IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i4d10.1007_s11269-022-03066-8.html
   My bibliography  Save this article

Uncertainty Analysis of Flood Control Design Under Multiple Floods

Author

Listed:
  • Yuming Huang

    (Wuhan University
    Nanjing Hydraulic Research Institute)

  • Yanjie Li

    (Guangxi University
    Guangxi University)

  • Min Liu

    (Guangxi University
    Guangxi University)

  • Liang Xiao

    (Guangxi University
    Guangxi University)

  • Fuwan Gan

    (Guangxi University
    Guangxi University)

  • Jian Jiao

    (Nanjing Hydraulic Research Institute)

Abstract

Hydraulic engineerings built on tributaries at the confluence of main and branch streams are significant to river management and runoff regulation. The Flood Control Design Level (FCDL) calculations for these works are directly influenced by tributary floods and supporting effects from the mainstream. However, the determination of design level under main and tributary floods has not been well investigated. To address this issue, the authors proposed a Copula-based approach to analyze the design level under multiple runoff discharge with a case study of the Guiping Shipping Hub(GPSH). The proposed method is compared with the conventional multivariate hydrological elements analysis approach, and the sampling uncertainty is also studied. The results showed that the joint distribution of main and tributary floods is well modeled by Clayton Copula, with PE3s as the best-fit marginal distributions. Furthermore, the different roles of main and branch fluxes in design level calculation can be identified by the offered Flood Control return period(FCRP). And the design levels conducted by the FCRP can avoid the situation over-or-under performed by the OR or AND RP. Moreover, flood combinations uncertainty analysis indicates that the uncertainty of the joint design combinations decreases with the increase of sample size n but increases with the rise of the design T. Finally, the 95% confidence interval and standard deviation of the design level calculated by FCRP are smaller than that of OR RP, which means the FCRP can reduce uncertainty under multiple floods. These results suggest that the proposed FCRP provides an appropriate approach for determining the design level under combined fluxes and serves as a reference for engineering practice.

