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Parameter Calibration of SWMM Model Based on Optimization Algorithm

Fengchang Xue1, *, Juan Tian1, Wei Wang2, Yanran Zhang1, Gohar Ali3

1 Nanjing University of Information Science & Technology, Nanjing, 210044, China.
2 Zhejiang Meteorological Bureau, Hangzhou, 31000, China.
3 Pakistan Meteorological Department, Islamabad, Pakistan.

* Corresponding Author: Fengchang Xue. Email: .

Computers, Materials & Continua 2020, 65(3), 2189-2199.


For the challenge of parameter calibration in the process of SWMM (storm water management model) model application, we use particle Swarm Optimization (PSO) and Sequence Quadratic Programming (SQP) in combination to calibrate the parameters and get the optimal parameter combination in this research. Then, we compare and analyze the simulation result with the other two respectively using initial parameters and parameters obtained by PSO algorithm calibration alone. The result shows that the calibration result of PSO-SQP combined algorithm has the highest accuracy and shows highly consistent with the actual situation, which provides a scientific and effective new idea for parameter calibration of SWMM model, moreover, has practical guidance for flood control and disaster mitigation.


Cite This Article

F. Xue, J. Tian, W. Wang, Y. Zhang and G. Ali, "Parameter calibration of swmm model based on optimization algorithm," Computers, Materials & Continua, vol. 65, no.3, pp. 2189–2199, 2020.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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