Optimal distribution of green and grey infrastructures coupled with real time control of the sewer for combined sewer overflows control as an adaptation measure to climate change

ABSTRACT

Optimization of the spatial distribution of green infrastructures (GIs) was performed for a combined sewer system located in the Province of Quebec, Canada, using a simulation-optimization tool with the aim of reducing seasonal combined sewer overflows (CSOs). The performance of four CSOs control alternatives involving the individual and integrated implementation of GIs with storage tanks and real time control (RTC) of the sewer was evaluated for a nine-year simulation period of historical rainfall data and for 20%-increased rainfall data (representative of potential climate change impact). The integration of GIs with RTC of the sewer (with or without storage tanks) lowered the total CSO volume by 95% to 99% under historical rainfall data and by 93% to 96% under increased rainfall intensities when compared to the reference scenario. Adapting GI’s number and location for optimal CSO control rather than according to space availability criteria reduced CSO frequency but had only a slight impact on CSO volume reduction.

KEYWORDS:

• Genetic algorithm
• rule-based control
• source control measure
• sustainable urban drainage systems
• low impact development
• nature-based solutions

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available on request from the corresponding author, S. Duchesne. The data are not publicly available due to a confidentiality agreement with the city where the case study sewer is located.

Supplementary material

Supplemental data for this article can be accessed https://doi.org/10.1080/1573062X.2024.2312497

Additional information

Funding

This research was funded by Tetra Tech [Grant RDCPJ 487284-15 and Grant ALLRP 544594-19] from the Natural Sciences and Engineering Research Council of Canada. Graduate studies of M.-È. Jean were supported by the Vanier Canada Graduate Scholarship from the Government of Canada. The authors acknowledge the expertise and support of Jamie M. Brescol, Karine Bilodeau, Christiane Marcoux, and Leni Trudel, at Tetra Tech CSO, and of Véronique Guay, from INRS-ETE, as well as the chief of Engineering and Environment of the municipality selected as the research case study. The authors are also grateful for the PCSWMM software license provided by Computational Hydraulics Inc.