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Title: Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

Abstract

Network model detail can influence the accuracy of results from analyses of water distribution systems. Some previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregated adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. But, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).

Authors:
 [1];  [2]
  1. Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division
  2. US Environmental Protection Agency (EPA), Cincinnati, OH (United States). National Homeland Security Research Center
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); USEPA
OSTI Identifier:
1393929
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Water Resources Planning and Management
Additional Journal Information:
Journal Volume: 141; Journal Issue: 1; Journal ID: ISSN 0733-9496
Publisher:
American Society of Civil Engineers (ASCE)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; drinking water; optimization; public health; simulation; water distribution systems; water quality

Citation Formats

Davis, Michael J., and Janke, Robert. Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events. United States: N. p., 2015. Web. doi:10.1061/(ASCE)WR.1943-5452.0000436.
Davis, Michael J., & Janke, Robert. Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events. United States. doi:10.1061/(ASCE)WR.1943-5452.0000436.
Davis, Michael J., and Janke, Robert. Thu . "Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events". United States. doi:10.1061/(ASCE)WR.1943-5452.0000436. https://www.osti.gov/servlets/purl/1393929.
@article{osti_1393929,
title = {Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events},
author = {Davis, Michael J. and Janke, Robert},
abstractNote = {Network model detail can influence the accuracy of results from analyses of water distribution systems. Some previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregated adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. But, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).},
doi = {10.1061/(ASCE)WR.1943-5452.0000436},
journal = {Journal of Water Resources Planning and Management},
number = 1,
volume = 141,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Journal Article:
Free Publicly Available Full Text
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Cited by: 1 work
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