The Dynamic Drivers of Flood Risk (DRIFT)
Lead Research Organisation:
University of Oxford
Department Name: Geography - SoGE
Abstract
The cost of floods averages more than £2 billion annually in the UK and is feared to keep rising as the climate changes. However, there are critical gaps in our understanding of what drives flood nonstationarity, affecting stakeholders' ability to make planning decisions about appropriate levels of flood risk management, land use, or infrastructure required to protect populations.
This project - the Dynamic Drivers of Flood Risk (DRIFT) - has been designed to address crucial challenges in understanding past and future changes in flood properties to improve decision-making support. The overarching aim is to develop a unified understanding of flood nonstationarity from the past into the future (1970-2070), transitioning seamlessly from short to long timescales. DRIFT will develop the first past-present-future prediction system allowing stakeholders to generate robust scenarios of drifting flood characteristics from the past into the future.
Probabilistic models will be developed describing the influence of changing weather characteristics, climate, engineering structures, and land cover on flood properties, such as flood peaks, return periods, probabilities, durations and extent. Past trends in flood properties will be seamlessly linked with future climate forecasts, predictions and projections, over short- to long-term horizons. Future changes in flood properties will be estimated using a multi-model ensemble approach that seamlessly combines climate timescales (seasonal forecasts, decadal predictions, and multi-decadal projections) and land cover scenarios (such as urbanisation or afforestation), as well as management decisions.
This past-present-future prediction system will be integrated within a decision support framework, providing simple and intuitive ways to display complex information on flood evolution. DRIFT's aim is to support stakeholders in making the best planning decisions to manage flood risks and achieve other co-benefits. A user-friendly decision support system will be co-developed to visualise changing flood characteristics under different scenarios. This tool will provide seamless information and visualisations of changing flood properties from the near to far future, for a range of climate and land cover scenarios.
DRIFT has an iterative structure, with Phase I focusing on co-developing the models and decision support software with five key groups of UK flood stakeholders and project partners. Phase II subsequently expands to other regions of the world where observational streamflow data are available. The long-term aim is to develop robust decision-making support on the evolution of flood characteristics, providing direct benefits for societies globally.
This project - the Dynamic Drivers of Flood Risk (DRIFT) - has been designed to address crucial challenges in understanding past and future changes in flood properties to improve decision-making support. The overarching aim is to develop a unified understanding of flood nonstationarity from the past into the future (1970-2070), transitioning seamlessly from short to long timescales. DRIFT will develop the first past-present-future prediction system allowing stakeholders to generate robust scenarios of drifting flood characteristics from the past into the future.
Probabilistic models will be developed describing the influence of changing weather characteristics, climate, engineering structures, and land cover on flood properties, such as flood peaks, return periods, probabilities, durations and extent. Past trends in flood properties will be seamlessly linked with future climate forecasts, predictions and projections, over short- to long-term horizons. Future changes in flood properties will be estimated using a multi-model ensemble approach that seamlessly combines climate timescales (seasonal forecasts, decadal predictions, and multi-decadal projections) and land cover scenarios (such as urbanisation or afforestation), as well as management decisions.
This past-present-future prediction system will be integrated within a decision support framework, providing simple and intuitive ways to display complex information on flood evolution. DRIFT's aim is to support stakeholders in making the best planning decisions to manage flood risks and achieve other co-benefits. A user-friendly decision support system will be co-developed to visualise changing flood characteristics under different scenarios. This tool will provide seamless information and visualisations of changing flood properties from the near to far future, for a range of climate and land cover scenarios.
DRIFT has an iterative structure, with Phase I focusing on co-developing the models and decision support software with five key groups of UK flood stakeholders and project partners. Phase II subsequently expands to other regions of the world where observational streamflow data are available. The long-term aim is to develop robust decision-making support on the evolution of flood characteristics, providing direct benefits for societies globally.
