Modelling Mixing Mechanisms in 1D Water Network Models

Lead Research Organisation: University of Sheffield
Department Name: Civil and Structural Engineering

Abstract

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. Predicting underlying water quality processes and their human and ecological impact is complicated as they are dependent on contaminant concentration. Current water quality modelling methods range from complex three dimensional computational fluid dynamics (3D CFD) models, for short time and small spatial scales, to one-dimensional (1D) time dependent models, critical for economic, fast, easy-to-use applications within highly complex situations in river catchments, water supply and urban drainage systems. Mixing effects in channels and pipes of uniform geometry can be represented with some confidence in highly turbulent, steady flows. However, in the majority of water networks, the standard 1D model predictions fall short because of knowledge gaps due to low turbulence, 3D shapes and unsteady flows. This Fellowship will work to address the knowledge gaps, delivering a step change in the predictive capability of 1D water quality network models. It will achieve this via the strategic leadership of a programme of laboratory and full-scale field measurements, the implementation of system identification techniques and active engagement with primary users. The proposal covers aspects from fundamental research, through applications, to end-user delivery, by providing a new modelling methodology to inform design, appraisal and management decisions made by environmental regulators, engineering consultants and water utilities.

Planned Impact

1D water quality network models are used in water supply, urban drainage and river catchment management. Regulators, operators, consultants, service suppliers and software developers have acknowledged the inadequacy of current knowledge and have welcomed this initiative to generate improved integrated understanding and more robust management tools. Evidence of this is provided in the strong Statements of Support from the key relevant regulators, Environment Agency and Drinking Water Inspectorate; through active, industry-leading consultants (Clear/RPS, Mouchel, JBA, WRc) who provide engineering guidance across the range of water network systems, to a major UK water utility (Severn Trent Water Ltd, who are required under the Water Framework Directive to implement cost-effective measures and to supply drinking water to achieve specific standards); and major international software developers (DHI). Additionally, Unilever, a major multi-national consumer products company, with expertise in environmental assessment, is providing guidance on wider catchment-scale applications. In the longer term, society will benefit significantly from the implementation of more accurate 1D water quality models as rural and urban environments will become better places to live, with improved water quality, and added biodiversity and amenity values.
Improved knowledge, application and impact from this proposal will contribute to the UK establishing itself as an innovation powerhouse in the global water technology sector, which the recent UKWRIP report estimates, in the period up to 2020, to amount to over $50 billion.
How will they benefit from this research?
- Regulators, utilities, and consultants will benefit directly from the new descriptions of mixing within network components and improved, validated modelling methodologies that will lead to better-informed network design, maintenance and management decisions.
- Academics and practitioners will benefit from rigorous methodologies for experimental and numerical mixing and residence time characterisation that will have generic value for future research and development activities relating to all types of mixing and water quality processes.
- Benefit to research staff - Staff engaged on the project will work within a high calibre research environment, with strong international links, undertaking fundamental research through to applied field studies and state-of-the-art model development, whilst interacting with regulators, utilities and a range of consultants. This represents a unique and highly valued skill set that will equip them to progress authoritatively into academic or practitioner roles within the global water technology sector.

Publications

10 25 50
 
Title Fluorescent dye traces in four UK sewer networks 
Description This dataset describes experimental fluorescent dye traces (temporal concentration profiles) recorded in manholes within combined sewer networks located in four different cities across the United Kingdom. It accompanies the journal article entitled "Quantifying mixing in sewer networks for source localisation" (Sonnenwald et al., submitted). This dataset was collected by Professor Ian Guymer and colleagues. This archive was funded by EPSRC grant EP/P012027/1 and the UK Health Security Agency. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Fluorescent_dye_traces_in_four_UK_sewer_networks/204802...
 
Title Fluorescent dye traces in four UK sewer networks 
Description This dataset describes experimental fluorescent dye traces (temporal concentration profiles) recorded in manholes within combined sewer networks located in four different cities across the United Kingdom. It accompanies the journal article entitled "Quantifying mixing in sewer networks for source localisation" (Sonnenwald et al., submitted). This dataset was collected by Professor Ian Guymer and colleagues. This archive was funded by EPSRC grant EP/P012027/1 and the UK Health Security Agency. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Fluorescent_dye_traces_in_four_UK_sewer_networks/204802...
 
Title Fluorescent dye traces in four UK sewer networks 
Description This dataset describes experimental fluorescent dye traces (temporal concentration profiles) recorded in manholes within combined sewer networks located in four different cities across the United Kingdom. It accompanies the journal article entitled "Quantifying mixing in sewer networks for source localisation" (Sonnenwald et al., submitted). This dataset was collected by Professor Ian Guymer and colleagues. This archive was funded by EPSRC grant EP/P012027/1 and the UK Health Security Agency. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Fluorescent_dye_traces_in_four_UK_sewer_networks/204802...
 
