Enhancing Site-Scale Stormwater Management Through Real-Time Adapter Control System

Meng, Xuli

Enhancing Site-Scale Stormwater Management Through Real-Time Adapter Control System

Meng, Xuli

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Publication Type:: Thesis
Issue Date:: 2025

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Field	Value	Language
dc.contributor.author	Meng, Xuli
dc.date.accessioned	2025-10-10T02:18:34Z
dc.date.available	2025-10-10T02:18:34Z
dc.date.issued	2025
dc.identifier.uri	http://hdl.handle.net/10453/190366
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	Urbanization, driven by population growth and rural-to-urban migration, has dramatically altered land use patterns, transforming natural landscapes into impervious surfaces such as roofs, roads, and parking lots. This shift has led to increased stormwater runoff, causing flooding, water quality degradation, and disturbances to aquatic ecosystems. A critical challenge in urban water management is overland flow flooding, where stormwater moves across surfaces before entering natural watercourses or underground systems. This localized flooding presents risks that traditional flood management strategies cannot adequately address. Additionally, the rising demand for potable water further stresses existing resources, underscoring the need for innovative solutions in stormwater management and water conservation. This PhD thesis explores the application of Real-Time Adaptive Control (RTAC) systems for site-scale stormwater management, incorporating advanced technologies such as cloud computing, Wi-Fi connectivity, and control units. The enhanced RTAC model allows real-time stormwater runoff analysis, optimizing storage and release mechanisms in stormwater harvesting facilities. This approach reduces the load on urban drainage networks, mitigates flooding, and protects infrastructure. The effectiveness of the RTAC system is demonstrated through its use in stormwater harvesting tanks within urban catchments, where it enhances storage efficiency during rainfall and ensures controlled release to urban waterways, reducing flooding risks. Prior to implementing the RTAC system in water-sensitive frameworks, this thesis compares a combined Water Sensitive Urban Design (WSUD) model with conventional WSUD models to evaluate their runoff management performance. Projections for 2000–2030 show an increase in impervious surfaces from 74.34% to 83.84%, leading to an additional 1,340 ML/yr of stormwater runoff. Both WSUD models reduce runoff and improve infiltration, with the combined WSUD model showing 20-30% better performance across various rainfall scenarios. The thesis also introduces the Site-Scale Real-Time Adaptive Control (SRAC) model for managing overland flow flooding. The SRAC model dynamically manages runoff by preemptively discharging water before storms, creating storage capacity, and releasing water post-storm. A case study demonstrates that the SRAC model reduced flooding volumes by over 98% during severe storms and decreased drainage system demand by 43%, potentially saving AU$7.87 million in infrastructure costs. The SRAC-WSUD method also outperforms conventional WSUD in pollutant removal, significantly reducing Total Suspended Solids, Total Phosphorus, and Total Nitrogen across different rainfall scenarios. While there was no significant difference in Gross Pollutant removal, the SRAC-WSUD method improved pollutant management and flow control. Future research should focus on optimizing water storage and addressing water quality concerns in stormwater harvesting systems.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/190366/3/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2025 Xuli Meng
dc.rights	au.edu.uts.lib/cph
dc.title	Enhancing Site-Scale Stormwater Management Through Real-Time Adapter Control System	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

Urbanization, driven by population growth and rural-to-urban migration, has dramatically altered land use patterns, transforming natural landscapes into impervious surfaces such as roofs, roads, and parking lots. This shift has led to increased stormwater runoff, causing flooding, water quality degradation, and disturbances to aquatic ecosystems. A critical challenge in urban water management is overland flow flooding, where stormwater moves across surfaces before entering natural watercourses or underground systems. This localized flooding presents risks that traditional flood management strategies cannot adequately address. Additionally, the rising demand for potable water further stresses existing resources, underscoring the need for innovative solutions in stormwater management and water conservation. This PhD thesis explores the application of Real-Time Adaptive Control (RTAC) systems for site-scale stormwater management, incorporating advanced technologies such as cloud computing, Wi-Fi connectivity, and control units. The enhanced RTAC model allows real-time stormwater runoff analysis, optimizing storage and release mechanisms in stormwater harvesting facilities. This approach reduces the load on urban drainage networks, mitigates flooding, and protects infrastructure. The effectiveness of the RTAC system is demonstrated through its use in stormwater harvesting tanks within urban catchments, where it enhances storage efficiency during rainfall and ensures controlled release to urban waterways, reducing flooding risks. Prior to implementing the RTAC system in water-sensitive frameworks, this thesis compares a combined Water Sensitive Urban Design (WSUD) model with conventional WSUD models to evaluate their runoff management performance. Projections for 2000–2030 show an increase in impervious surfaces from 74.34% to 83.84%, leading to an additional 1,340 ML/yr of stormwater runoff. Both WSUD models reduce runoff and improve infiltration, with the combined WSUD model showing 20-30% better performance across various rainfall scenarios. The thesis also introduces the Site-Scale Real-Time Adaptive Control (SRAC) model for managing overland flow flooding. The SRAC model dynamically manages runoff by preemptively discharging water before storms, creating storage capacity, and releasing water post-storm. A case study demonstrates that the SRAC model reduced flooding volumes by over 98% during severe storms and decreased drainage system demand by 43%, potentially saving AU$7.87 million in infrastructure costs. The SRAC-WSUD method also outperforms conventional WSUD in pollutant removal, significantly reducing Total Suspended Solids, Total Phosphorus, and Total Nitrogen across different rainfall scenarios. While there was no significant difference in Gross Pollutant removal, the SRAC-WSUD method improved pollutant management and flow control. Future research should focus on optimizing water storage and addressing water quality concerns in stormwater harvesting systems.

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http://hdl.handle.net/10453/190366