Evaluating flow cytometric metrics for enhancing microbial monitoring in drinking water treatment processes

Flow cytometry (FCM) offers a rapid method for bacterial detection in drinking water but faces challenges in terms of data analysis, particularly gating subjectivity. This study evaluates three metrics derived from the Intact Cell Count (ICC): High/Low Nucleic Acid (HNA/LNA) ratios, Bray–Curtis Dissimilarity Index (BCDI), and FCM fingerprints—to enhance microbial monitoring approaches across different water treatment and distribution stages. ICC provided a direct assessment of microbial load in high cell count scenarios, while HNA/LNA ratios were valuable during low microbial levels. BCDI effectively tracked microbial population changes throughout treatment processes. A lead–lag analysis revealed that ICC changes often precede or coincide with BCDI changes and lead changes in HNA/LNA ratios. FCM fingerprinting visualized spatial and temporal variations in microbial communities. Combining these FCM metrics improved microbial water quality assessment and supports approaches to optimise water treatment strategies from a microbial perspective. • 3 parameters of ICC compared: HNA/LNA, BCDI, and fingerprints to detect microbial dynamics. • HNA/LNA favourable in low cell count loading scenarios after oxidative treatments. • BCDI tracks microbial community changes well across treatment stages. • ICC changes occurred prior to other metrics (BCDI HNA/LNA) suggesting FCM tracks microbial population changes. • Combination of FCM metrics offers a practical framework for water quality professionals.