Probabilistic fecal pollution source profiling and microbial source tracking for an urban river catchment.

Area of Science:

• Environmental Science
• Microbiology
• Water Quality Management

Background:

• Urban river catchments face complex fecal pollution challenges from various sources.
• Accurate identification of fecal pollution sources is crucial for effective water safety management.
• Existing methods may lack the precision to differentiate between multiple contributing sources.

Purpose of the Study:

• To develop and validate an innovative approach for estimating the occurrence and extent of fecal pollution sources in urban river catchments.
• To differentiate between human and animal fecal contributions to river contamination.
• To establish statistical relationships between microbial indicators, tracers, and pathogens.

Main Methods:

• Probabilistic estimation of daily fecal indicator bacteria (FIBs) and pathogen excretion from human and animal sources.
• Source-targeted monitoring design based on initial hypotheses.
• Verification using chemical tracers, Clostridium perfringens spores, and host-associated genetic microbial source tracking (MST) markers.
• Multi-parametric correlation analysis.

Main Results:

• Treated wastewater (WWTP) identified as the primary source of fecal pollution during dry weather.
• Combined sewer overflows (CSOs) estimated to contribute 80-99% of FIBs and pathogens during wet weather.
• Human genetic markers were significantly higher than animal markers; statistical links found between C. perfringens spores, human MST markers, and Giardia.

Conclusions:

• The developed approach effectively estimates fecal pollution sources in urban catchments.
• It provides a robust basis for water safety management, microbial fate modeling, and infection risk assessment.
• This methodology enhances understanding of microbial contamination dynamics in urban rivers.