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Flood Frequency Analysis of Interconnected Rivers by Copulas

Author

Listed:
  • Esmaeel Dodangeh

    (Sari Agriculture Science and Natural Resources University)

  • Vijay P. Singh

    (Texas A & M University)

  • Binh Thai Pham

    (Duy Tan University)

  • Jiabo Yin

    (Wuhan University)

  • Guang Yang

    (University of Wisconsin-Madison)

  • Amirhosein Mosavi

    (Ton Duc Thang University
    Ton Duc Thang University)

Abstract

Flood frequency analysis (FFA) considering the confluence of interconnected rivers is important for hydraulic structures (such as dams or diversions) design, but it has received little attention. This study develops a copula-based method for FFA and quantile estimation considering the confluence of two interconnected rivers, along with the uncertainty estimation by a nonparametric bootstrapping algorithm. Flood probability distribution and return periods are estimated for the two rivers by mapping from bivariate to univariate peak flow quantile estimation. The methodology is applied to the case study of Qezel Ozan and Shahrud Rivers which merge to one of the largest reservoir dams in Iran: Sefidrud (Manjil) dam. According to the results from Peak flow records from Gilvan station (GPF) at Qezel Ozan River and from Loshan station (LCF) at Shahrud River, Gaussian copula with Weibull and gamma margins fits best. Also, it shows that some peak flow quantiles with the same magnitudes have a different probability of occurrences at the confluence of the rivers, and the bivariate estimation uncertainty usually plays an important role in FFA. These findings suggest the use of bivariate instead of univariate distributions to the peak flows at the confluence of interconnected rivers, in which the sampling uncertainty should be considered.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:11:d:10.1007_s11269-020-02634-0
    DOI: 10.1007/s11269-020-02634-0
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    References listed on IDEAS

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    1. W. Breymann & A. Dias & P. Embrechts, 2003. "Dependence structures for multivariate high-frequency data in finance," Quantitative Finance, Taylor & Francis Journals, vol. 3(1), pages 1-14.
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    3. Bahram Saghafian & Hossein Mehdikhani, 2014. "Drought characterization using a new copula-based trivariate approach," 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. 72(3), pages 1391-1407, July.
    4. 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.
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    Cited by:

    1. 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.
    2. 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.
    3. Zhang, Yaling & Guo, Li & Liang, Chuan & Zhao, Lu & Wang, Junqin & Zhan, Cun & Jiang, Shouzheng, 2022. "Encounter risk analysis of crop water requirements and effective precipitation based on the copula method in the Hilly Area of Southwest China," Agricultural Water Management, Elsevier, vol. 266(C).
    4. 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.
    5. 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.
    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.

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