AWWA ACE59853

Much attention has recently been placed on the vulnerability of the U.S. drinking water supplies to assault by terrorists. That our systems, as they are currently configured, are vulnerable to attack has been widely recognized. While most supply sources are limited in their vulnerability due to the massive volumes of water involved, the distribution systems remain a vulnerable and tempting target as was clearly stated in a recent GAO report to Congress that listed the vulnerability of the distribution system to attack as the largest security risk to water supplies. Research on a system designed to address the problem of distribution system monitoring is described in this paper. The developed system employs an array of common analytical instrumentation, such as pH and chlorine monitors, coupled with advanced interpretive algorithms to provide detection/identification-response networks that are capable of enhancing system security, as has been advocated by several Federal research initiatives. Through the use of laboratory testing in beakers, computer modeling, pilot scale testing on pipe loops and real world beta site deployment, the system has been shown to be effective in detecting a wide diversity of possible threats. The system has been challenged with, and found effective against, a variety of agents including TICs (toxic industrial chemicals), TIMs (toxic industrial materials), and chemical and biological warfare agents. Other possible more obscure classes of threat agents such as street drugs, homemade toxins, and commercial agricultural chemicals have also been tested. In addition, the system has been shown to recognize common accidental intrusions such as antifreeze and sewage. The response of these various agents not only detects the presence of a contaminant, but the unique responses elicited from the sensor array allows for the possibility of identification. Through the use of a searchable library of agent profiles, the system described is capable of providing not only an alarm, but also an identification of the likely cause. The profiles of over 60 of the most likely threat agents and common contaminants have been complied. In addition, a proprietary baseline estimator dramatically and immediately reduces false warnings due to regular fluctuations in operational parameters upon start-up. As time since deployment increases, the number of false positives is rapidly reduced to near zero by the system's programmed ability to learn what is normal for a given operation. Includes 11 references, tables, figures.