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WDS Hydraulics and WQ Uncertainty Dataset
OwnerUnited State Environmental Protection Agency - view all
Update frequencyunknown
Last updatedabout 1 year ago
Format
Overview

The GitHub site has the dataset used to create the manuscript figures, which examined which simulation parameters influenced the spread of contamination within a water distribution system. The dataset includes the values for the metrics of interest, which were extent of contamination, population impacted, extent of contamination in the unknown zone, and the population impacted in the unknown zone. These values changed according to the simulation parameter combination set that was used in modeling the affects of a contamination incident within a water distribution system. These parameters included demand, valve closure, contaminant reaction coefficient, injection start time, injection duration, and injection location (as listed in Table 1 of the paper). Two different water distribution system models were used in the paper, the KL network and the N6 network. In addition, some of the simulation model input files that were used to create the data are also provided on the GitHub site, but not all of the input files are provided since there were approximately 25 million simulations. A README file is provided on the GitHub site for more explanation of the files provided. This dataset is associated with the following publication: Hart, D., J.S. Rodriguez, J. Burkhardt, B. Borchers, C. Laird, R. Murray, K. Klise, and T. Haxton. Quantifying hydraulic and water quality uncertainty to inform sampling of drinking water distribution systems. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT. American Society of Civil Engineers (ASCE), Reston, VA, USA, 145(1): ., (2019).

contamination incidentsdrinking water distribution systemextent of contaminationuncertaintywater distribution system modeling
Additional Information
KeyValue
dcat_modified2018-10-26
dcat_publisher_nameU.S. EPA Office of Research and Development (ORD)
guidhttps://doi.org/10.23719/1390121
ib1_trust_framework[]
language
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    8d552fc5-c611-47b0-84a7-b0af11d04cb0
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