4.7 Article

At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions

期刊

WATER RESOURCES MANAGEMENT
卷 32, 期 1, 页码 285-300

出版社

SPRINGER
DOI: 10.1007/s11269-017-1810-7

关键词

GEV; Kappa; Wakeby; L-moments; Flood risk; Water resources management

资金

  1. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [307523/2014-4, 303059/2013-3, 485279/2013-4]
  2. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
  3. Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [PPM X 415/2016]
  4. Fundacao de Amparo a Pesquisa do Estado do Rio Grande do Sul (FAPERGS) [2082-2551/13-0]

向作者/读者索取更多资源

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.

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