Population growth and climate change place a strain on water resources; hence, there are growing initiatives to reduce household water use. UKWIR (2016) have a stated aim to halve water abstraction by 2050. This will significantly reduce inflow to sewer systems and increase wastewater concentration. This work presents a new stochastic sewer model that can be used to predict both hydraulic and pollutant loading for various water saving scenarios. The stochastic sewer model is based on integration of the stochastic water demand model SIMDEUM® with the InfoWorks ICM® (Sewer Edition) hydraulic model and software. This model has been developed using foul sewer networks, i.e. where household discharges are the dominant inflow; however, it could also be used in combined sewage systems where rainwater flows would add to the stochastic dry weather flow (DWF). The stochastic sewer model was tested and validated on several real catchments in the Wessex Water area of the UK. Calibration was carried out using metered consumption data. The stochastic sewer model gives an accurate prediction of the diurnal patterns of sewage discharge at a household level and was validated using real flow measurements within the catchment. The results obtained indicate that this model can be used to accurately predict changes in flow due to water conservation. A preliminary study for the impact of low water use on this validated network model has been conducted and it was found that overnight and daytime flow was reduced by up to 80% whereas evening flows remained largely similar. Extended stagnation times were observed in the street scale pipes (150 mm) in the low water use scenario.
- Household discharge
- Reduced water consumption
- Sewer design
- Stochastic sewer modelling
- Wastewater quality
- Water conservation
ASJC Scopus subject areas
- Water Science and Technology
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- Department of Chemical Engineering - Senior Lecturer
- Centre for Sustainable and Circular Technologies (CSCT)
- Water Innovation and Research Centre (WIRC)
- Centre for Regenerative Design & Engineering for a Net Positive World (RENEW)
Person: Research & Teaching, Core staff