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Comparative Study of Flood Coincidence Risk Estimation Methods in the Mainstream and its Tributaries

Author

Listed:
  • Na Li

    (Wuhan University)

  • Shenglian Guo

    (Wuhan University)

  • Feng Xiong

    (Bureau of Hydrology, Changjiang Water Resources Commission)

  • Jun Wang

    (Wuhan University)

  • Yuzuo Xie

    (Wuhan University)

Abstract

The coincidence of floods in the mainstream and its tributaries may lead to a large flooding in the downstream confluence area, and the flood coincidence risk analysis is very important for flood prevention and disaster reduction. In this study, the multiple regression model was used to establish the functional relationship among flood magnitudes in the mainstream and its tributaries. The mixed von Mises distribution and Pearson Type III distribution were selected to fit the probability distribution of the annual maximum flood occurrence dates and magnitudes, respectively. The joint distributions of the annual maximum flood occurrence dates and magnitudes were established using copula function, respectively. Fuhe River in the Poyang Lake region was selected as a study case. The joint probability, co-occurrence probability and conditional probability of flood magnitudes were quantitatively estimated and compared with the predicted flood coincidence risks. The results show that the selected marginal and joint distributions can fit observed flood dataset very well. The coincidence probabilities of flood occurrence dates in the upper mainstream and its tributaries mainly occur from May to early July. It is found that the conditional probability is the most consistent with the predicted flood coincidence risks in the mainstream and its tributaries, and is more reliable and rational in practice.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:2:d:10.1007_s11269-021-03050-8
    DOI: 10.1007/s11269-021-03050-8
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    References listed on IDEAS

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    1. Davor Kvočka & Roger A. Falconer & Michaela Bray, 2016. "Flood hazard assessment for extreme flood events," 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. 84(3), pages 1569-1599, December.
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    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.
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    Cited by:

    1. Zhenyu Mu & Xueshan Ai & Jie Ding & Kui Huang & Senlin Chen & Jiajun Guo & Zuo Dong, 2022. "Risk Analysis of Dynamic Water Level Setting of Reservoir in Flood Season Based on Multi-index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3067-3086, July.
    2. Karim Solaimani & Fatemeh Shokrian & Shadman Darvishi, 2023. "An Assessment of the Integrated Multi-Criteria and New Models Efficiency in Watershed Flood Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 403-425, January.
    3. Zhangjun Liu & Jingwen Zhang & Tianfu Wen & Jingqing Cheng, 2022. "Uncertainty Quantification of Rainfall-runoff Simulations Using the Copula-based Bayesian Processor: Impacts of Seasonality, Copula Selection and Correlation Coefficient," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 4981-4993, October.

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