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  • Developing best practice guidelines for lake modelling to inform quantitative microbial risk assessment

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    Embargoed until: 2024-01-28
    File version
    Accepted Manuscript (AM)
    Author(s)
    Yu, Songyan
    Sturm, Katrin
    Gibbes, Badin
    Kennard, Mark J
    Veal, Cameron
    Middleton, Duncan
    Fisher, Paul
    Rotherham, Simon
    Hamilton, David P
    Griffith University Author(s)
    Yu, Sunny
    Kennard, Mark J.
    Hamilton, David P.
    Year published
    2022
    Metadata
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    Abstract
    Numerical models of lakes and reservoirs have been widely applied to provide quantitative forecasts of pathogen occurrence and persistence in source water to inform quantitative microbial risk assessment (QMRA). There is an emerging need in the water supply industry for a set of best practice modelling guidelines, supporting consistent and repeatable use of lake modelling approaches that could be used to provide quality assurance to water authorities and regulators. To aid in the development of these guidelines, we conducted a literature review to summarise common modelling steps from existing water modelling guidelines as ...
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    Numerical models of lakes and reservoirs have been widely applied to provide quantitative forecasts of pathogen occurrence and persistence in source water to inform quantitative microbial risk assessment (QMRA). There is an emerging need in the water supply industry for a set of best practice modelling guidelines, supporting consistent and repeatable use of lake modelling approaches that could be used to provide quality assurance to water authorities and regulators. To aid in the development of these guidelines, we conducted a literature review to summarise common modelling steps from existing water modelling guidelines as the basis for best practice guidelines for lake modelling. We also report on the results of a workshop, expert interviews, and online surveys that identify common challenges and requirements for each step. The summarised lake modelling steps and key requirements pave the way to complete the development of best practice guidelines for lake modelling to inform QMRA.
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    Journal Title
    Environmental Modelling & Software
    Volume
    150
    DOI
    https://doi.org/10.1016/j.envsoft.2022.105334
    Copyright Statement
    © 2022 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Subject
    Environmental management
    Publication URI
    http://hdl.handle.net/10072/412114
    Collection
    • Journal articles

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