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SCADA data and the quantification of hazardous events for QMRA
Author(s) -
Peter M. Nilsson,
David J. Roser,
Rebecka Thorwaldsdotter,
Susan Petterson,
Carwyn Davies,
R. S. Signor,
Olof Bergstedt,
Nicholas J. Ashbolt
Publication year - 2007
Publication title -
journal of water and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 59
eISSN - 1996-7829
pISSN - 1477-8920
DOI - 10.2166/wh.2007.138
Subject(s) - scada , hazardous waste , cusum , event (particle physics) , statistics , data mining , residual , environmental science , computer science , real time computing , engineering , mathematics , waste management , physics , algorithm , quantum mechanics , electrical engineering
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.

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