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Water quality modeling in the dead end sections of drinking water (Supplement)

Metadata Updated: November 12, 2020

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated concentration profiles showed significant dependence on the spatial distribution of the flow demands compared to temporal variation.

This dataset is associated with the following publication: Abokifa, A., J. Yang , C. Lo, and P. Biswas. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 18(89): 107-117, (2015).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

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References

https://www.researchgate.net/publication/284233815_Water_Quality_Modeling_in_the_Dead_End_Sections_of_Drinking_Water_Distribution_Networks

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Publisher U.S. EPA Office of Research and Development (ORD)
Maintainer
Identifier A-h9wf-367
Data Last Modified 2015-12-14
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Harvest Object Id 0d31b24f-2cb5-42ac-94a6-88eb192b5777
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Program Code 020:000
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents https://www.researchgate.net/publication/284233815_Water_Quality_Modeling_in_the_Dead_End_Sections_of_Drinking_Water_Distribution_Networks
Source Datajson Identifier True
Source Hash 4f7bb48c3e5fce2971637167e112b5e4b0385284
Source Schema Version 1.1

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