Department Name: Geography and Environmental Sciences

Abstract

LANDMARK (LAND MAnagement for flood RisK reduction in lowland catchments) will evaluate the effectiveness of realistic and scalable land-based NFM measures to reduce the risk from flooding from surface runoff, rivers and groundwater in groundwater-fed lowland catchments. We will study measures like crop choice, tillage practices and tree planting, that have been identified by people who own and manage land, to have the greatest realisable potential. NFM measures will be evaluated for their ability to increase infiltration, evaporative losses and/or below-ground water storage, thereby helping to store precipitation to reduce surface runoff and slow down the movement of water to reduce peak levels in groundwater and rivers. However, we need to carefully examine the balance between increased infiltration, soil water storage and evaporative losses under different types of NFM measures, because long-term increases in infiltration could actually increase groundwater and river flood risk if there is less capacity within the ground and in rivers to store excess precipitation from storm events. Also, following a review of the available research to date, other researchers (Dadson et al, 2017) came to the conclusion that land-based NFM measures would only provide effective protection against small flood events in small catchments. As the catchment size and flood events increase, the effectiveness of land-based NFM measures in reducing flood risk would decrease significantly. However, this idea needs to be tested further.

Currently, there are many unanswered gaps in knowledge that make it hard to include land-based NFM measures in flood risk mitigation schemes. The Environment Agency tell us that there are no case studies on land-based NFM measures to support decision making, with most focusing on leaky barriers made from trees. Yet, land-based NFM measures have potential to do more than just reduce flood risk, including improving water quality, biodiversity and sustainable food and fibre production. So in LANDMARK, we will carry out research to help to fill this evidence gap, and test the ideas Dadson et al. proposed about land-based NFM using the West Thames River Basin as a case-study area. We will work at three spatial scales (field, catchment and large river basin) and explore modelling scenarios, developed with people who own and manage land and live at risk of flooding, to look at how land-based NFM could affect flooding. Scenarios will include experiences in the recent past in July 2007 and over the winter of 2013-14, and how future land use and management could affect flood risk in 2050 as the climate changes. We will consider how government policy could change after we leave the EU to support land-based NFM.

Work will be carried out in five stages: (1) we will bring together available maps, data and local knowledge on current land use and management, and use this to create scenarios for modelling experiments to explore land use and management measures impact on events from the past and in the future; (2) we will make measurements to see how below-ground water storage and infiltration vary between different land-based NFM in fields where innovative land management is being practiced; (3) we will collect data from sensors sitting above the ground, flying on drones and on satellites to see how vegetation and soil moisture vary across large catchment areas; (4) we will use all the data collected from 1-3 to run modelling experiments across a range of scales, linking together models that capture soil and vegetation processes, overland and groundwater flows and catchment hydrology, exploring variation in model outputs; and (5) we will create web applications to display and explore the outputs from the modelling experiments. All this work will be supported by workshops, field visits, reports and resources to support people and their learning about how land-based NFM measures work and could be used to reduce flood risk.

Planned Impact

LANDMARK will deliver new knowledge and tools to help develop realistic and scalable plans to reduce pluvial, fluvial and groundwater flood risk using land-based NFM in lowland groundwater-fed catchments. Specific groups include:

- Communities at risk of flooding: flood groups, parish councils and farmers will benefit from evidence created to support expanding land-based NFM measures to reduce flood risk where traditional defences aren't feasible and to extend life of hard defences elsewhere. Uncertainty and sensitivity analysis of a range of scenarios will help to improve understanding of the realistic level of protection provided, helping to inform flood preparedness measures.
- Environment Agency, Lead Local Flood Authorities and Regional Flood and Coastal Committee responsible for planning and delivering flood risk management will also benefit from evidence to support planning and decision making to enable land-based NFM measures to be used to deliver flood risk protection and prolong the life of hard infrastructure investments. Improved model and parameter development will also help inform planning and flood forecasting (including updated FEH statistics).
- Policy Makers and Regulators in Defra, Environment Agency, Forestry Commission and Natural England will benefit from the evidence created to inform post-Brexit agri-environment policy development. Evaluation of new remote sensing capability (e.g. Sentinel-1 and 2) to monitor soil moisture/NFM benefits from different land use and management could help the Rural Payments Agency support delivery of land-based NFM options. Evidence will inform climate change adaptation strategies for the Committee on Climate Change, including potential to safeguard public water supply and improve resilience of ecosystems and agriculture.
- Land owners, managers and advisors, including farmers, farm advisors and representatives (e.g. FWAG, NFU), forestry (e.g. Forestry Commission, Confor, Institute of Chartered Foresters), river and conservation charities (e.g. National Trust, Woodland Trust, Wildlife Trusts, Rivers Trusts) will benefit from case-study information demonstrating flood risk co-benefits delivered from a range of land-based NFM measures to tailor to their needs, and from possible future policy changes to support delivery.
- Catchment partnerships (e.g. led by Rivers Trusts) will directly benefit from the increased capacity and capability to explore scenarios to inform catchment management plans, case studies and realistic web-based applications to explore options. This include evidence of the appropriate scale or uptake of measures needed to deliver benefits. Impact of land-based NFM measures on mitigating drought risk and associated water quality and biodiversity risks will support environmental improvements.
- Water Industry (e.g. Affinity Water, Thames Water) will benefit from knowledge and tools created to explore impact of catchment management on water resources, particularly impacts on low flows and on water quality and quantity to safeguarding drinking water supply. This includes enhanced evidence from cover crops currently funded by Thames Water to protect drinking water quality.
- Environmental consultancies (e.g. JBA and CGI) with flood risk delivery contracts for the EA and Defra will benefit from additional capability developed through hydrological model development, improved evidence to constrain parameters and uncertainty, development of remote sensing data products to support NFM management, modelling and flood forecasting, and improved NFM opportunity mapping capability to include a wider range of land-based NFM measures in lowland catchments.
- General public will benefit from wider knowledge and evidence to support understanding about of the link between land use and management and flood and drought risk management. LANDMARK will provide a range of online resources (including possible MOOC), press briefings and media information resources.

Organisations