Details of Award
NERC Reference : NE/S015795/2
THE EVOLUTION OF GLOBAL FLOOD HAZARD AND RISK [EVOFLOOD]
Grant Award
- Principal Investigator:
- Professor DR Parsons, Loughborough University, Geography and Environment
- Co-Investigator:
- Dr SJ McLelland, University of Hull, Energy and Environment Institute
- Co-Investigator:
- Professor R Hardy, Durham University, Geography
- Grant held at:
- Loughborough University, Geography and Environment
- Science Area:
- Atmospheric
- Earth
- Freshwater
- Marine
- Terrestrial
- Overall Classification:
- Unknown
- ENRIs:
- Biodiversity
- Global Change
- Natural Resource Management
- Pollution and Waste
- Environmental Risks and Hazards
- Science Topics:
- Flood modelling
- Floods
- Regional & Extreme Weather
- Earth Surface Processes
- Geohazards
- Floods
- Flood models
- Flood risk
- Abstract:
- Flooding is the deadliest and most costly natural hazard on the planet, affecting societies across the globe. Nearly one billion people are exposed to the risk of flooding in their lifetimes and around 300 million are impacted by floods in any given year. The impacts on individuals and societies are extreme: each year there are over 6,000 fatalities and economic losses exceed US$60 billion. These problems will become much worse in the future. There is now clear consensus that climate change will, in many parts of the globe, cause substantial increases in the frequency of occurrence of extreme rainfall events, which in turn will generate increases in peak flood flows and therefore flood vast areas of land. Meanwhile, societal exposure to this hazard is compounded still further as a result of population growth and encroachment of people and key infrastructure onto floodplains. Faced with this pressing challenge, reliable tools are required to predict how flood hazard and exposure will change in the future. Existing state-of-the-art Global Flood Models (GFMs) are used to simulate the probability of flooding across the Earth, but unfortunately they are highly constrained by two fundamental limitations. First, current GFMs represent the topography and roughness of river channels and floodplains in highly simplified ways, and their relatively low resolution inadequately represents the natural connectivity between channels and floodplains. This restricts severely their ability to predict flood inundation extent and frequency, how it varies in space, and how it depends on flood magnitude. The second limitation is that current GFMs treat rivers and their floodplains essentially as 'static pipes' that remain unchanged over time. In reality, river channels evolve through processes of erosion and sedimentation, driven by the impacts of diverse environmental changes (e.g., climate and land use change, dam construction), and leading to changes in channel flow conveyance capacity and floodplain connectivity. Until GFMs are able to account for these changes they will remain fundamentally unsuitable for predicting the evolution of future flood hazard, understanding its underlying causes, or quantifying associated uncertainties. To address these issues we will develop an entirely new generation of Global Flood Models by: (i) using Big Data sets and novel methods to enhance substantially their representation of channel and floodplain morphology and roughness, thereby making GFMs more morphologically aware; (ii) including new approaches to representing the evolution of channel morphology and channel-floodplain connectivity; and (iii) combining these developments with tools for projecting changes in catchment flow and sediment supply regimes over the 21st century. These advances will enable us to deliver new understanding on how the feedbacks between climate, hydrology, and channel morphodynamics drive changes in flood conveyance and future flooding. Moreover, we will also connect our next generation GFM with innovative population models that are based on the integration of satellite, survey, cell phone and census data. We will apply the coupled model system under a range of future climate, environmental and societal change scenarios, enabling us to fully interrogate and assess the extent to which people are exposed, and dynamically respond, to evolving flood hazard and risk. Overall, the project will deliver a fundamental change in the quantification, mapping and prediction of the interactions between channel-floodplain morphology and connectivity, and flood hazard across the world's river basins. We will share models and data on open source platforms. Project outcomes will be embedded with scientists, global numerical modelling groups, policy-makers, humanitarian agencies, river basin stakeholders, communities prone to regular or extreme flooding, the general public and school children.
- Period of Award:
- 31 Aug 2022 - 30 Apr 2026
- Value:
- £448,106 Lead Split Award
Authorised funds only
- NERC Reference:
- NE/S015795/2
- Grant Stage:
- Awaiting Event/Action
- Scheme:
- Large Grant
- Grant Status:
- Active
- Programme:
- Large Grant
This grant award has a total value of £448,106
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DI - T&S |
|---|---|---|---|---|---|
| £112,946 | £59,712 | £86,670 | £22,797 | £79,088 | £86,892 |
If you need further help, please read the user guide.