Full Description

The Water Security (WS) initiative contamination warning system (CWS) pilot deployed inCincinnati is comprised of five monitoring and surveillance components, one of which is onlinewater quality monitoring. While real-time water quality monitoring has the potential todetect many contaminants of concern, they do not speak to the feasibility of discriminating waterquality changes attributable to contamination from normal variability in the baseline. To addressthis aspect of the problem, change detection algorithms, referred to as event detection systems(EDS), were utilized in the Cincinnati CWS pilot.EDS tools must be trained to the specific water quality being monitored and then tuned tobalance the trade-off between false alarms and false negatives (or undetected contaminationevents). To facilitate this training and tuning, a large-scale evaluation study was performed inwhich two EDS tools were challenged with thousands of datasets containing background datafrom the CWS pilot and simulated contamination incidents (Umberg and Allgeier, 2007).Contamination simulations were based on laboratory experimentation and theoretical analysesthat demonstrate the correlation between contaminant concentration and a change in one or morewater quality parameters, including: TOC, CL2, COND, ORP, pH, and TURB. The results ofthis study were not only instrumental in training and tuning the EDS tools for deployment at theCWS pilot, but also illustrate fundamental aspects of the performance capabilities of waterquality monitoring and event detection.This paper presents a subset of the results from this large-scale evaluation study, focusing on theability of the two EDS tools under study to detect different contaminant types. Includes 9 references, tables, figures.

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Edition: Vol. - No. Published: 04/01/2008 Number of Pages: 15File Size: 1 file , 830 KB