OSTRICH-SWMM: A new multi-objective optimization tool for green infrastructure planning with SWMM

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.

[1]  Teemu Kokkonen,et al.  Spatial resolution considerations for urban hydrological modelling , 2014 .

[2]  Zhenduo Zhu,et al.  Three-dimensional model to capture the fate and transport of combined sewer overflow discharges: A case study in the Chicago Area Waterway System. , 2017, The Science of the total environment.

[3]  Peter Krebs,et al.  Automatic Calibration Approach for Multiple Rain Events in SWMM Using Latin Hypercube Sampling , 2018, New Trends in Urban Drainage Modelling.

[4]  C. Nietch,et al.  Storm Water Management Model: Performance Review and Gap Analysis. , 2017, Journal of sustainable water in the built environment.

[5]  Robert A. Marryott,et al.  Optimal Groundwater Management: 1. Simulated Annealing , 1991 .

[6]  David J. Sample,et al.  Assessing the Effects of Climate Change on Water Quantity and Quality in an Urban Watershed Using a Calibrated Stormwater Model , 2017 .

[7]  Timothy T Eaton,et al.  Approach and case-study of green infrastructure screening analysis for urban stormwater control. , 2018, Journal of environmental management.

[8]  T. Culver,et al.  Optimal design of a compacted soil liner containing sorptive amendments , 2006 .

[9]  Saad Bennis,et al.  Improving nonlinear optimization algorithms for BMP implementation in a combined sewer system , 2016 .

[10]  Yang Yang,et al.  Optimizing surface and contributing areas of bioretention cells for stormwater runoff quality and quantity management. , 2018, Journal of environmental management.

[11]  David J. Sample,et al.  Reducing combined sewer overflows by using outlet controls for Green Stormwater Infrastructure: Case study in Richmond, Virginia , 2015 .

[12]  L. Shawn Matott,et al.  Calibrating Environment Canada's MESH Modelling System over the Great Lakes Basin , 2014 .

[13]  Tao Tao,et al.  Multi-Objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: Framework Development and Case Study , 2015, Water Resources Management.

[14]  Marcio Giacomoni,et al.  Multi-Objective Evolutionary Optimization and Monte Carlo Simulation for Placement of Low Impact Development in the Catchment Scale , 2017 .

[15]  S Maheepala,et al.  Can stormwater harvesting restore pre-development flows in urban catchments in South East Queensland? , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[16]  Nien-Sheng Hsu,et al.  Optimization of low impact development layout designs for megacity flood mitigation , 2018, Journal of Hydrology.

[17]  Charles R. Severance,et al.  Discovering JavaScript Object Notation , 2012, Computer.

[18]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[19]  L Shawn Matott,et al.  Application of heuristic optimization techniques and algorithm tuning to multilayered sorptive barrier design. , 2006, Environmental science & technology.

[20]  Mohammad Reza Nikoo,et al.  Developing a stochastic conflict resolution model for urban runoff quality management: Application of info-gap and bargaining theories , 2016 .

[21]  Bryan A. Tolson,et al.  Pareto archived dynamically dimensioned search with hypervolume-based selection for multi-objective optimization , 2013 .

[22]  James R. Craig,et al.  Pump-and-treat optimization using analytic element method flow models , 2006 .

[23]  Jeroen C. J. H. Aerts,et al.  A global framework for future costs and benefits of river-flood protection in urban areas , 2017, Nature Climate Change.

[24]  Zulkifli Yusop,et al.  Modelling runoff quantity and quality in tropical urban catchments using Storm Water Management Model , 2012, International Journal of Environmental Science and Technology.

[25]  María Nariné Torres,et al.  A Prioritization Tool for SUDS Planning in Large Cities by Coupling an Urban Drainage Model with Mixed Integer Linear Programming , 2018 .

[26]  Bryan A. Tolson,et al.  Dynamically dimensioned search algorithm for computationally efficient watershed model calibration , 2007 .

[27]  M. Suidan,et al.  Modeling Techniques of Best Management Practices: Rain Barrels and Rain Gardens Using EPA SWMM-5 , 2010 .

[28]  E. Poeter,et al.  Documentation of UCODE; a computer code for universal inverse modeling , 1998 .

[29]  L. Shawn Matott,et al.  Application of MATLAB and Python optimizers to two case studies involving groundwater flow and contaminant transport modeling , 2011, Comput. Geosci..

[30]  Yang Yang,et al.  Simulating the hydrological performance of low impact development in shallow groundwater via a modified SWMM , 2018, Journal of Hydrology.

[31]  John Riverson,et al.  A watershed-scale design optimization model for stormwater best management practices , 2012, Environ. Model. Softw..

[32]  Jane Elith,et al.  Green Infrastructure Design Based on Spatial Conservation Prioritization and Modeling of Biodiversity Features and Ecosystem Services , 2015, Environmental Management.

[33]  N. Alamdari,et al.  Modeling Climate Change Impacts on the Effectiveness of Stormwater Control Measures in Urban Watersheds , 2018 .

[34]  Bryan A. Tolson,et al.  A benchmarking framework for simulation-based optimization of environmental models , 2012, Environ. Model. Softw..

[35]  L. Shawn Matott,et al.  Incorporating nonlinear isotherms into robust multilayer sorptive barrier design , 2009 .

[36]  Ruth W Stidger.  Urban Stormwater Control- What it Costs , 2007 .

[37]  Zahra Zahmatkesh,et al.  A multi-stakeholder framework for urban runoff quality management: Application of social choice and bargaining techniques. , 2016, The Science of the total environment.

[38]  Nico Goldscheider,et al.  Modeling spatially and temporally varied hydraulic behavior of a folded karst system with dominant conduit drainage at catchment scale, Hochifen-Gottesacker, Alps , 2014 .

[39]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[40]  Steven J. Burian,et al.  Hydrologic modeling analysis of a passive, residential rainwater harvesting program in an urbanized, semi-arid watershed , 2014 .

[41]  H. Gao,et al.  USE OF A GENETIC ALGORITHM AND MULTI-OBJECTIVE PROGRAMMING FOR CALIBRATION OF A HYDROLOGIC MODEL , 1998 .

[42]  Mohammad Karamouz,et al.  Reliability-Based Flood Management in Urban Watersheds Considering Climate Change Impacts , 2013 .

[43]  Kun Zhang,et al.  A comprehensive review of spatial allocation of LID-BMP-GI practices: Strategies and optimization tools. , 2018, The Science of the total environment.

[44]  David J. Sample,et al.  Water Quality Characterization of Irrigation and Storm Runoff for a Nursery , 2018, New Trends in Urban Drainage Modelling.

[45]  Brenda Rashleigh,et al.  An integrated modeling framework for performing environmental assessments: Application to ecosystem services in the Albemarle-Pamlico basins (NC and VA, USA) , 2011 .