MUSIC model accuracy in predicting stormwater quality

Fletcher, Wade Daniel (2013) MUSIC model accuracy in predicting stormwater quality. [USQ Project]


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This dissertation investigates the use of stormwater treatment devices for urban catchments within Australia. The primary goal of the dissertation is to assess the
accuracy of MUSIC modelling of stormwater pollutant generation and pollutant reduction to assess the effectiveness of the devices it is used to design.

A bio-filtration and detention basin with a moderately sized urban catchment was selected as the test site. The inlet into the existing basin was sampled over 6 months,
during several storms, with flow depths measured and water samples taken at 6 minute intervals. These water samples were then analysed at a local laboratory and the results
compared to the MUSIC model that was set up to replicate the basin catchment. These samples and discharges were then compared against the results of a MUSIC model of
the site catchment. A pollutant trap was constructed at the basin inlet to collect gross pollutants to check the accuracy of the gross pollutants generation within MUSIC.

Given the limitations in time and funding it was not possible to provide a definitive answer as to the accuracy of flow, pollutant generation and pollutant reduction
predictions by MUSIC. The level of modelled gross pollutants was reasonably accurate in relation to the volumes that were collected on site. On average the mass of the gross pollutants were 35% less than what was predicted by the MUSIC model but this was to be expected as not all the sediment or organics were captured.

Sampled inflow TSS and TP pollutant levels were generally below the modelled values. Inflow TN values were the least accurate of all the pollutants especially after periods of
prolonged rain where the modelled TN concentrations were well above what was sampled. On average sampled TN and TP inflow concentrations were 61% and 48% lower
respectively than the modelled concentrations. The average sampled concentration of inflow TSS was 56% lower than the corresponding concentration modelled by MUSIC. It should be noted that the storm events that were sampled were smaller than an average storm. Previous research also found that there was a tendency by the MUSIC software to overestimate the pollutant concentrations for smaller storms.

It should also be kept in mind that due to finding and time constraints the sampling in this project assesses the instantaneous concentration not the annual loads. Therefore
there is a greater margin for error. In order to determine the accuracy of annual loads of pollutant generation and pollutant reduction it is recommended that more detailed
research is undertaken over an extended period.

The setup of the bio-filtration basin was not considered to be adequate enough to provide for an accurate assessment of the modelled pollutant reduction. Results of the sampled outflow show a minimal reduction in pollutants and the condition of the samples basin should be kept in mind.

By better understanding the accuracy of stormwater pollutant modelling and variations due to a range of factors it is hoped that better design methodology and design guidelines can be adopted for the treatment of stormwater pollutants. This will hopefully benefit councils, engineers and developers as well as the community and environment by providing a cleaner and more sustainable water supply for centuries to come.

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Item Type: USQ Project
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021)
Supervisors: Brodie, Ian
Date Deposited: 05 Mar 2014 20:16
Last Modified: 06 Mar 2014 01:56
Uncontrolled Keywords: music model accuracy; stormwater quality; urban catchments; water quality
Fields of Research (2008): 09 Engineering > 0905 Civil Engineering > 090508 Water Quality Engineering
Fields of Research (2020): 40 ENGINEERING > 4004 Chemical engineering > 400499 Chemical engineering not elsewhere classified
Socio-Economic Objectives (2008): D Environment > 96 Environment > 9606 Environmental and Natural Resource Evaluation > 960611 Urban Water Evaluation (incl. Water Quality)

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