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This is a project within the multi-disciplinary EPSRC and ESRC Centre for Doctoral Training (CDT) on Quantification and Management of Risk & Uncertainty in Complex Systems & Environments, within the Institute for Risk and Uncertainty. The studentship is granted for 4 years and includes, in the first year, a Master in Decision Making under Risk & Uncertainty. The project includes extensive collaboration with prime industry to build an optimal basis for employability.
Outline of project:
The largest uncertainty in predicting river flood risk lies in the accurate estimation of the resistance imposed by the morphology of the river on the flow. This resistance is crucial to estimate because it dictates the river flow velocity and therefore the depth of the water. In industry the common approach is to estimate this resistance based on a representative bed surface grain size that is usually measured at low flows. The simple idea being that a coarser surface imposes a greater flow resistance. However there are two fundamental problems with this approach that create uncertainties in flood risk estimation. First, river bed surfaces display a spatially complex, three-dimensional structure. Thus a representative surface grain size does not fully account for multi-scale roughness effects on near-bed hydraulics. Secondly, during flooding the grain size and morphology of the river changes through transport processes which orientate, imbricate, sort and layer the sediment deposits. Therefore river bed surfaces have systematic patterns of morphology according to flood conditions, and estimates of flow resistance that are made at low flows are not applicable in times of flooding. Thus these simplistic flow resistance models fail, suggesting that this approach is not generally applicable in rivers. This evidence reveals there is an urgent need to rethink the way in which we parameterise flow resistance.
The aim of this studentship is to produce new process-based models of flow resistance that are developed through a better understanding of the complex interaction between river morphology, near-bed hydraulics and flood events. This aim will be achieved through a combined experimental-modelling approach. Using the Liverpool Waves and Current Channel in the Hydraulics Laboratory the student will recreate different flood events (duration and magnitude), examine how river morphology changes, and measure how these changes impact upon near-bed flow hydraulics (http://tinyurl.com/qzlj2d6). The student will use our state-of-the-art PIV system to measure in detail how velocity and turbulence changes with different flood sequences, and use Structure-from-Motion techniques to measure the changing bed geometry. These data will be used to produce new parameterizations of flow resistance that account for the effect of bed geometry complexity - and its change due to flooding - on velocity and turbulence. These new relationships will be incorporated into an existing CFD river flow model. The model will enable the student to quantify the uncertainty in flood risk predictions over a broader range of conditions than those studied in the laboratory. The two major outcomes will be a new modelling tool that can provide the detailed estimates of near-bed hydraulics necessary for accurate estimation of flow resistance, and the first quantification of the effect of changing river morphology and flood conditions on uncertainties in flood risk prediction. Thus the outcomes will be of major benefit to those involved in managing and assessing flood risk.
Expected background: Applicants should have a honours degree (minimum 2.1) or a Masters degree in Environmental Sciences (Geography, Geology or Environmental Sciences), Engineering (preferably Civil, Environmental or Mechanical), or in relevant fields of the Mathematical Sciences. Experience in modelling or conducting flume experiments would be advantageous.
The PhD Studentship (Tuition fees + stipend of £ 14,296 annually over 4 years) is available for Home/EU students. In addition, a budget for use in own responsibility will be provided.