- Opportunity to investigate what causes flood change across the UK and how flood risk will evolve under changing climate and land cover
- Close collaboration with a wide range of academic and industry partners and short visit opportunities, such as 3-18 months to the Lighthill Risk Network (LRN), the UK Met Office, and the UK Centre for Ecology & Hydrology (CEH)
- Opportunity to develop strong skills in R programming, large data analysis, numerical modelling and cluster computing
Floods are one of the most damaging natural hazards in the UK, affecting millions of people and billions of pounds in property values per year (Evans et al, 2004). For example, the extensive winter floods that occurred during November 2015 to February 2016 cost over £5 billion (Marsh et al, 2016), and the February 2020 floods caused severe risk to thousands of houses and businesses (Sefton et al., 2021). There is growing concern that flood risk may become worse across the UK since flood magnitude and frequency have experienced considerable changes in many catchments (Blöschl et al., 2020). Evidence shows that in temperate river catchments, the 50-year flood event as assessed in the 1970s now occurs every 21 years on average (Slater et al., 2021).
An increasing body of work has described the “death” of flood stationarity (Milly et al., 2008), meaning that the mean, variance or shape of a flood time series may shift over time under the effects of different drivers, such as climate change and land cover change. Increased precipitation may lead to increased river flooding, while increased temperature may enhance evapotranspiration and thus decrease catchment wetness prior to high intensity precipitation events. Urbanisation introduces more impervious land, reducing infiltration and increasing runoff volumes. However, the relative and combined effects of these different drivers across different catchment types are still poorly understood. For example, are changing precipitation patterns dominant or is urbanisation more important for flood change? and how will flood risk evolve under changing climate and land cover?
This project aims to: 1) quantify the relative impacts of different drivers on floods across a large sample of UK catchments; and 2) assess the evolution of future flood risk considering the influence of both climate and land cover change in catchments with already high flood risks. This work will help understand and address the challenges imposed by climate change and urban expansion and provide scientific insights for sustainable development, flood management, and the insurance industry. The student will have the opportunity to work closely with project partners in government and industry to translate research into practice.
This is a CENTA Flagship Project
This project is suitable for CASE funding
HostUniversity of Birmingham
- Climate and Environmental Sustainability
- Dr Shasha Han (University of Birmingham)
- Dr Louise Slater (University of Oxford, [email protected])
- Dr Joshua Larsen (University of Birmingham, [email protected])
- Dr Fraser Lott (UK Met office, [email protected])
- Mr Jamie Hannaford (UK Centre for Ecology & Hydrology, [email protected])
- Dr Cameron Rye (Lighthill Risk Network, [email protected])
We will identify a large sample of UK catchments which have good data record and minor human influence. Using high performance computing supported by BEAR (Birmingham Environment for Academic Research), we will extract data from key datasets, including flow data from the National River Flow Archive (NRFA, the UK’s focal point for river flow data), climate observations from HadUK-Grid, climate projections from UKCP18, satellite-derived high-resolution urban maps, and land cover projection maps. Statistical models will be developed to investigate the relationships between flooding, precipitation, temperature, soil moisture, and urbanisation, and spatial variations in the relative impacts of different drivers on floods will be analysed and compared based on the developed models. For catchments under high risk of flooding, future flood projections will be developed based on climate (e.g. RCP8.5) and land cover (e.g. SSP1-5) scenarios, and flood risk will be assessed to provide actionable information to our industry partners.
Training and skills
This project is highly interdisciplinary, bringing together hydrology (numerical modelling), climate science (climate change), sustainable development (urban planning), data science (large data analysis), and computer science (programming). The student will receive training and knowledge on all the involved research areas across the supervisory team. Extensive training will be provided to develop large data analysis and numerical modelling skills, which involve hands-on training in R programming and ArcGIS. The student also have access to a wide range of personal development training courses. By spending time at host/partner institutions, the student will learn how research is translated in practical contexts.
Partners and collaboration
In addition to the close collaborations across the University of Birmingham, the Lighthill Risk Network will provide additional CASE funding and host the student with co-supervision from Dr Cameron Rye. The student will have the opportunity to work with Dr Louise Slater from the University of Oxford on flood non-stationarity and will be exposed to extensive network and academic communications through the Oxford Hydrology group. Dr Fraser Lott from the UK Met Office will provide guidance on attribution techniques and could also host the student at the Met Office (e.g. 6 months). The student also has the opportunity to spend time at the UK Centre for Ecology & Hydrology to work with Mr Jamie Hannaford and benefit from his expertise on hydrological trends and variability. The Environment Agency will also co-supervise this project and provide additional support in flood risk management, land use management, and climate change impact assessment.
For more information on the project, please do not hesitate to contact Dr Shasha Han or Josh Larsen [email protected]
More information about BEAR (Birmingham Environment for Academic Research) can be found here:
If you wish to apply to the project, please visit: https://sits.bham.ac.uk/lpages/LES068.htm
Attend DR trainings (e.g. statistics, using R for data processing), collect and process data, identify study catchments, and develop statistical models.
Quantify the relative impacts of different drivers on floods across the UK, attend conferences and write journal paper to deliver research results.
Develop projections of future floods and assess flood risk, attend conferences (e.g. EGU), write further journal paper(s), write and submit thesis.
Blöschl, G. et al. (2020) ‘Current European flood-rich period exceptional compared with past 500 years’, Nature, 583(7817), pp. 560–566. doi: 10.1038/s41586-020-2478-3.
Hannaford, J. et al. (2021) ‘An updated national-scale assessment of trends in UK peak river flow data: how robust are observed increases in flooding?’, Hydrology Research, 52(3), pp. 699–718. doi: 10.2166/nh.2021.156.
Milly, P. C. D. et al. (2008) ‘Climate change: Stationarity is dead: Whither water management?’, Science, 319(5863), pp. 573–574. doi: 10.1126/science.1151915.
Rye, C. J., Boyd, J. A. and Mitchell, A. (2021) ‘Normative approach to risk management for insurers’, Nature Climate Change, 11(6), pp. 460–463. doi: 10.1038/s41558-021-01031-8.
Sefton, C. et al. (2021) ‘The 2019/2020 floods in the UK: a hydrological appraisal’, Weather. doi: 10.1002/wea.3993.
Slater, L. et al. (2021) ‘Global Changes in 20-Year, 50-Year, and 100-Year River Floods’, Geophysical Research Letters, 48(6), pp. 1–10. doi: 10.1029/2020GL091824.
Web page with an author:
Evans, E., et al. (2004) Foresight Future Flooding. Scientific Summary. Available at: https://econadapt-library.eu/node/1458 (Accessed: 01 October 2021).
Marsh, T., et al. (2016) The winter floods of 2015/2016 in the UK -a review. National Hydrological Monitoring Programme. Available at: https://www.ceh.ac.uk/sites/default/files/2015-2016%20Winter%20Floods%20report%20Low%20Res.pdf (Accessed: 01 October 2021).
This project is unlikely to be impacted by any restrictions from COVID-19, since the project is mostly computational and does not involve fieldwork, and all the data required are either publicly available or available through request. Although there are opportunities for national or international exchange study, online meetings and online courses are alternatives in case of local or national lockdown.