Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed

Oseong Lim; Young Hwan Choi; Do Guen Yoo; Joong Hoon Kim

doi:10.1007/978-3-030-31967-0_8

Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed

Oseong Lim, Young Hwan Choi, Do Guen Yoo, Joong Hoon Kim

School of Civil, Environmental and Architectural Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019
Editors	Joong Hoon Kim, Zong Woo Geem, Donghwi Jung, Do Guen Yoo, Anupam Yadav
Publisher	Springer
Pages	70-75
Number of pages	6
ISBN (Print)	9783030319663
DOIs	https://doi.org/10.1007/978-3-030-31967-0_8
Publication status	Published - 2020
Event	5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019 - Kunming, China Duration: 2019 Jul 20 → 2019 Jul 22

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1063
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019
Country	China
City	Kunming
Period	19/7/20 → 19/7/22

Keywords

Calibration
Parameter estimation
SWMM
Sewer level data

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science(all)

Access to Document

10.1007/978-3-030-31967-0_8

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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 J. H. Kim, Z. W. Geem, D. Jung, D. G. Yoo, & A. Yadav (Eds.), Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019 (pp. 70-75). (Advances in Intelligent Systems and Computing; Vol. 1063). Springer. https://doi.org/10.1007/978-3-030-31967-0_8

Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed. / Lim, Oseong; Choi, Young Hwan; Yoo, Do Guen; Kim, Joong Hoon.

Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019. ed. / Joong Hoon Kim; Zong Woo Geem; Donghwi Jung; Do Guen Yoo; Anupam Yadav. Springer, 2020. p. 70-75 (Advances in Intelligent Systems and Computing; Vol. 1063).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lim, O, Choi, YH, Yoo, DG & Kim, JH 2020, Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed. in JH Kim, ZW Geem, D Jung, DG Yoo & A Yadav (eds), Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019. Advances in Intelligent Systems and Computing, vol. 1063, Springer, pp. 70-75, 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019, Kunming, China, 19/7/20. https://doi.org/10.1007/978-3-030-31967-0_8

Lim O, Choi YH, Yoo DG, Kim JH. Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed. In Kim JH, Geem ZW, Jung D, Yoo DG, Yadav A, editors, Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019. Springer. 2020. p. 70-75. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-31967-0_8

Lim, Oseong ; Choi, Young Hwan ; Yoo, Do Guen ; Kim, Joong Hoon. / Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed. Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019. editor / Joong Hoon Kim ; Zong Woo Geem ; Donghwi Jung ; Do Guen Yoo ; Anupam Yadav. Springer, 2020. pp. 70-75 (Advances in Intelligent Systems and Computing).

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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.",

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N1 - Funding Information: Acknowledgements. This work was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) (No. 2016R1A2A1A-05005306). Publisher Copyright: © 2020, Springer Nature Switzerland AG.

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N2 - 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.

AB - 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.

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Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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