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Modelling Mixing Mechanisms in 1D Water Network Models


The management of water quality in rivers, urban drainage and water supply networks is essential for ecological and
human well‐being. Predicting the effects of management strategies requires knowledge of the hydrodynamic processes covering spatial scales of a few millimetres (turbulence) to several hundred kilometres (catchments), with a similarly large range of timescales from milliseconds to weeks. This Fellowship will work to address the knowledge gaps due to low turbulence, 3D shapes and unsteady flows, through a programme of laboratory and full‐scale field measurements and the use of system identification techniques. The proposal will provide a new modelling methodology to inform design, appraisal and management decisions made by environmental regulators, engineering consultants and water utilities.

To launch the research, Professor Guymer is organising a kick off workshop.

Aims and Objectives

The aims of the research are to quantify physical flow processes, to develop new approaches for describing solute mixing processes within low Reynolds’ number flows, complex 3D flow fields and unsteady flows and to implement them within 1D numerical network models. The project is novel, integrating fundamental numerical analysis, with focussed laboratory and field studies providing unique data. This will quantify fundamental residence time distributions
(RTDs) which will more accurately describe the mixing mechanisms present within hydraulic networks. It integrates knowledge across several research fields, using experience gained over many years, to address a major societal concern: the occurrence of contaminants in water systems.

The following objectives apply:

  1. Perform a Data Mining exercise to identify & analyse high quality solute mixing data
  2. Conduct laboratory solute tracer and hydrodynamic studies to quantify and interpret mixing within low Reynolds’ Number, complex 3D and unsteady flows
  3. Develop intelligent field instrumentation to conduct remote, automated tracing studies
  4. Perform field measurement of residence time distributions in urban drainage and river systems
  5. Utilise the laboratory & field data, and validated CFD modelling, to quantify RTDs appropriate for describing the influence of shape changes and unsteady flows on mixing
  6. Implement novel mixing descriptions and conduct scenario modelling to explore the sensitivity of predictions to residence time distributions
  7. Disseminate the validated modelling methodology, together with appropriate descriptions of the mixing processes


This project is funded by


Project Partners