OSTRICH-SWMM: A new multi-objective optimization tool for green infrastructure planning with SWMM. (March 2019)

• Record Type: Journal Article
• Authors: Macro, Kristina; Matott, L. Shawn; Rabideau, Alan; Ghodsi, Seyed Hamed; Zhu, Zhenduo
• Is Part Of: Environmental modelling & software. Volume 113(2019)
• Page Start: 42
• Page End: 47
• Publication Date: 2019-03
• Subjects: Green infrastructure -- Multi-objective optimization -- SWMM -- Rain barrel; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.12.004
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The installation of Green Infrastructure (GI) can revitalize communities while reducing sewage overflows and improving runoff quality. However, determining the proper GI investment is a challenging management task. Numerical hydrologic models, such as the Storm Water Management Model (SWMM), are the primary design tool for GI. A new open-source multi-objective SWMM optimization tool was developed by connecting SWMM with the existing Optimization Software Toolkit for Research Involving Computational Heuristics (OSTRICH). In contrast to similar tools, it is open-source and has a large selection of parallelized algorithms. A case study of stormwater management in Buffalo, New York, demonstrated how the tool can illuminate trade-offs between the cost of rain barrel placement and the resulting reduction in combined sewer overflows. In the future, this tool could be used to optimize different types of GI features and contribute to a broader decision support framework for urban land use and stormwater management. Highlights: A new open-source tool was developed for optimizing green infrastructure. Rain barrel placement was optimized to balance runoff volume reduction with cost. The performance of some of the tool's parallelized algorithms was explored.