Online characterization of bacterial processes in drinking water systems

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


The use of traditional drinking water microbial quality monitoring methods, including heterotrophic plate counts (HPCs) and total coliform counts, are not only laborious and time-consuming but also do not readily allow identification of risk areas in the network. Furthermore, if areas of concern are identified, and mitigation measures are taken, it takes days before the effectiveness of these measures is known. This study identified flow cytometry (FCM) as an online sensor technology for bacterial water quality monitoring in the distribution network. We monitored the total bacterial cell numbers and biodiversity in a drinking water distribution system (DWDS) using an online FCM. Two parallel online FCM monitoring systems were installed on two different locations at a drinking water treatment plant (DWTP; Saudi Arabia) supplying chlorinated water to the distribution and in the network 3.6 km away from the DWTP. The FCMs were operated at the same time in parallel to assess the biological stability in DWDSs. The flow cytometric data was compared with the conventional water quality detection methods (HPC and total coliforms). HPC and total coliforms were constantly below the detection limits, while the FCM provided detectable total cell count data and enabled the quantification of changes in the drinking water both with time and during distribution. Results demonstrate the value of FCM as a tool for compliance monitoring and risk assessment of DWDSs.
Original languageEnglish (US)
Journalnpj Clean Water
Issue number1
StatePublished - Mar 27 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST).


Dive into the research topics of 'Online characterization of bacterial processes in drinking water systems'. Together they form a unique fingerprint.

Cite this