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AWWA WSC70043
- Beyond Security: Real-Time Water Distribution Monitoring to Optimize Water Quality
- Conference Proceeding by American Water Works Association, 11/01/2009
- Publisher: AWWA
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Distribution system water quality monitoring is still in its infancy, but there is an emerging realization of itspotential value. The initial emphasis has been on developing ways to detect deliberate or inadvertentchemical and biological attacks on water distribution systems. The potential for harm was made clear inthe case of the Milwaukee Cryptosporidiosis outbreak of 1993 (McGuire, 2006), in which thousands ofpeople became ill.Historically, water quality has been monitored on a limited basis to determine compliance with regulatorystandards such as periodic monitoring for chlorine residual and total coliform. Yet the need for morecomprehensive monitoring has been demonstrated by a growing body of research that indicates thatwater quality can potentially change between the water treatment plant (WTP) and the ultimate consumer(Baribeau et al, 2005; Zhang et al, 2002; LeChevallier, 1990). Therefore, in addition to alerting a utility ofa contamination event, a second potential application for distribution monitoring is to ensure that thewater received by the public has not degraded below acceptable standards.While examining databases from numerous well-operated utilities (Cook et al, 2008), the authorsdetermined that real-time distribution system data can provide early-warning of: nitrification inchloraminated water systems; elevated disinfection byproducts (DBP); explanations for turbiditychanges in the distribution system that are unrelated to distribution system operation; and, estimatingdetention times between the WTP and distal locations. The last finding, which is beyond this paper'sscope, could allow near-real-time hydraulic model calibration.This paper presents three cases in which distribution system monitoring data was used to detect earlywater quality degradation, to offer explanations as to why the degradation occurred, and to propose thatsuch monitoring, along with data analysis, could be used to enhance effective operational decision-making. Includes 16 references, figures.