Abstract
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.
Original language | English |
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Pages (from-to) | 908-917 |
Number of pages | 10 |
Journal | Journal of Hydrology |
Volume | 573 |
Early online date | 4 Apr 2019 |
DOIs | |
Publication status | Published - 1 Jun 2019 |
Funding
This study was conducted as part of the Water Informatics, Science and Engineering (WISE) Centre for Doctoral Training (CDT), funded by the UK Engineering and Physical Sciences Research Council , Grant No. EP/L016214/1 . Olivia Bailey is supported by a research studentship from this CDT. The authors acknowledge Wessex Water for providing the sewerage data utilised in this work.
Keywords
- 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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Tom Arnot
- Department of Chemical Engineering - Senior Lecturer
- Centre for Sustainable Chemical Technologies (CSCT)
- Water Innovation and Research Centre (WIRC)
- Centre for Regenerative Design & Engineering for a Net Positive World (RENEW)
- Institute of Sustainability and Climate Change
- Centre for Doctoral Training in Real-Time Digital Water-Based Systems for Environmental Health Protection (RED-ALERT CDT)
Person: Research & Teaching, Core staff, Affiliate staff
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Jan Hofman
- Department of Chemical Engineering - Professor
- Water Innovation and Research Centre (WIRC)
- Centre for Nanoscience and Nanotechnology
- Centre for Regenerative Design & Engineering for a Net Positive World (RENEW)
- Institute of Sustainability and Climate Change
- Centre of Excellence in Water-Based Early-Warning Systems for Health Protection (CWBE)
Person: Research & Teaching, Core staff, Affiliate staff