AWWA WQTC65781

The primary goal of a Contaminant Warning System (CWS) is to quickly detect a possible contamination incident within a water distribution system so that action can be taken to minimize consequences. The US Environmental Protection Agency's (USEPA's) Water Security (WS) Initiative (formerly WaterSentinel) seeks to design, deploy, and evaluate a model CWS. The WS-CWS model combines multiple monitoring and surveillance strategies including online water quality monitoring, sampling and analysis, enhanced security monitoring, consumer complaint surveillance, and public health surveillance. Online water quality (WQ) monitoring is the focus of the evaluation described in this paper. This component consists of monitoring stations placed strategically throughout the water distribution system that contain sensors that continuously monitor various WQ parameters. It is impractical to install sensors that directly monitor for each possible contaminant because there are simply too many potential contaminants and a lack of sensor technologies to cover even a fraction of these contaminants. Therefore, under the WS-CWS design, contamination is detected indirectly by monitoring standard WQ parameters in an attempt to identify water quality anomalies, or deviations from an established water quality base state, that might be indicative of contamination. Anomalies in one or more WQ parameters can provide early warning of contamination, but only if they can be picked out of noisy background data. Distribution system water quality data is naturally variable and largely unpredictable, and the imperfect sensor hardware that collects the data adds to the uncertainty. Therefore, the online monitoring component of WS-CWS relies upon event detection algorithms to distinguish between normal variations in water quality and changes in water quality triggered by abnormal conditions. In this paper, event detection system (EDS) refers to a software package that includes event detection algorithm(s). In practice, EDS tools will work in near real-time by receiving data via remote telemetry through the water utility's supervisory control and data acquisition (SCADA) system, perform an analysis in near real-time, and return a result (i.e., either sound an alarm or not, or indicate the probability of an event on an operator's screen). While such abnormality detection tools have been used in other applications, there is little experience applying them to detection of anomalies in drinking water systems. The WS-CWS pilot continues to provide a unique opportunity to collect data necessary for a rigorous evaluation of EDS tools. This paper describes the evaluation approach developed as part of the WS Initiative including the experimental matrix and performance measures used, the two EDS tools evaluated and deployed at the WS-CWS pilot utility, and a portion of the results of the evaluation conducted in the Spring of 2007. The primary objectives of this evaluation included selecting one or more EDS tool for deployment at the pilot utility, establishing a process for evaluating EDS tools which mimics normal utility operating conditions, improving understanding of EDS tool capabilities, and quantifying the performance of EDS tools. Includes 11 references, tables, figures.