Organisations
- University of Oxford (Fellow, Lead Research Organisation)
- Jeremy Benn Associates (United Kingdom) (Project Partner)
- United States Geological Survey (Project Partner)
- Environment Agency (Project Partner)
- Flood Forecasting Centre FFC (Project Partner)
- UK CENTRE FOR ECOLOGY & HYDROLOGY (Project Partner)
- European Centre for Medium-Range Weather Forecasts (Project Partner)
Publications
Anderson B
(2022)
Statistical Attribution of the Influence of Urban and Tree Cover Change on Streamflow: A Comparison of Large Sample Statistical Approaches
in Water Resources Research
Berghuijs W
(2023)
Groundwater shapes North American river floods
in Environmental Research Letters
Chai Y
(2022)
Constrained CMIP6 projections indicate less warming and a slower increase in water availability across Asia.
in Nature communications
Feng S
(2022)
Greenhouse Gas Emissions Drive Global Dryland Expansion but Not Spatial Patterns of Change in Aridification
in Journal of Climate
Gu L
(2022)
Intensification of Global Hydrological Droughts Under Anthropogenic Climate Warming
in Water Resources Research
Gu L
(2023)
Large anomalies in future extreme precipitation sensitivity driven by atmospheric dynamics.
in Nature communications
Gu L
(2022)
Global Increases in Compound Flood-Hot Extreme Hazards Under Climate Warming
in Geophysical Research Letters
Description | Reliable predictions of flooding can help society to manage the associated risk to lives and property. However, it is challenging to predict whether we might see more or fewer floods over the next 1-10 years, due to the difficulty of simulating dynamic changes in atmospheric circulation at these timescales. The research from the DRIFT project has revealed that a large ensemble of climate models can be used to predict average winter flood conditions over the UK in the next decade. Although the climate models underestimate the magnitude of atmospheric variability in the north Atlantic, we have shown that identifying a subset of skillful climate model simulations improves the ability to predict floods. Our results suggest that decadal climate predictions over the next 2-5 years may be useful for flood risk management. |
Exploitation Route | This research has shown that floods can be predicted 2-5 years ahead. Multiyear averages could be used for operational flood prediction by flood forecasting agencies, to provide an indication of whether floods are likely to occur more or less frequently in the coming years. |
Sectors | Environment,Other |
URL | https://eos.org/editor-highlights/predicting-flood-conditions-in-the-next-few-years |
Description | Impact is just starting to emerge from this work. This section will be updated at a later date. The American Geophysical Union's journal EoS published an editor's highlights piece about our work: https://eos.org/editor-highlights/predicting-flood-conditions-in-the-next-few-years Dr Louise Slater gave a "School members" lecture to Sixth Form students at the Royal Geographical Society on the factors explaining the evolution of flooding at the global scale. |
First Year Of Impact | 2023 |
Sector | Environment |
Impact Types | Societal,Economic |
Description | Appointed to the UK Flood Hydrology Roadmap Scientific and Technical Advisory Group (STAG) |
Geographic Reach | National |
Policy Influence Type | Participation in a guidance/advisory committee |
Title | Snakemake workflow: uk-decadal-flood-prediction |
Description | A Snakemake workflow for making decadal flood predictions using CMIP5/6 decadal hindcasts. The workflow reproduces the results described in our research article: Moulds S, Slater LJ, Dunstone NJ, Smith DM (2023). Skillful decadal flood prediction. Geophysical Research Letters, 49, e2022GL100650. https://doi.org/10.1029/2022GL100650. This dataset contains the workflow itself (workflow/*), a configuration file (config/config.yml), the data required to run the workflow (resources/*), and the output from the most recent top to bottom run (results/*). The workflow itself, without any data, corresponds to release v1.0.0. To use the Github repository you should copy the resources directory from this dataset to the project root and create a results directory prior to running the workflow. |
Type Of Material | Data analysis technique |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | It is too early to describe impact. |
URL | https://doi.org/10.5281/zenodo.6940449 |
Description | Invited talk - American Geophysical Union - Advances in Hybrid Prediction of Hydrometeorological Extremes: Decadal Prediction |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | This was an invited talk in the session on Hydrometeorologic Extremes: Prediction, Simulation, and Change at the American Geophysical Union (AGU) annual meeting. |
Year(s) Of Engagement Activity | 2022 |
Description | Royal Geographical Society School Member Lecture: Explaining the evolution of floods in time and space |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | The Royal Geographical Society's School Member Lectures are run 3 times a year and are for School Members (approx. 700 schools) to attend. They are held at the Society's HQ in London, and are attended by A Level students and their teachers. These lectures are free for School Members to attend; they are recorded and put online for School Members afterwards. I gave this lecture to a live audience of school members on 1 March 2023 at the RGS. The recording of my talk is available online to all School members of the RGS (at https://www.rgs.org/schools/teaching-resources/explaining-the-evolution-of-floods-in-time-and-spa/) |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.rgs.org/schools/teaching-resources/explaining-the-evolution-of-floods-in-time-and-spa/ |