Optimal Design of Storm Sewer Network Based on Risk Analysis by Combining Genetic Algorithm and SWMM Model

Document Type : Research Article


1 PhD student in Water Structures, Tarbiat Modares University, Tehran, Iran

2 Faculty of Tarbiat Modares University

3 Professor of Shahid Chamran University


The design of an urban storm sewer network is a costly task. Therefore, the design should be done so that the total cost becomes minimal. This requires modeling the problem in an optimization form. Floods are stochastic. Designing such a system is associated with risk. Thus, a project is optimal when both design costs and potential future risks are incorporated. This means that the selection of rainfall-runoff return period has to be based on risk analysis. SWMM software was used to handle hydraulic network simulation and the Network optimization was performed using a genetic algorithm in which the decision variables were the diameter and slope of the pipes. To calculate the cost of run-off damage, relationships for land uses, infrastructure and traffic were provided. The accuracy of the simulation-optimization model seeking the optimal design of the storm sewer network was approved by a benchmark network evaluation. The developed model was implemented in a region of Tehran city to determine the optimal design return period with a risk analysis approach. The results showed that the 10-year return period with is the optimal return period with an annual damage risk cost of 508.68 billion rials, an annual design cost of 943.78 billion rials and a total cost of 1452.45 billion rials. Therefore, the developed method in which the genetic algorithm and SWMM model are combined in addition to the risk-based design approach is an effective tool for the optimal design of storm sewer networks.


Main Subjects

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