Open Access
ARTICLE
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. 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.
Keywords
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. https://doi.org/10.32604/cmc.2020.06513
Citations