Optimal sampling locations contamination extent WDS figure dataset 08242018
The dataset was created from simulating contamination incidents in a water distribution system and selecting optimal sampling locations to identify the contamination incident. This data includes the number of contamination scenarios still credible after each sampling cycle; the number of nodes correctly identified as being contaminated after each sampling cycle; and the number of nodes identify as likely contaminated, likely not contaminated, and uncertain after each sampling cycle.
This dataset is associated with the following publication:
Rodriguez, S., M. Bynum, C. Laird, D. Hart, K. Klise, J. Burkhardt, and T. Haxton. Optimal sampling locations to reduce uncertainty in contamination extent in water distribution systems. Journal of Infrastructure Systems. American Society of Civil Engineers (ASCE), Reston, VA, USA, 27(3): 1-31, (2021).
Resources
1 resource available
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Opt_Sampling_Paper_Figure_Data.xlsx
APPLICATION/VND.OPENXMLFORMATS-OFFICEDOCUMENT.SPREADSHEETML.SHEET
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "020:00" ] |
| contactPoint |
{ "fn": "Terranna Haxton", "hasEmail": "mailto:haxton.terra@epa.gov" } |
| description | The dataset was created from simulating contamination incidents in a water distribution system and selecting optimal sampling locations to identify the contamination incident. This data includes the number of contamination scenarios still credible after each sampling cycle; the number of nodes correctly identified as being contaminated after each sampling cycle; and the number of nodes identify as likely contaminated, likely not contaminated, and uncertain after each sampling cycle. This dataset is associated with the following publication: Rodriguez, S., M. Bynum, C. Laird, D. Hart, K. Klise, J. Burkhardt, and T. Haxton. Optimal sampling locations to reduce uncertainty in contamination extent in water distribution systems. Journal of Infrastructure Systems. American Society of Civil Engineers (ASCE), Reston, VA, USA, 27(3): 1-31, (2021). |
| distribution |
[ { "title": "Opt_Sampling_Paper_Figure_Data.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502586/Opt_Sampling_Paper_Figure_Data.xlsx" } ] |
| identifier | https://doi.org/10.23719/1502586 |
| keyword |
[ "Drinking water distribution system", "Source identification", "drinking water distribution system modeling", "grab samples", "model uncertainty", "modeling and optimization" ] |
| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2018-08-24 |
| programCode |
[ "020:060" ] |
| publisher |
{ "name": "U.S. EPA Office of Research and Development (ORD)", "subOrganizationOf": { "name": "U.S. Environmental Protection Agency", "subOrganizationOf": { "name": "U.S. Government" } } } |
| references |
[ "https://doi.org/10.1061/(asce)is.1943-555x.0000628" ] |
| rights |
null
|
| title | Optimal sampling locations contamination extent WDS figure dataset 08242018 |
