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Multivariate Flood Frequency Analysis Using Bivariate Copula Functions

Author

Listed:
  • Homa Razmkhah

    (Islamic Azad University)

  • Alireza Fararouie

    (Islamic Azad University)

  • Amin Rostami Ravari

    (Islamic Azad University)

Abstract

Multivariate analysis of flood frequency was used extensively in water resources research. Often the only flood peak or volume is analyzed with statistical distributions, but for a perfect and exact result, the four main characteristics of a flood event, as well as peak, volume, duration, and time-to-peak, are needed. For this reason, multivariate statistical approaches like copula functions developed. This research aims to define and use the bivariate copula (2-copula) probability distribution functions (PDF) for flood characteristics multivariate analysis. When the joint distribution of characteristics such as volume and peak is known, it is possible to define the probability of simultaneous occurrence of design volume and peak flow values.

Suggested Citation

  • Homa Razmkhah & Alireza Fararouie & Amin Rostami Ravari, 2022. "Multivariate Flood Frequency Analysis Using Bivariate Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 729-743, January.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:2:d:10.1007_s11269-021-03055-3
    DOI: 10.1007/s11269-021-03055-3
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    References listed on IDEAS

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    1. Olusola O. Ayantobo & Yi Li & Songbai Song, 2019. "Multivariate Drought Frequency Analysis using Four-Variate Symmetric and Asymmetric Archimedean Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 103-127, January.
    2. M. Reddy & Poulomi Ganguli, 2012. "Bivariate Flood Frequency Analysis of Upper Godavari River Flows Using Archimedean Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(14), pages 3995-4018, November.
    3. 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.
    4. Ernst Wit & Edwin van den Heuvel & Jan-Willem Romeijn, 2012. "‘All models are wrong...’: an introduction to model uncertainty," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 217-236, August.
    5. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
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    Cited by:

    1. Poornima Unnikrishnan & Kumaraswamy Ponnambalam & Nirupama Agrawal & Fakhri Karray, 2023. "Joint Flood Risks in the Grand River Watershed," Sustainability, MDPI, vol. 15(12), pages 1-14, June.
    2. Ibrahim Halil Deger & Musa Esıt & Mehmet Ishak Yuce, 2023. "Univariate and Bivariate Hydrological Drought Frequency Analysis by Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(12), pages 4881-4907, September.
    3. Yifan Jia & Songbai Song & Liting Ge, 2023. "Trimmed L-Moments of the Pearson Type III Distribution for Flood Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1321-1340, February.
    4. Shuhui Guo & Lihua Xiong & Jie Chen & Shenglian Guo & Jun Xia & Ling Zeng & Chong-Yu Xu, 2023. "Nonstationary Regional Flood Frequency Analysis Based on the Bayesian Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 659-681, January.

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