The PODDS model, developed by the Pennine Water Group at the University of Sheffield has been shown capable of predicting the discolouration response of distribution networks to changes in hydraulic conditions. Results highlighting the capabilities of the full model are presented in Figure 1. The model is based on the novel application of cohesive transport theory and its development has led to a step change in philosophy and perception relating to discolouration. The initial PODDS research project however did not include development of the model into a tool suitable to be readily utilised by the water industry. Practical application is limited by the scope of the parameter dataset and the time required to apply the full model to complex networks.

This project is therefore a way for the project collaborators to lead the industry in developing and producing a practical tool for planning discolouration related operational and maintenance strategies.

Figure 1. Example simulation results for use of full PODDS model




Overall this project is aimed at the development of tools and knowledge to facilitate the maintenance of asset performance using proactive, forward looking approaches.
1. Undertake additional fieldwork, using well established methodologies, to develop a robust dataset of parameter values to populate the PODDS model and its derivatives.
2. Develop a simplified discolouration risk (potential) scoring methodology . This will be built into an EPAnet compatible tool and tested.
3. Undertake repeat field investigations (as in objective 1) to establish material regeneration rates to inform maintenance return intervals.




1. Dataset of model parameter values to populate the PODDS model. This will allow assignment of parameters values at pipe level, on the basis of GIS asset data and other available information.
2. Methodology and EPAnet based software tool for the evaluation of discolouration risk (potential) based on the PODDS modelling approach and parameter database.
3. Quantification of discolouration material regeneration (or accumulation) rates occurring within real systems, and interpretation with respect to the contributing factors.
4. Reports on fieldwork monitoring at each site to provide details of operations undertaken, data plots and model fitting.
5 . A final project report with executive summary.

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