BioRTC model enables exploration of real time control strategies for stormwater biofilters

Shen, Pengfei, , Bratieres, Katia, & (2023) BioRTC model enables exploration of real time control strategies for stormwater biofilters. Water Research, 247, Article number: 120793.

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Description

Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a ‘base’ model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (Ec) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively.

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ID Code: 245095
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Deletic, Anaorcid.org/0000-0002-3535-7451
McCarthy, David T.orcid.org/0000-0001-8845-6501
Additional Information: Acknowledgement: The authors would like to thank Melbourne Water for generously sharing the data of the Hawthorn Main Drain West Catchment. The support of the EPHM lab team in Monash University for experiment implementation is gratefully acknowledged. This work was supported by the Australian Research Council [Linkage Project Number LP160100408].
Measurements or Duration: 12 pages
Keywords: E. coli, Microbes, Modelling, Real time control, Stormwater biofilters, Stormwater harvesting
DOI: 10.1016/j.watres.2023.120793
ISSN: 0043-1354
Pure ID: 152122942
Divisions: Current > QUT Faculties and Divisions > Faculty of Engineering
Current > Schools > School of Civil & Environmental Engineering
Funding Information: The authors would like to thank Melbourne Water for generously sharing the data of the Hawthorn Main Drain West Catchment. The support of the EPHM lab team in Monash University for experiment implementation is gratefully acknowledged. This work was supported by the Australian Research Council [Linkage Project Number LP160100408]. The authors would like to thank Melbourne Water for generously sharing the data of the Hawthorn Main Drain West Catchment. The support of the EPHM lab team in Monash University for experiment implementation is gratefully acknowledged. This work was supported by the Australian Research Council [Linkage Project Number LP160100408 ].
Copyright Owner: 2023 Elsevier Ltd.
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Deposited On: 12 Dec 2023 00:53
Last Modified: 29 Feb 2024 14:07