The threat of terrorist action targeting water supplies is often overlooked for the more historically obvious
threats of an air attack or a dirty bomb. Studies have shown that an attack on water is simple to orchestrate, inexpensive
and can result in mass casualties. The twin motivators of the terrorist threat to water along with consumer demands for
safe and potable supplies has lead to a sea change in the drinking water industry. From a historical perspective, most
monitoring in the distribution system as well as source water has been relegated to the occasional snapshot provided by
grab sampling for a few limited parameters or the infrequent regulatory testing required by mandates such as the Total
Coliform Rule. New technologies are being deployed to ameliorate the threat from both intentional and accidental water
contamination. The threat to water and these new technologies are described as well as needs and requirements for new
sensors to improve the monitoring structure.
Both real events and models have proven that drinking water systems are vulnerable to deliberate and/or accidental
contamination. Additionally, homeland security initiatives and modeling efforts have determined that it is relatively easy
to orchestrate the contamination of potable water supplies. Such contamination can be accomplished with classic and
non-traditional chemical agents, toxic industrial chemicals (TICs), and/or toxic industrial materials (TIMs). Subsequent
research and testing has developed a proven network for detection and response to these threats. The method uses offthe-
shelf, broad-spectrum analytical instruments coupled with advanced interpretive algorithms. The system detects and
characterizes any backflow events involving toxic contaminants by employing unique chemical signature (fingerprint)
response data. This instrumentation has been certified by the Office of Homeland Security for detecting deliberate and/or
accidental contamination of critical water infrastructure. The system involves integration of several mature technologies
(sensors, SCADA, dynamic models, and the HACH HST Guardian Blue instrumentation) into a complete, real-time,
management system that also can be used to address other water distribution concerns, such as corrosion. This paper
summarizes the reasons and results for installing such a distribution-based detection and protection system.
Water infrastructure needs in the US are expected to exceed a cost of over 300 billion dollars in the coming
years. While security has become a priority since 9/11 budgets for this expenditure are often constrained. This
necessitates that solutions be dual use in nature. Since 9/11 numerous communities have installed multi-parameter
monitoring stations in the distribution system as early warning systems for potential water security threats. These
systems have recorded large streams of data relevant to water quality in the distribution systems. In this study data
streams from a number of communities are analyzed for pertinent information as to the health and operation of the
distribution system. Changes in water quality are correlated with known causes attributable to day-to-day operational
changes and also anomalous events (pipe bursts, accidental back flows, cross connections, chemical over feeds,
treatment plant problems, nitrification events, etc.). Information concerning what action was taken to ameliorate the
problem will also be linked to the data for the identified events thus demonstrating dual use for these systems.
A system designed to address the problem of distribution system monitoring is described here. The developed system employs an array of common analytical instrumentation, such as pH and chlorine monitors, coupled with advanced interpretive algorithms housed in an event monitor to provide detection/identification-response networks that are capable of enhancing system security and quality. A variety of real world venues and testing protocols were used to verify the efficacy of the system. Deployed systems are shown to demonstrate the capability of learning base line in a rapid timeframe while being capable of detecting and characterizing system anomalies related to security and basic water quality operations. Included are data generated from several real world events including caustic overfeeds, rain events, street work and major line breaks among others.
Drinking water is one of the nation's key infrastructure assets that have been deemed vulnerable to deliberate terrorist attacks. While the threat to reservoir systems and water sources is deemed to be minimal, the vulnerability of the drinking water distribution systems to accidental or deliberate contamination due to a backflow event is becoming a well-recognized possibility. The myriad possible points of incursion into a distribution system and the ease of mounting a backflow event, combined with the fact that little or no quality monitoring occurs after the water has left the treatment plant, makes the danger of such an attack acute. This was clearly stated in a General Accounting Office (GAO) report to Congress that listed the vulnerability of the distribution system to attack as the largest security risk to water supplies. Prior to this there has not been a system capable of detecting such an event and alerting the system's managers so that effects of an attack or accident can be contained. The general scientific consensus is that no practical, available, or cost-effective real-time technology exists to detect and mitigate intentional attacks or accidental incursions in drinking water distribution systems. The rapid detection and identification of breaches of security in the water distribution system is crucial in initiating appropriate corrective action. The ability of a technology system to detect incursion on a real time basis and give indications as to the cause could dramatically reduce the impact of any such scenario. As the vulnerability of the distribution system becomes more widely recognized, the development of a system such as the one described will be an invaluable tool in maintaining the integrity of the nations drinking water supply.
Distribution system monitoring has typically included a minimal set of water quality parameters, acquired at low frequency.
The parameter set, and frequency of data acquisition are insufficient for the surveillance of typical distribution systems' water quality in the event of agent introduction.
An improved methodology is discussed. The method includes a more complete set of water quality parameters acquired at higher frequency, mathematical processing to alarm on deviations from operational baseline, pattern recognition of deviations, statistical analysis of recurring events, and a learning function which allows recurring events to be recognized and categorized as normal operation or unknown. Examples of events from distribution systems are presented and discussed.
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