Open Access

ARTICLE

Parameter Calibration of SWMM Model Based on Optimization Algorithm

Fengchang Xue^{1, *}, 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. https://doi.org/10.32604/cmc.2020.06513

Received 03 March 2019; Accepted 10 September 2019; Issue published 16 September 2020

Abstract

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.

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Citations