From Research to Operational Impact: Real-Time Monitoring Published in Clean Water
- Feb 23
- 3 min read
A new peer-reviewed publication in Clean Water (Nature Portfolio) evaluates automated near-real-time flow cytometry for monitoring microbiological dynamics at an alpine karst spring used for drinking water supply.
The study was led by researchers from TU Wien and the Medical University of Vienna and assessed automated on-site monitoring under real operational conditions.
Karst aquifers are a critical drinking water resource. Globally, around 10% of the population relies on karst systems, and in Austria nearly half of the population depends on alpine karst aquifers.
Yet these systems are highly dynamic.
As explained by the lead researcher, Dr. Lena Campostrini:
“After precipitation events, water and potential contaminants can move quickly through the system, making near-real-time monitoring essential for timely decision-making.”
Rapid transport through karst systems means that microbiological conditions can change within a short time frame. Detecting these changes reliably is therefore essential for effective water management.
Study Objective
The research team investigated whether automated, near-real-time flow cytometry can serve as a reliable on-site monitoring tool at a drinking water spring.
The monitoring strategy combined:
Long-term measurements to assess seasonal hydrological and contamination patterns
High-frequency monitoring during six precipitation events
Comparison of flow cytometry parameters with abiotic indicators such as turbidity and UV254
Microbiological reference parameters, including E. coli
Monitoring was conducted directly at the operational spring, reflecting real environmental variability.
Key Findings
During one of the precipitation events, the researchers observed a clear increase in total and intact microbial cell concentrations.
As described by Dr. Lena Campostrini
“We observed a clear increase in total and intact microbial cells that was not obvious or was delayed in abiotic parameters such as turbidity or UV254.”
Importantly, E. coli concentrations peaked at the same time as total and intact microbial cells.
This highlights the complementary value of automated microbial monitoring alongside traditional abiotic parameters.
The study further reports that when machine learning tools were applied for pollution forecasting, models including flow cytometry-derived parameters provided the highest predictive power.
Combining Long-Term and High-Frequency Monitoring
The research also demonstrated the importance of understanding the individual hydrological behavior of each karst system.
Low-frequency long-term monitoring revealed seasonal hydrological and contamination patterns. High-frequency monitoring provided insight into rapid microbial changes during contamination events.
According to Dr. Lena Campostrini:
“Combining long-term monitoring with targeted high-frequency campaigns helps optimize economic and temporal resources while still ensuring a thorough understanding of the karst system.”
Implications for Drinking Water Monitoring
At the investigated spring, the study concludes that automated flow cytometry can meaningfully complement existing monitoring approaches.
It can support:
More targeted sampling
Improved risk assessment
Better-informed decisions on spring water management
The technology evaluated in this study is implemented in the BactoSense system, which enables automated, on-site microbial monitoring based on flow cytometry principles.
Read the Full Publication
The full peer-reviewed study is available in Clean Water.
For utilities interested in exploring how automated microbial monitoring can support dynamic source management, contact the bNovate team to learn more.
Frequently Asked Questions
What is automated flow cytometry in drinking water monitoring?
Automated flow cytometry is a method that quantifies microbial cells in water samples. In this study, it was used on site at a drinking water spring to provide near-real-time data on total and intact microbial cell concentrations.
Why are alpine karst springs difficult to monitor?
Karst systems respond rapidly to precipitation events. Water and potential contaminants can move quickly through the aquifer, causing short-term changes in microbiological water quality. Detecting these changes requires monitoring approaches capable of capturing dynamic events.
How does near-real-time microbial monitoring differ from turbidity monitoring?
Turbidity measures particles in water, while UV254 measures organic matter. Flow cytometry directly quantifies microbial cells. The study showed that microbial cell increases were observed clearly, even when turbidity or UV254 responses were delayed or less pronounced.
What did the study show about predictive monitoring?
When machine learning tools were applied for pollution forecasting, models that included flow cytometry-derived parameters demonstrated the highest predictive power compared to models based solely on conventional monitoring data.
What is BactoSense?
BactoSense is an automated on-site monitoring system based on flow cytometry principles. It enables near-real-time quantification of microbial cells in water and was the technology platform evaluated in this study.