A benchmarking framework for control and optimization of smart stormwater networks

Rimer, Sara P.; Mullapudi, Abhiram; Troutman, Sara C.; Kerkez, Branko

doi:10.1145/3302509.3313336

Cited by 8 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Within the past few years, several research groups have presented surrogate modelling studies on each their case areas and using their own specific case data, which makes it impossible to compare the methods directly (Kroll et al, 2017;Ledergerber et al, 2019;Mahmoodian et al, 2018;Thrysøe et al, 2019;Wolfs and Willems, 2017). Within the research field of Real Time Control (RTC) of urban drainage systems, the lack of open data sets has led to the development of synthetic test 50 models, such as the Astlingen network (Schütze et al, 2017;Sun et al, 2020) and the Pystorms networks (Rimer et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The Bellinge data set: open data and models for community-wide urban drainage systems research

Pedersen¹,

Pedersen²,

Vigueras-Rodríguez³

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. This paper describes a comprehensive and unique open-access data set for research within hydrological and hydraulic modelling of urban drainage systems. The data comes from a mainly combined urban drainage system covering a 1.7 km2 area in the town of Bellinge, a suburb to the city of Odense, Denmark. The data set consists of up to 10 years of observations (2010–2020) from 13 level meters, one flow meter, one position-sensor and four power sensors in the system, along with rainfall data from three rain gauges and two weather radars (X- and C-band), and meteorological data from a nearby weather station. The system characteristics of the urban drainage system (information about manholes, pipes etc.) can be found in the data set along with characteristics of the surface area (contour lines etc.). Two detailed hydrodynamic, distributed urban drainage models of the system are provided in the software systems Mike Urban and EPA SWMM. The two simulation models generally show similar responses, but systematic differences are present since the models have not been calibrated. With this data set we provide a useful case that enables independent testing and replication of results from future scientific developments and innovation within urban hydrology and urban drainage system research. The data set can be downloaded from https://doi.org/10.11583/DTU.c.5029124, (Pedersen et al., 2021a).

show abstract

Section: Introductionmentioning

confidence: 99%

The Bellinge data set: open data and models for community-wide urban drainage systems research

Pedersen¹,

Pedersen²,

Vigueras-Rodríguez³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…In the past few years, several research groups have presented surrogate modelling studies on each of their case areas using their own specific case data, which makes it impossible to compare the methods directly (Kroll et al, 2017;Ledergerber et al, 2019;Mahmoodian et al, 2018;Thrysøe et al, 2019;Wolfs and Willems, 2017). Within the research field of real-time control (RTC) of urban drainage systems, the lack of open data sets has led to the development of synthetic test models, such as the Astlingen network (Schütze et al, 2017;Sun et al, 2020) and the Pystorms networks (Rimer et al, 2019). While such synthetic networks are useful due to their stringent focus on the most relevant processes for the purpose at hand, the usage of actual networks to benchmark the performance of RTC methods would help the end-users in the utility companies to decide which methods to implement for their specific system.…”

Section: Introductionmentioning

confidence: 99%

The Bellinge data set: open data and models for community-wide urban drainage systems research

Pedersen¹,

Pedersen²,

Vigueras-Rodríguez

et al. 2021

Earth Syst. Sci. Data

View full text Add to dashboard Cite

Abstract. This paper describes a comprehensive and unique open-access data set for research within hydrological and hydraulic modelling of urban drainage systems. The data come from a mainly combined urban drainage system covering a 1.7 km2 area in the town of Bellinge, a suburb of the city of Odense, Denmark. The data set consists of up to 10 years of observations (2010–2020) from 13 level meters, 1 flow meter, 1 position sensor and 4 power sensors in the system, along with rainfall data from three rain gauges and two weather radars (X- and C-band), and meteorological data from a nearby weather station. The system characteristics of the urban drainage system (information about manholes, pipes, etc.) can be found in the data set along with characteristics of the surface area (contour lines, surface description, etc.). Two detailed hydrodynamic, distributed urban drainage models of the system are provided in the software systems MIKE URBAN and EPA Storm Water Management Model (SWMM). The two simulation models generally show similar responses, but systematic differences are present since the models have not been calibrated. With this data set we provide a useful case that will enable independent testing and replication of results from future scientific developments and innovation within urban hydrology and urban drainage systems research. The data set can be downloaded from https://doi.org/10.11583/DTU.c.5029124 (Pedersen et al., 2021a).

show abstract

“…The need to reduce downstream flooding, improve system water quality, and avoid local overflow in the case study are reasons for exploring benefits of RTC. The stormwater drainage system of the case study has been benchmarked as the 'gamma' SWMM model of the open source pystorms package (Rimer et al, 2019). The pystorms package is a benchmarking framework to make smart stormwater network control problems accessible to control experts and promote the growth of a broader community with the easy cross-comparison of control strategy performances.…”

Section: Overview Of the Case Studymentioning

confidence: 99%

Modeling Operations in System-level Real-time Control for Urban Flooding Reduction and Water Quality Improvement -An Open-source Benchmarked Case

Burian

Oroza

et al. 2023

Preprint

View full text Add to dashboard Cite

Increases in the integrated application of smart sensing and control technologies enable urban drainage engineers to retrofit stormwater storage facilities with controllers actuating valves and gates to address flooding and water quality problems across the entire watershed. This objective becomes increasingly challenging because simultaneously controlling the spatially distributed storage assets to solve the stormwater issue at downstream outlet sites does not necessarily alleviate overflow at upstream storage ponds. To that end, this study presents a system-level real-time control simulation for assessing the performance of controllers in the trade-off between flooding mitigation at downstream outlets and water quality improvements at the upstream storage units like the detention pond. Using a benchmarked urban stormwater drainage model located in the southeast of Michigan, USA, with watershed-scale flooding and water quality challenges, we investigated the temporal changes in water depth, flow, and total suspended solids under different real-time control strategies, including one individual control operated only at the most downstream outlet site and two system-level controls operated at all storage detention sites. Modeling results show that the system-level control reduces peak water depth, shortens flooding duration, and removes pollutant load, by up to 7.3%, 34%, and 65%, respectively. However, system-level control does not always perform better than the individual control strategy, especially in addressing flooding duration in the most downstream outlet. This modeling work advances real-time control understanding for building adaptive stormwater management solution against water quantity and quality issues.

show abstract

A benchmarking framework for control and optimization of smart stormwater networks

Cited by 8 publications

References 10 publications

The Bellinge data set: open data and models for community-wide urban drainage systems research

The Bellinge data set: open data and models for community-wide urban drainage systems research

The Bellinge data set: open data and models for community-wide urban drainage systems research

Modeling Operations in System-level Real-time Control for Urban Flooding Reduction and Water Quality Improvement -An Open-source Benchmarked Case

Contact Info

Product

Resources

About