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https://hdl.handle.net/2440/75849
Type: | Conference item |
Title: | Simulation tools for minimizing pathogen risk in drinking water reservoirs |
Author: | Hipsey, M. Antenucci, J. Brookes, J. Burch, M. Regel, R. |
Citation: | Proceedings of the 6th International Conference on Hydroinformatics, held in Singapore 21-24 June, 2004 / S.-Y. Liong, K.-K. Phoon and V. Babovic (eds.): pp.415-423 |
Publisher: | World Scientific Publishing |
Issue Date: | 2004 |
ISBN: | 9812387870 |
Conference Name: | International Conference on Hydroinformatics (6th : 2004 : Singapore) |
Statement of Responsibility: | Matthew R. Hipsey, Jason P. Antenucci, Justin D. Brookes, Mike D. Burch and Rudi H. Regel |
Abstract: | Contamination of water supplies intended for human consumption by pathogenic microorganisms is a concern for water managers in developed and developing countries alike. Typically, pathogens are associated with disturbed landscapes such as those used for human settlements or agricultural practices, and they progress from the catchment to the river or stream during periods of significant rainfall. Ultimately, they reach drinking water reservoirs and are potentially distributed to consumers. There is therefore a need for tools that can be applied to assess pathogen fate and transport as they move through a reservoir. This paper documents the development of a suite of freely available tools that range in complexity from a simple web-based intrusion model (INFLOW), to a onedimensional hydrodynamic and pathogen model (DYRESM-CAEDYM), to a full three dimensional model of hydrodynamics and pathogen fate and transport (ELCOMCAEDYM). Results from the models are presented and assessed against data collected during a comprehensive field campaign in Australia that tracked pathogen concentrations throughout two reservoirs subjected to inflow forcing from rivers with high pathogen loads. All three models proved themselves as useful tools for investigating pathogen dynamics and are able to estimate dilution rates and timescales for risk reduction through inactivation and settling. The information provided by the models can be used to recommend a simple monitoring program and adaptive risk management strategies. The benefits and limitations of each of the models are also discussed. |
Rights: | © 2004 World Scientific Publishing Company |
Description (link): | http://www.cwr.uwa.edu.au/research/publications.php?rec=2020 |
Appears in Collections: | Aurora harvest 4 Earth and Environmental Sciences publications Environment Institute Leaders publications |
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