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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Development of a process-based model to predict pathogen budgets for the Sydney drinking water catchment
Christobel M Ferguson1, Barry F W Croke, Peter J Beatson
1Ecowise Environmental Pty Ltd, 16A Lithgow St, Fyshwick, ACT 2609, Australia. cferguson@ecowise.com.au
Journal of Water and Health
|August 7, 2007
Summary
A new mathematical model predicts pathogen loads in drinking water catchments. This tool helps prioritize management strategies to reduce microbial risks from Cryptosporidium, Giardia, and E. coli in raw source water.
Area of Science:
- Environmental Science
- Water Quality Management
- Mathematical Modeling
Background:
- Pathogen reduction in drinking water catchments is crucial for raw source water quality.
- Effective management requires accurate prediction of microbial loads.
- Existing methods may not fully capture complex catchment dynamics.
Purpose of the Study:
- To develop a process-based mathematical model to predict pathogen loads (Cryptosporidium, Giardia, E. coli) in drinking water catchments.
- To provide a tool for evaluating management options and prioritizing control measures.
- To quantify microbial generation and transport from various sources.
Main Methods:
- Developed a process-based mathematical model named pathogen catchment budgets (PCB).
- Integrated land use, flow data, and catchment-specific information (e.g., sewage treatment plants).
- Applied the model to the Wingecarribee catchment to rank sub-catchment pathogen contributions under different weather conditions.
Main Results:
- The pathogen catchment budgets (PCB) model successfully predicts microbial loads.
- Identified sub-catchments with the highest pathogen contributions during dry and wet weather events.
- Sensitivity analysis highlighted pathogen excretion rates and manure mobilization as key factors.
Conclusions:
- The PCB model is a valuable tool for prioritizing pathogen control measures in drinking water catchments.
- Understanding pathogen excretion and manure dynamics is critical for effective risk management.
- The model aids in safeguarding raw source water quality against microbial contamination.
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