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
    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
    Country/TerritoryChina
    CityKunming
    Period19/7/2019/7/22

    Bibliographical note

    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.

    Keywords

    • Calibration
    • Parameter estimation
    • SWMM
    • Sewer level data

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • General Computer Science

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