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1. Stormwater impact on water quality of rivers subjected to point sources and urbanization - the case of Addis Ababa, Ethiopia: Stormwater impact on water quality of rivers

   https://doi.org/10.1111/wej.12381  

   Adugna, Dagnachew ; Lemma, Brook ; Sahilu Gebrie, Geremew ; Larsen, Larissa ; Yeshitela, Kumelachew ; Bergen Jensen, Marina ( February 2019 , Water and Environment Journal)
2. Ecosystem services and U.S. stormwater planning: An approach for improving urban stormwater decisions

   https://doi.org/10.1016/j.envsci.2018.06.006  

   BenDor, Todd K. ; Shandas, Vivek ; Miles, Brian ; Belt, Kenneth ; Olander, Lydia ( October 2018 , Environmental Science & Policy)
3. Reachability Analysis as a Design Tool for Stormwater Systems

   https://doi.org/10.1109/sustech.2018.8671362  

   Chapman, Margaret P. ; Smith, Kevin M. ; Cheng, Victoria ; Freyberg, David L. ; Tomlin, Claire J. ( November 2018 , 2018 IEEE Conference on Technologies for Sustainability (SusTech))

   Effective stormwater management requires systems that operate safely and deliver improved environmental outcomes in a cost-effective manner. However, current design practices typically evaluate performance assuming that a given system starts empty and operates independently from nearby stormwater infrastructure. There is a conspicuous need for more realistic design-phase indicators of performance that consider a larger set of initial conditions and the effects of coupled dynamics. To this end, we apply a control-theoretic method, called reachability analysis, to produce a more objective measure of system robustness. We seek two primary contributions in this work. First, we demonstrate how the application of reachability analysis to a dynamic model of a stormwater network can characterize the set of initial conditions from which every element in the network can avoid overflowing under a given surface runoff signal of finite duration. This is, to the authors’ knowledge, the first published application of reachability analysis to stormwater systems. Our second contribution is to offer an interpretation of the outcomes of the proposed reachability analysis as a measure of system robustness that can provide useful information when making critical design decisions. We illustrate the effectiveness of this method in revealing the trade-offs of particular design choices relative to a desired level of robustness. 

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4. A benchmarking framework for control and optimization of smart stormwater networks: demo abstract

   https://doi.org/10.1145/3302509.3313336  

   Rimer, Sara P. ; Mullapudi, Abhiram ; Troutman, Sara C. ; Kerkez, Branko ( January 2019 , ICCPS '19 Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems)
5. Reinforcement Learning for Flooding Mitigation in Complex Stormwater Systems during Large Storms

   https://doi.org/10.1109/EUROCON52738.2021.9535587  

   Wang, Cheng ; Bowes, Benjamin D. ; Beling, Peter A. ; Goodall, Jonathan L. ( July 2021 , IEEE EUROCON 2021 - 19th International Conference on Smart Technologies)

   Compared with capital improvement projects, real-time control of stormwater systems may be a more effective and efficient approach to address the increasing risk of flooding in urban areas. One way to automate the design process of control policies is through reinforcement learning (RL). Recently, RL methods have been applied to small stormwater systems and have demonstrated better performance over passive systems and simple rule-based strategies. However, it remains unclear how effective RL methods are for larger and more complex systems. Current RL-based control policies also suffer from poor convergence and stability, which may be due to large updates made by the underlying RL algorithm. In this study, we use the Proximal Policy Optimization (PPO) algorithm and develop control policies for a medium-sized stormwater system that can significantly mitigate flooding during large storm events. Our approach demonstrates good convergence behavior and stability, and achieves robust out-of-sample performance. 

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