Title Longitudinal and transverse dispersion within cylinder arrays with varying cylinder diameter distributions 
Description This dataset describes CFD simulations run at the University of Sheffield in 2019-2020 to investigate the effects of stem size distribution on dispersion within random cylinder arrays. It reports geometry characteristics, model results, and dispersion coefficients. 159 geometries were generated and 137 CFD simulations were run consisting of combinations of 8 stem diameter distributions and 20 solid volume fractions. This dataset was created by Dr Fred Sonnenwald under EPSRC grant EP/P012027/1. It accompanies the journal article entitled "The Impact of Cylinder Diameter Distribution on Longitudinal and Transverse Dispersion within Random Cylinder Arrays". 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Stem_Diameter_Distribution_transverse_and_longitudinal_...
 
Title Longitudinal and transverse dispersion within cylinder arrays with varying cylinder diameter distributions 
Description This dataset describes CFD simulations run at the University of Sheffield in 2019-2020 to investigate the effects of stem size distribution on dispersion within random cylinder arrays. It reports geometry characteristics, model results, and dispersion coefficients. 159 geometries were generated and 137 CFD simulations were run consisting of combinations of 8 stem diameter distributions and 20 solid volume fractions. This dataset was created by Dr Fred Sonnenwald under EPSRC grant EP/P012027/1. It accompanies the journal article entitled "The Impact of Cylinder Diameter Distribution on Longitudinal and Transverse Dispersion within Random Cylinder Arrays". 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Stem_Diameter_Distribution_transverse_and_longitudinal_...
 
Title Stem Diameter Distribution transverse and longitudinal Dispersion within cylinder arrays 
Description This dataset describes CFD simulations run at the University of Sheffield in 2019-2020 to investigate the effects of stem size distribution on dispersion within random cylinder arrays. It reports geometry characteristics, model results, and dispersion coefficients. 159 geometries were generated and 137 CFD simulations were run consisting of combinations of 8 stem diameter distributions and 20 solid volume fractions. This dataset was created by Dr Fred Sonnenwald under EPSRC grant EP/P012027/1. It accompanies the journal article entitled "The Impact of Stem Diameter Distribution on Transverse and Longitudinal Dispersion within Random Cylinder Arrays". 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Stem_Diameter_Distribution_transverse_and_longitudinal_...
 
Title Stem Diameter Distribution transverse and longitudinal dispersion within cylinder arrays 
Description This dataset describes CFD simulations run at the University of Sheffield in 2019-2020 to investigate the effects of stem size distribution on dispersion within random cylinder arrays. It reports geometry characteristics, model results, and dispersion coefficients. 159 geometries were generated and 137 CFD simulations were run consisting of combinations of 8 stem diameter distributions and 20 solid volume fractions. This dataset was created by Dr Fred Sonnenwald under EPSRC grant EP/P012027/1. It accompanies the journal article entitled "The Impact of Stem Diameter Distribution on Transverse and Longitudinal Dispersion within Random Cylinder Arrays" (under review). 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://figshare.shef.ac.uk/articles/dataset/Stem_Diameter_Distribution_transverse_and_longitudinal_...
 
Description This package implements the compartmental mixing model described in the journal article Predicting manhole mixing using a compartmental model (Sonnenwald et al., submitted). This model uses jet theory to divide a manhole into multiple zones and work out the exchange between zones. Using these values, the model then uses compartmental mixing theory to predict downstream concentrations based on upstream concentrations. This document outlines running the model and how the code functions. The accompanying document Further details and equations of a compartmental model for describing mixing in manholes provides the theoretical background and equations used. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
URL https://figshare.shef.ac.uk/articles/software/Code_for_a_compartmental_model_for_describing_mixing_i...
 
Description This package implements the compartmental mixing model described in the journal article Predicting manhole mixing using a compartmental model (Sonnenwald et al., submitted). This model uses jet theory to divide a manhole into multiple zones and work out the exchange between zones. Using these values, the model then uses compartmental mixing theory to predict downstream concentrations based on upstream concentrations. This document outlines running the model and how the code functions. The accompanying document Further details and equations of a compartmental model for describing mixing in manholes provides the theoretical background and equations used. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
URL https://figshare.shef.ac.uk/articles/software/Code_for_a_compartmental_model_for_describing_mixing_i...
 
Description IAHR Key Note lecture 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact On-line presentation to ~300 Conference participants
Year(s) Of Engagement Activity 2020
URL https://iahr2020.pl/keynote-lectures/
 
Description Interview for Polish Academy of Sciences magazine 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact -
Year(s) Of Engagement Activity 2020
 
Description Keynote lecture at 9th International Symposium on Environmental Hydraulics, 18- 22 July 2021, Seoul, Republic of Korea. 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact International conference to generate discussion around the physical processes contributing to longitudinal dispersion on the natural environment. Generated several questions, good discussion and follow up exchanges.
Year(s) Of Engagement Activity 2021
URL https://sites.google.com/view/9thiseh/keynote-lectures
 
Description Kick-off meeting for Prof. Ian Guymer's EPSRC Fellowship, 16/01/2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Kick-off meeting for Prof. Ian Guymer's EPSRC Fellowship, 16/01/2018
Year(s) Of Engagement Activity 2018