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At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions

Author

Listed:
  • Felício Cassalho

    (Federal University of Pelotas)

  • Samuel Beskow

    (Federal University of Pelotas)

  • Carlos Rogério Mello

    (Federal University of Lavras)

  • Maíra Martim Moura

    (Federal University of Pelotas)

  • Laura Kerstner

    (Federal University of Pelotas)

  • Leo Fernandes Ávila

    (Federal University of Pelotas)

Abstract

The proper design of hydraulic structures as well as river basin management are directly dependent on adequate estimates of maximum streamflow, preferably obtained from long historical series. However, the scarce hydrological monitoring, recurrent in developing countries and the need for estimates associated with high return periods (RPs) have led to the use of estimation methods based statistical procedures, such as at-site flood frequency analysis. This study presents a framework for at-site flood frequency analysis coupled with multiparameter probability distribution functions (PDFs) (GEV, LN3, PE3, GLO, GPA, KAP and WAK), in which all the statistical procedures are derived from L-moments, in order to investigate the applicability of these PDFs in comparison to those of 2-parameters (EV1, LN2 and Gamma). The modeling framework was evaluated considering 106 maximum annual streamflow (MAS) series for the Rio Grande do Sul State - Brazil. PDFs’ goodness-of-fit was studied in accordance with the Anderson-Darling test. It can be concluded that: i) the multiparameter distributions, especially KAP and WAK, had performance superior to the traditional 2-parameter distributions, providing a greater number of historical series better adjusted by such multiparameter PDFs; ii) shorter series were usually better represented by GEV when compared to the other PDFs, which is an important characteristic when long historical series are not frequently available; and iii) the quantile estimates derived from multiparameter PDFs presented lower Relative Absolute Error, thus emphasizing the importance of using such PDFs in water resources management and engineering projects.

Suggested Citation

  • Felício Cassalho & Samuel Beskow & Carlos Rogério Mello & Maíra Martim Moura & Laura Kerstner & Leo Fernandes Ávila, 2018. "At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 285-300, January.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:1:d:10.1007_s11269-017-1810-7
    DOI: 10.1007/s11269-017-1810-7
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    References listed on IDEAS

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    Cited by:

    1. Samiran Das, 2020. "Assessing the Regional Concept with Sub-Sampling Approach to Identify Probability Distribution for at-Site Hydrological Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 803-817, January.
    2. Wiesław Szulczewski & Wojciech Jakubowski, 2018. "The Application of Mixture Distribution for the Estimation of Extreme Floods in Controlled Catchment Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3519-3534, August.
    3. Samiran Das, 2022. "Performance of a multi-parameter distribution in the estimation of extreme rainfall in tropical monsoon climate conditions," 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. 110(1), pages 191-205, January.
    4. Sonali Swetapadma & C. S. P. Ojha, 2020. "Selection of a basin-scale model for flood frequency analysis in Mahanadi river basin, 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. 102(1), pages 519-552, May.
    5. Pezhman Allahbakhshian-Farsani & Mehdi Vafakhah & Hadi Khosravi-Farsani & Elke Hertig, 2020. "Regional Flood Frequency Analysis Through Some Machine Learning Models in Semi-arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2887-2909, July.
    6. Fawad, Muhammad & Yan, Ting & Chen, Lu & Huang, Kangdi & Singh, Vijay P., 2019. "Multiparameter probability distributions for at-site frequency analysis of annual maximum wind speed with L-Moments for parameter estimation," Energy, Elsevier, vol. 181(C), pages 724-737.

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