Journal of Water and Health Vol 5 No Suppl 1 pp S99–S105 © IWA Publishing 2007 doi:10.2166/wh.2007.138
SCADA data and the quantification of hazardous events for QMRA
P. Nilsson, R. Thorwaldsdotter, D. Roser, S. Petterson, C. Davies, R. Signor, N. Ashbolt and O. Bergstedt
Division of Ergonomics and Aerosol Technology, Department of Design Sciences, Faculty of Engineering, Lund University, PO Box 118, SE-221 00, Lund, Sweden
School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia Tel.: +61 2 9385 5137; Fax: +61 2 9313 8624; djroser@civeng.unsw.edu.au
Göteborg Vatten Projekteringsavdelningen, PO Box 123, SE-424 23, Angered, Sweden
ABSTRACT
The objective of this study was to assess the use of on-line monitoring to support the QMRA at water treatment plants studied in the EU MicroRisk project. SCADA data were obtained from three Catchment-to-Tap Systems (CTS) along with system descriptions, diary records, grab sample data and deviation reports. Particular attention was paid to estimating hazardous event frequency, duration and magnitude. Using Shewart and CUSUM we identified ‘change-points’ corresponding to events of between 10 min and > 1 month duration in timeseries data. Our analysis confirmed it is possible to quantify hazardous event durations from turbidity, chlorine residual and pH records and distinguish them from non-hazardous variability in the timeseries dataset. The durations of most ‘events’ were short-term (0.5–2.3 h). These data were combined with QMRA to estimate pathogen infection risk arising from such events as chlorination failure. While analysis of SCADA data alone could identify events provisionally, its interpretation was severely constrained in the absence of diary records and other system information. SCADA data analysis should only complement traditional water sampling, rather than replace it. More work on on-line data management, quality control and interpretation is needed before it can be used routinely for event characterization.
Keywords: hazardous events; QMRA; quality control; SCADA; timeseries
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