The Dynamic Drivers of Flood Risk (DRIFT) – UKRI Future Leaders Fellowship; PI (2021-2028). Oxford PDRAs: Dr Simon Moulds (2021-2023); Dr Boen Zhang (2023-2025)

Across the globe, future flood risk is often assessed by using climate model outputs to try to describe the ‘drift’ (non-stationarity) in flood magnitude and frequency. Yet, most long-term flood predictions cannot be taken at face value due to the limited accuracy of climate model outputs and because they ignore many of the key factors that affect flooding, such as long-term changes in groundwater, antecedent conditions, land use, and water management decisions. This project – the Dynamic Drivers of Flood Risk (DRIFT) – aims to develop a more comprehensive understanding of flood non-stationarity by drawing on a holistic set of flood drivers across various timescales. DRIFT will develop the first “hybrid”, multi-model, past-present-future prediction system, using machine learning to combine Earth observations with large ensembles of climate model predictions. Past trends will be seamlessly linked with future predictions over monthly to decadal horizons. This past-present-future prediction system will be integrated within a decision support framework, providing simple and intuitive ways to visualise flood evolution under various scenarios. DRIFT’s aim is to support stakeholders in making the best planning decisions to manage flood risks while achieving other co-benefits.

The Evolution of Global Flood Hazard and Risk (EvoFlood) – NERC Large Grant (2021-2026). Oxford PDRAs: Dr Michel Wortmann; Dr Yinxue Liu

Evoflood aims to establish, at the global scale, the relative importance of changes in hydro-climatology versus geomorphology (evolution of channel and floodplain morphology and connectivity, driven by shifts in precipitation patterns, streamflow regime, and catchment sediment fluxes) in driving flood hazard and risk. Within the Evoflood project, Louise Slater leads Workpackage 1 (Universities of Oxford, Birmingham, Reading and Southampton) which seeks to develop a global dataset of bankfull discharge and bankfull return periods; quantify global patterns, trends, and drivers of flooding over the past 40 years; and develop streamflow and sediment climatologies and scenarios of change, to inform a new, dynamic global flood model.

Identifying how a non-stationary environment affects species persistence – ARC discovery project (co-I; led by Pr. Rebecca Lester) (2022-2025)

Understanding the physical mechanisms behind compound heatwave-drought hazards and associated ecosystem risks in drylands of Global South under climate change – NSFC (coI; led by Dr. Jiabo Yin) (2024-2026)

UKRI AI Centre for Doctoral Training inAI for the Environment (Intelligent Earth) (co-I; led by Pr. Philip Stier) (2024-2032; 8 years)

Past grants (selection)

The impacts of urbanisation on river flooding – John Fell Fund, PI (2020-2022)

Financial planning for natural disasters: flood risk in Central Java – NERC/ESRC, co-I (2018-2020)

On the predictability of hydrological extremes using satellite data – SSPGS Seedcorn, Loughborough University, PI (2017)

Forecasting changes in atmospheric rivers, Institute for Advanced Studies, LU with IIT Indore, India, PI (2017)

To what extent have changes in river channel capacity contributed to flood hazard trends in England and Wales? British Society for Geomorphology, PI (2015)

Where do floodplains begin in fluvial networks? – National Center for Airborne Laser Mapping (NCALM), Geosensing Systems Engineering, High resolution Airborne LiDAR data, National Science Foundation, PI