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Title: A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study

Abstract

Water utilities are vulnerable to a wide variety of human-caused and natural disasters. The Water Network Tool for Resilience (WNTR) is a new open source PythonTM package designed to help water utilities investigate resilience of water distribution systems to hazards and evaluate resilience-enhancing actions. In this paper, the WNTR modeling framework is presented and a case study is described that uses WNTR to simulate the effects of an earthquake on a water distribution system. The case study illustrates that the severity of damage is not only a function of system integrity and earthquake magnitude, but also of the available resources and repair strategies used to return the system to normal operating conditions. While earthquakes are particularly concerning since buried water distribution pipelines are highly susceptible to damage, the software framework can be applied to other types of hazards, including power outages and contamination incidents.

Authors:
 [1]; ORCiD logo [2];  [1];  [3]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Purdue Univ., West Lafayette, IN (United States)
  3. US Environmental Protection Agency (EPA), Cincinnati, OH (United States). National Homeland Security Research Center
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1399510
Report Number(s):
SAND-2017-6950J
Journal ID: ISSN 1364-8152; 654955
Grant/Contract Number:
AC04-94AL85000
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Environmental Modelling and Software
Additional Journal Information:
Journal Volume: 95; Journal Issue: C; Journal ID: ISSN 1364-8152
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Klise, Katherine A., Bynum, Michael, Moriarty, Dylan, and Murray, Regan. A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study. United States: N. p., 2017. Web. doi:10.1016/j.envsoft.2017.06.022.
Klise, Katherine A., Bynum, Michael, Moriarty, Dylan, & Murray, Regan. A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study. United States. doi:10.1016/j.envsoft.2017.06.022.
Klise, Katherine A., Bynum, Michael, Moriarty, Dylan, and Murray, Regan. Fri . "A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study". United States. doi:10.1016/j.envsoft.2017.06.022.
@article{osti_1399510,
title = {A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study},
author = {Klise, Katherine A. and Bynum, Michael and Moriarty, Dylan and Murray, Regan},
abstractNote = {Water utilities are vulnerable to a wide variety of human-caused and natural disasters. The Water Network Tool for Resilience (WNTR) is a new open source PythonTM package designed to help water utilities investigate resilience of water distribution systems to hazards and evaluate resilience-enhancing actions. In this paper, the WNTR modeling framework is presented and a case study is described that uses WNTR to simulate the effects of an earthquake on a water distribution system. The case study illustrates that the severity of damage is not only a function of system integrity and earthquake magnitude, but also of the available resources and repair strategies used to return the system to normal operating conditions. While earthquakes are particularly concerning since buried water distribution pipelines are highly susceptible to damage, the software framework can be applied to other types of hazards, including power outages and contamination incidents.},
doi = {10.1016/j.envsoft.2017.06.022},
journal = {Environmental Modelling and Software},
number = C,
volume = 95,
place = {United States},
year = {Fri Jul 07 00:00:00 EDT 2017},
month = {Fri Jul 07 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on July 7, 2018
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