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  • An autonomous decision support system for manganese forecasting in subtropical water reservoirs

    Author(s)
    Bertone, Edoardo
    Stewart, Rodney A
    Zhang, Hong
    Bartkow, Michael
    Hacker, Charles
    Griffith University Author(s)
    Hacker, Charles
    Stewart, Rodney A.
    Zhang, Hong
    Bertone, Edoardo
    Bartkow, Michael E.
    Year published
    2015
    Metadata
    Show full item record
    Abstract
    Manganese monitoring and removal is essential for water utilities in order to avoid supplying discoloured water to consumers. Traditional manganese monitoring in water reservoirs consists of costly and time-consuming manual lake samplings and laboratory analysis. However, vertical profiling systems can automatically collect and remotely transfer a range of physical parameters that affect the manganese cycle. In this study, a manganese prediction model was developed, based on the profiler's historical data and weather forecasts. The model effectively forecasted seven-day ahead manganese concentrations in the epilimnion of ...
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    Manganese monitoring and removal is essential for water utilities in order to avoid supplying discoloured water to consumers. Traditional manganese monitoring in water reservoirs consists of costly and time-consuming manual lake samplings and laboratory analysis. However, vertical profiling systems can automatically collect and remotely transfer a range of physical parameters that affect the manganese cycle. In this study, a manganese prediction model was developed, based on the profiler's historical data and weather forecasts. The model effectively forecasted seven-day ahead manganese concentrations in the epilimnion of Advancetown Lake (Queensland, Australia). The manganese forecasting model was then operationalised into an automatically updated decision support system with a user-friendly graphical interface that is easily accessible and interpretable by water treatment plant operators. The developed tool resulted in a reduction in traditional expensive monitoring while ensuring proactive water treatment management.
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    Journal Title
    Environmental Modelling & Software
    Volume
    73
    DOI
    https://doi.org/10.1016/j.envsoft.2015.08.008
    Subject
    Water Resources Engineering
    Publication URI
    http://hdl.handle.net/10072/98556
    Collection
    • Journal articles

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