If we don't manage rainfall appropriately, it can lead to flooding. Traditionally, urban areas have been drained using underground sewer systems. These can be expensive and disruptive to build and maintain. Storm runoff collects contaminants as it flows over urban surfaces and through sewer pipes, and is a significant cause of river pollution. In many cities, combined sewers discharge raw sewage into natural water bodies during storm events. Without intervention, growing populations and the effects of climate change will increase the frequency and severity of urban flooding and pollution events. As an alternative to building more/larger sewers, we are starting to implement SuDS (Sustainable Drainage Systems). SuDS is an overarching term for a 'toolbox' of techniques that aim to deal with the quantity of rainfall, but also to have a positive impact on water quality, amenity and biodiversity. Retrofitting SuDS into urban areas can help to improve stormwater management within our existing urban areas. Vegetated bioretention cells (often referred to as rain gardens) are one of the simplest, practical and most reproducible SuDS options. They can be fitted adjacent to urban streets, dealing directly with road runoff. Bioretention cells are emerging as a preferred option in the USA and Australia. However, we do not yet have the same understanding of their performance as for traditional measures such as pipes. This is because they have 'living' elements (i.e. plants & soil) whose functionality varies from place to place and over time. The soil has a critical role to play in supporting plant life and managing runoff. Bioretention cells typically use engineered soils or 'substrates' that need to meet specific physical requirements. To reduce the requirements for imported materials, we need to be confident of their performance with locally-sourced substrate components, thereby reducing cost and improving overall sustainability. Water usage by plants helps to reduce runoff. We will observe plant water usage (evapotranspiration rates) in six full-scale bioretention cells functioning under semi-controlled conditions as part of the Newcastle University's new National Green Infrastructure Facility (funded by UKCRIC: EP/R010102/1). Controlled tests using smaller columns at the University of Sheffield's climate controlled laboratories will allow us to explore more substrate options. We will measure plant respiration in installed SuDS systems to generate a database of evapotranspiration rates for different urban plant types. Bioretention cells slow down excess flow before it is passed to the sewer. We will carry out a detailed investigation of how the substrate and drainage outlet arrangements affect runoff detention. Information relating to maintenance needs is particularly sparse, with clogging of substrates especially poorly understood. We will use magnetic, fluorescent, tracer particles to explore the vulnerability of substrates to clogging by the dirt and fine particles present in road runoff. Drainage engineers use hydraulic models to represent catchment runoff and sewer system flows. The new data will allow us to develop a numerical model of bioretention cell rainfall-runoff processes. Our project partners include the developers of the most widely-used drainage network modelling tools. We will work with them to include bioretention cells in their software. We will also update the cutting-edge urban flood risk model CityCAT to incorporate bioretention cells. Soil and vegetation conditions change over time in response to seasonal weather patterns, and vegetation lifecycles. Furthermore, the hydrological response is sensitive to rainfall duration and intensity, as well as antecedent soil moisture conditions. Conventional approaches to sizing drainage components tend to ignore all these sources of variability. We will develop new SuDS design guidance that uses probabilistic performance functions to address this.

Reliable and comprehensive flood forecasting is crucial to ensure resilient cities and sustainable socio-economic development in a future faced with an unprecedented increase in atmospheric temperature and intensified precipitation. Floodwaters from the areas surrounding a city can heavily affect flood cycle behaviour across urban areas, introducing uncertainties into the forecast that are often non-negligible. However, currently the extent to which we can predict flood hazards is limited, and existing methods cannot for example deal with inter-regional dependencies (e.g. as was seen when floods affected nine different countries across Central and Eastern Europe). Presently in the UK approx. 25% of yearly flood insurance claims are from areas outside the zones forecast to be at flood risk, and annual flood damage costs are already high (approx. £1.5 billion). Also more than 20,000 houses per year continue to be built on floodplains. The need to transform flood forecasting for a range of applications and scales has already been recognised by various parties. The UK Climate Change Risk Assessment 2017 Evidence Report prioritises flooding as the greatest direct climate change related threat for UK cities now and in the future, and urges urgent action to be taken, including the development of new solutions over the next 5 years. The hydraulic software industry and consultancy firms have expressed a desire for more reliable and sophisticated flood forecasting approaches, which can also reduce the manual labour required. In addition, mathematics and engineering research communities are still searching for forecasting models that are joined-up, reliable and efficient, as well as versatile and adaptable. To address this need, 'Multi-Wavelets' technology will be employed in this fellowship with a view to transforming flood forecasting routines from a disparate set of activities into a unified automatic framework. The applicant's vision is to exploit the innate capability of Multi-Wavelets technology to reformulate flood forecasting methods by providing a smart modelling foundation for the delivery of timely and accurate flood maps, alongside statistically quantified uncertainties. This research presents a unique opportunity for the applicant, UK academia and UK industry, to establish a world leading capability in a nascent field while addressing Living With Environmental Change (LWEC) priorities for improved forecasting of environmental change. The fellowship research will stimulate the creation of new software infrastructure capable of significantly improving our flood forecasting ability across length scales and under multiple uncertainties, helping us to better design infrastructure against flood risk and to plan for the consequences.