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OFFICE OF RESEARCH AND DEVELOPMENT
National Homeland Security Research Center
TECHNICAL BRIEF
Assessing Potential Impacts Associated With Contamination
Events in Water Distribution Systems: A Sensitivity Analysis
Purpose
This study examines the adverse effects of contamination events in
water distribution systems using models for 12 actual systems that
serve populations ranging from about 104 to over 10s persons. This
study extends previous work (Davis and Janke 2010) and provides an
improved understanding of the nature of the adverse effects that
could be associated with contamination events. The results
presented support water utilities, their consultants, and researchers
in conducting contaminant vulnerability analyses and designing and
implementing contamination warning systems.
Methodology
In this study, adverse effects are defined as the number of people
who are exposed to a contaminant above some dose level (mass of contaminant in milligrams) due to ingestion
of contaminated tap water. The number of people who receive a dose above a particular level defines the
impact associated with an event. Impact refers to the number of people exposed above some level.
A wide range of dose levels are considered in order to accommodate a wide range of potential contaminants.
For a particular contaminant, dose level can be related to a health effect level. For example, a dose level could
correspond to the median lethal dose, i.e., the dose that would be fatal to 50% of the exposed population. The
dose level required to reach a common endpoint can vary by orders of magnitude, depending on the toxicity of
the contaminant. Highly toxic contaminants may be associated with a particular response at a very low dose
level, whereas contaminants with low toxicity may only be associated with the same response at a much higher
dose level.
This study examines how impacts depend on five factors that either define the nature of a contamination event
or involve assumptions that are used in assessing exposure to the contaminant: (1) duration of contaminant
injection, (2) time of contaminant injection, (3) quantity or mass of contaminant injected, (4) population
distribution in the water distribution system, and (5) the ingestion pattern of the potentially exposed
population. For each of these factors, the sensitivities of impacts to injection location and contaminant toxicity
are also examined.
The sensitivity of impacts to the various factors studied is determined by comparing the impacts associated with
different cases of a factor, for example, comparing 1-h versus 24-h injection durations. Impacts are estimated
for injections at all non-zero demand nodes in a particular model. For the 12 networks considered in this study,
the comparisons involve simulation of injections at thousands of nodes. In order to facilitate comparisons,
locations of contaminant injection, which consist of network model nodes, are identified in terms of the ranking
of the associated impact. The nth percentile injection node is the node associated with the nth percentile impact.
Two types of sensitivities are examined with respect to the various factors: sensitivity that results in variations
in the magnitude of the nth percentile impact and sensitivity that results in changes in the injection locations that
are associated with the nth percentile and higher impacts.
ADVANCING OUR NATION'S SECURITY THROUGH SCIENCE
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Results
Impacts were found to be sensitive to all the factors examined. The degree of sensitivity is dependent on the
particular water system, the location of contaminant injection, and the dose level or toxicity level of the
contaminant considered. Sensitivity of impacts to all the factors considered tends to increase with decreasing
toxicity of the contaminant, with considerable inter-network variability. With the exception of the population
distribution, sensitivity to the various factors tends to be highest at lower impact levels (e.g., impacts below the
80th percentile). Conversely, for the population distribution factor, sensitivity is lowest at the lower impact
levels. For injection duration, impacts generally are higher for longer duration injections. Definite patterns are
present in the sensitivity of impacts to injection time, but these vary substantially across the networks. As
would be expected, impacts are larger for larger mass injections, but the sensitivity can vary dramatically
depending on the contaminant toxicity level and the network. Estimated impacts can be sensitive to
assumptions about how population is distributed in a network, particularly at high impact levels and low toxicity
levels, again with considerable variability across networks. Finally, impacts can be sensitive to assumptions
about ingestion patterns in the potentially exposed population, with sensitivities varying across networks and
tending to be highest for low toxicity levels.
When the various factors are considered together (not including the ingestion model) and depending on the
contaminant toxicity level, the magnitudes of impacts are most sensitive to injection mass or duration:
• At high toxicity levels, impacts are most sensitive to injection duration, although the relative changes in
impacts due to changes in duration may not be large for high percentile impacts. Impacts are larger for
longer duration injections and the increases tend to be more important for lower percentile impacts.
• At high toxicity levels, impacts are not particularly sensitive to injection mass, given a likely range in
injection masses.
• At low toxicity levels, impacts are most sensitive to injection mass, with impacts increasing for larger
injection mass.
The influence of the various factors on the location of high percentile injection locations can be as important or
more important than their influence on the magnitudes of impacts. In addition, the choice of contaminant has a
major influence on which nodes are high impact injection locations. The sharing (overlap) of the same high-
percentile injection nodes for different values of a factor can vary substantially by contaminant and impact level
(percentile of impact). Overlap tends to decrease with decreasing toxicity of the contaminant and increasing
impact level for all the factors considered, with considerable variability among the networks.
Applications
The results of this sensitivity analysis can be applied in the design of CWSs and in the analysis of vulnerabilities
of water distribution systems. CWSs are designed to minimize the adverse effects associated with a
contamination event. Therefore, estimating such adverse effects is an important part of any CWS design. This
sensitivity analysis should encourage designers of vulnerability studies and CWSs to consider (1) the factors that
define a contamination event, (2) the possible uncertainties associated with establishing the distribution of the
population within a network and estimating ingestion doses, (3) the contaminant used in determining adverse
effects, and (4) network-to-network variability.
For more information: Visit the NHSRC Web site at www.epa.gov/nhsrc
Technical Contact: Robert Janke (513) 569-7160, janke.robert@epa.gov
Reference: Davis, M. J., and Janke, R. (2010). "Patterns in potential impacts associated with contamination events in
water distribution systems." Journal of Water Resources Planning and Management, (16 March 2010),
10.1061/(ASCE)WR. 1943-5452.0000084
November, 2010
EPA/600/R-10/061
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