Towards the automation of water quality monitoring networks

Copp, John B.; Belia, Evangelina; Hübner, Christian; Thron, Mario; Vanrolleghem, Peter; Rieger, Leiv

doi:10.1109/coase.2010.5584638

Cited by 5 publications

(1 citation statement)

References 3 publications

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“…The second approach, confidence value, is part of the DIMS.CORE RTC system of DHI (Ingeduld , 2007). Finally, the third approach -time series analysis -has been implemented as part of the Primodal Systems RSM30 PrecisionNow software (Copp et al, 2010). Implementation of those tools in practical scenarios allows operators and process engineers following the status of current and past measurements and the detection of doubtful data and potential sensors faults.…”

Section: Case Studymentioning

confidence: 99%

Validating data quality during wet weather monitoring of wastewater treatment plant influents

Alferes¹,

Lynggaard-Jensen²,

Munk-Nielsen³

et al. 2013

proc water environ fed

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Efficient monitoring of water systems and proper use of the collected data in further applications such as modelling, forecasting influent water quality and real-time control depends on careful data quality control. Given the size of the data sets produced nowadays in online water quality monitoring schemes, automated data validation is the only feasible option. In this paper, software tools for automatic data quality assessment with a practical orientation are presented. The developments from three organizations ranging from simple to more complex methods for automated data validation are described and evaluated for water quality measurements collected at the inlet of wastewater treatment plants, where probably the hardest measurement conditions are found. The objective of this collaborative effort is to come up with better tools and improved approaches for implementing a successful automatic data quality control procedure.

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Section: Case Studymentioning

confidence: 99%