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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationAdvances in Harmony Search, Soft Computing and Applications, ICHSA 2019
EditorsJoong Hoon Kim, Zong Woo Geem, Donghwi Jung, Do Guen Yoo, Anupam Yadav
PublisherSpringer
Pages70-75
Number of pages6
ISBN (Print)9783030319663
DOIs
Publication statusPublished - 2020 Jan 1
Event5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019 - Kunming, China
Duration: 2019 Jul 202019 Jul 22

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1063
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019
CountryChina
CityKunming
Period19/7/2019/7/22

Keywords

  • Calibration
  • Parameter estimation
  • Sewer level data
  • SWMM

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Parameter Estimation of Storm Water Management Model with Sewer Level Data in Urban Watershed'. Together they form a unique fingerprint.

  • Cite this

    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