Journal of Water and Health Vol 5 No 2 pp 187–208 © IWA Publishing 2007 doi:10.2166/wh.2007.013
Development of a process-based model to predict pathogen budgets for the Sydney drinking water catchment
Christobel M. Ferguson, Barry F. W. Croke, Peter J. Beatson, Nicholas J. Ashbolt and Daniel A. Deere
Ecowise Environmental Pty Ltd, 16A Lithgow StFyshwick, ACT 2609, Australia cferguson@ecowise.com.au
Integrated Catchment Assessment and Management Centre, Australian National University, Canberra, ACT 0200, Australia
PO Box 3003Marrickville, NSW 2204, Australia
Centre for Water and Waste Technology, School of Civil and Environmental Engineering, UNSWSydney, 2052, Australia
Cooperative Research Centre for Water Quality and Treatment, Private Mailbag 3Salisbury, SA 5108, Australia
ABSTRACT
In drinking water catchments, reduction of pathogen loads delivered to reservoirs is an important priority for the management of raw source water quality. To assist with the evaluation of management options, a process-based mathematical model (pathogen catchment budgets - PCB) is developed to predict Cryptosporidium, Giardia and E. coli loads generated within and exported from drinking water catchments. The model quantifies the key processes affecting the generation and transport of microorganisms from humans and animals using land use and flow data, and catchment specific information including point sources such as sewage treatment plants and on-site systems. The resultant pathogen catchment budgets (PCB) can be used to prioritize the implementation of control measures for the reduction of pathogen risks to drinking water. The model is applied in the Wingecarribee catchment and used to rank those sub-catchments that would contribute the highest pathogen loads in dry weather, and in intermediate and large wet weather events. A sensitivity analysis of the model identifies that pathogen excretion rates from animals and humans, and manure mobilization rates are significant factors determining the output of the model and thus warrant further investigation.
Keywords: catchment; Cryptosporidium; model; pathogen; watershed
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