Abstract
The rainfall-runoff analysis model in urban watersheds should be constructed to establish flood damage countermeasures. The SWMM (Storm Water Management Model) is a representative model for rainfall-runoff analysis of urban watersheds. While this model is based on many parameters and provides relatively reliable results, it contains many ambiguous parameters. Therefore, parameter estimation is essential for rainfall-runoff analysis model and can be done using optimization algorithms. Harmony search algorithm is used to automatically estimate the parameters of the SWMM. Unlike the previous studies, the parameters are estimated by considering not only the inflow data but also the sewer level data. Parameter estimation is applied to the flood simulation on the catchment of Yongdap pump station basin, Seongdong-gu, Seoul, South Korea. The results estimated by supposed model are reliable in terms of both inflow and sewer level. The verification results of the calibrated model show the error within 5%, which are within the allowable error range.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cho, J.H., Seo, H.J.: Parameter optimization of SWMM for runoff quantity and quality calculation in a eutrophic lake watershed using a genetic algorithm. Water Sci. Technol. Water Supply 7(5–6), 35–41 (2007)
Di Pierro, F., Khu, S.T., Savić, D.: From single-objective to multiple-objective multiple-rainfall events automatic calibration of urban storm water runoff models using genetic algorithms. Water Sci. Technol. 54(6–7), 57–64 (2006)
Kang, T.U., Lee, S.H., Kang, S.U., Park, J.P.: A study for an automatic calibration of urban runoff model by the SCE-UA. J. Korea Water Resour. Assoc. 45(1), 15–27 (2012)
Krebs, G., Kokkonen, T., Valtanen, M., Koivusalo, H., Setälä, H.: A high resolution application of a stormwater management model (SWMM) using genetic parameter optimization. Urban Water J. 10(6), 394–410 (2013)
Lee, J.M., Jin, K.N., Kim, Y.J., Yoon, J.R.: A study on the Establishment of Reasonable Guidelines for Prior Review System on the Influence of Disasters (2010)
Liong, S.Y., Chan, W.T., Lum, L.H.: Knowledge-based system for SWMM runoff component calibration. J. Water Resour. Plan. Manage. 117(5), 507–524 (1991)
Mancipe-Munoz, N.A., Buchberger, S.G., Suidan, M.T., Lu, T.: Calibration of rainfall-runoff model in urban watersheds for stormwater management assessment. J. Water Resour. Plan. Manage. 140(6), 05014001 (2014)
Tan, S.B., Chua, L.H., Shuy, E.B., Lo, E.Y.M., Lim, L.W.: Performances of rainfall-runoff models calibrated over single and continuous storm flow events. J. Hydrol. Eng. 13(7), 597–607 (2008)
Acknowledgements
This work was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) (No. 2016R1A2A1A05005306).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Lim, O., Choi, Y.H., Yoo, D.G., Kim, J.H. (2020). Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed. In: Kim, J., Geem, Z., Jung, D., Yoo, D., Yadav, A. (eds) Advances in Harmony Search, Soft Computing and Applications. ICHSA 2019. Advances in Intelligent Systems and Computing, vol 1063. Springer, Cham. https://doi.org/10.1007/978-3-030-31967-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-31967-0_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31966-3
Online ISBN: 978-3-030-31967-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)