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Probabilistic Performance Specifications for SuDS/Green Infrastructure
This project will utilise commercial and in-house hydrological/hydraulic modelling tools to develop robust probabilistic performance specifications for SuDS (Sustainable Drainage Systems). We will utilise continuous long time-series rainfall, incorporating best estimates of climate change scenarios, to capture the hydrological functioning of these systems under both extreme and routine rainfall inputs.

Use of Machine Learning (AI) for Rainfall Disaggregation
This proposal follows on from our EPSRC-funded 'Urban Green DaMS' project. DaMS refers to 'Design and Modelling of Sustainable Drainage Systems (SuDS)'. One of the outcomes from this project was confirmation that design work should be underpinned by the use of continuous simulation modelling (to properly capture how these nature-based solutions (e.g. bioretention cells) wet and dry in response to weather patterns and plant growth cycles. To do this, we (i.e. academics and practitioners in the UK) need appropriate continuous rainfall time-series at high temporal resolution (e.g. 5 min time-steps). UKCP18 provides us with an excellent resource in terms of future rainfall time-series, but these are only available with hourly time-steps. We need a tool that disaggregates these projected future rainfall time-series from hourly to 5-minute time-steps. There are several different ways of doing this, but we would like to try AI, which is often well-suited to 'pattern-matching' type problems. The NIMROD radar data provides access to high quality historic rainfall data at high temporal resolution, which can be used to train the AI.

Sustainable growing media for vegetated SuDS
Vegetated SuDS, e.g. bioretention cells, manage rainfall inputs and/or stormwater inflows through a range of hydrological processes including interception and evapotranspiration (ET) by plants, infiltration at the surface, percolation through the growing media and exfiltration into the native subsoil. There are strong drivers to utilise locally-recycled growing media within these SuDS, but there are risks & uncertainties in so doing. For example: how accurate are the materials data sheets associated with each delivery of the media, and how much variability is typical/acceptable?; how do different materials affect the performance of the blended mixture overall, both at the time of installation and as the media evolves/ages over time?; how do media characteristics impact on the risk of clogging at the surface, and how can this be mitigated? The aim of this PhD is to undertake detailed laboratory studies to answer all or some of the above questions, focusing on currently-available recycled materials. Use will be made of infiltration columns to assess hydraulic conductivity and laboratory visualisation techniques utilising fluorescent tracer particles.

Beyond Drainage: The Impact of SuDS on Urban Microclimates
Urban stormwater management increasingly makes use of SuDS (Sustainable Drainage Systems), which often incorporate open water and/or vegetation. Evapotranspiration from SuDS is expected to have a beneficial (cooling) impact on the urban microclimate, and may also have benefits for the indoor climate in adjacent buildings. The project will use a range of modelling tools (and possibly some experimental work) to quantify these effects.

Inflow Capture Efficiency for SuDS inlets
This project will focus on the development of robust CFD-modelling procedures to enable better design and analysis of inlets used to direct road runoff into SuDS (Sustainable Drainage Systems) devices such as bioretention cells. Use will be made of new and/or existing field or laboratory data sets to validate the CFD work.

Computational Fluid Dynamics (CFD) Applications in Urban Drainage
CFD modelling tools enable engineers to visualise 3D flow patterns within complex structures and to represent the movement of sediments and/or dissolved materials within the flows. This approach has provided insights into, for example, sediment deposition within combined sewage storage chambers, gross solids separation in combined sewer overflows and the passage of intermittently-discharged solutes through pipes and manholes. There are a number of ways in which this work might be further developed, including the exploration of links between residence time distributions and energy losses or the development of robust time-dependent modelling methodologies. In all cases use will be made of either new or existing field or laboratory data sets to validate the CFD work.