Suggested Citation

  • Yuming Huang & Yanjie Li & Min Liu & Liang Xiao & Fuwan Gan & Jian Jiao, 2022. "Uncertainty Analysis of Flood Control Design Under Multiple Floods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1175-1189, March.
  • Handle: RePEc:spr:waterr:v:36:y:2022:i:4:d:10.1007_s11269-022-03066-8
    DOI: 10.1007/s11269-022-03066-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03066-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11269-022-03066-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiyuan Deng & Weinan Ren & Ping Feng, 2016. "Design flood recalculation under land surface change," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(2), pages 1153-1169, January.
    2. S. Baidya & Ajay Singh & Sudhindra N. Panda, 2020. "Flood frequency analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(3), pages 1137-1158, February.
    3. Esmaeel Dodangeh & Vijay P. Singh & Binh Thai Pham & Jiabo Yin & Guang Yang & Amirhosein Mosavi, 2020. "Flood Frequency Analysis of Interconnected Rivers by Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(11), pages 3533-3549, September.
    4. Jiabo Yin & Shenglian Guo & Zhangjun Liu & Guang Yang & Yixuan Zhong & Dedi Liu, 2018. "Uncertainty Analysis of Bivariate Design Flood Estimation and its Impacts on Reservoir Routing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1795-1809, March.
    5. Xiyuan Deng & Weinan Ren & Ping Feng, 2016. "Design flood recalculation under land surface change," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(2), pages 1153-1169, January.
    6. Yang Peng & Xianliang Yu & Hongxiang Yan & Jipeng Zhang, 2020. "Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(12), pages 3913-3932, September.
    7. Reza Modarres, 2008. "Regional Frequency Distribution Type of Low Flow in North of Iran by L-moments," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(7), pages 823-841, July.
    8. Fang, Hong-Bin & Fang, Kai-Tai & Kotz, Samuel, 2002. "The Meta-elliptical Distributions with Given Marginals," Journal of Multivariate Analysis, Elsevier, vol. 82(1), pages 1-16, July.
    9. Kui Xu & Chao Ma & Jijian Lian & Lingling Bin, 2014. "Joint Probability Analysis of Extreme Precipitation and Storm Tide in a Coastal City under Changing Environment," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-11, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali Nasiri Khiavi & Mehdi Vafakhah & Seyed Hamidreza Sadeghi, 2022. "Comparative prioritization of sub-watersheds based on Flood Generation potential using physical, hydrological and co-managerial approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 1897-1917, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Na Li & Shenglian Guo & Feng Xiong & Jun Wang & Yuzuo Xie, 2022. "Comparative Study of Flood Coincidence Risk Estimation Methods in the Mainstream and its Tributaries," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 683-698, January.
    2. Jianzhu Li & Qiushuang Ma & Yu Tian & Yuming Lei & Ting Zhang & Ping Feng, 2019. "Flood scaling under nonstationarity in Daqinghe River basin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 675-696, September.
    3. R. K. Jaiswal & T. R. Nayak & A. K. Lohani & R. V. Galkate, 2022. "Regional flood frequency modeling for a large basin in India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1845-1861, March.
    4. Ming Zhong & Ting Zeng & Tao Jiang & Huan Wu & Xiaohong Chen & Yang Hong, 2021. "A Copula-Based Multivariate Probability Analysis for Flash Flood Risk under the Compound Effect of Soil Moisture and Rainfall," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 83-98, January.
    5. Tranmer, Andrew W. & Marti, Clelia L. & Tonina, Daniele & Benjankar, Rohan & Weigel, Dana & Vilhena, Leticia & McGrath, Claire & Goodwin, Peter & Tiedemann, Matthew & Mckean, Jim & Imberger, Jörg, 2018. "A hierarchical modelling framework for assessing physical and biochemical characteristics of a regulated river," Ecological Modelling, Elsevier, vol. 368(C), pages 78-93.
    6. Sabrina Ali & Ataur Rahman, 2022. "Development of a kriging-based regional flood frequency analysis technique for South-East Australia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 2739-2765, December.
    7. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
    8. Shilan Li & Jianxin Shi & Paul Albert & Hong-Bin Fang, 2022. "Dependence Structure Analysis and Its Application in Human Microbiome," Mathematics, MDPI, vol. 11(1), pages 1-14, December.
    9. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    10. Hongshi Xu & Kui Xu & Lingling Bin & Jijian Lian & Chao Ma, 2018. "Joint Risk of Rainfall and Storm Surges during Typhoons in a Coastal City of Haidian Island, China," IJERPH, MDPI, vol. 15(7), pages 1-20, June.
    11. He, Yong & Zhang, Liang & Ji, Jiadong & Zhang, Xinsheng, 2019. "Robust feature screening for elliptical copula regression model," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 568-582.
    12. Dong Hwan Oh & Andrew J. Patton, 2017. "Modeling Dependence in High Dimensions With Factor Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 139-154, January.
    13. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    14. Barry K. Goodwin & Matthew T. Holt & Gülcan Önel & Jeffrey P. Prestemon, 2018. "Copula-based nonlinear modeling of the law of one price for lumber products," Empirical Economics, Springer, vol. 54(3), pages 1237-1265, May.
    15. Kalyagin, V.A. & Koldanov, A.P. & Koldanov, P.A., 2022. "Reliability of maximum spanning tree identification in correlation-based market networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    16. Christian Genest & Johanna Nešlehová & Jean-François Quessy, 2012. "Tests of symmetry for bivariate copulas," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(4), pages 811-834, August.
    17. Krajina, A., 2009. "A Method of Moments Estimator of Tail Dependence in Elliptical Copula Models," Other publications TiSEM f3f5a961-02ff-4a2b-ab93-4, Tilburg University, School of Economics and Management.
    18. Murray D Smith, 2004. "Stochastic Frontier Models With Correlated Error Components," Econometric Society 2004 Australasian Meetings 121, Econometric Society.
    19. Claudia Klüppelberg & Gabriel Kuhn, 2009. "Copula structure analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 737-753, June.
    20. Cherubini, Umberto & Mulinacci, Sabrina & Romagnoli, Silvia, 2011. "A copula-based model of speculative price dynamics in discrete time," Journal of Multivariate Analysis, Elsevier, vol. 102(6), pages 1047-1063, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:36:y:2022:i:4:d:10.1007_s11269-022-03066-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.