At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions

Felício Cassalho (), Samuel Beskow, Carlos Rogério Mello, Maíra Martim Moura, Laura Kerstner and Leo Fernandes Ávila
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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

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 1, No 17, 285-300

Abstract: 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.

Keywords: GEV; Kappa; Wakeby; L-moments; Flood risk; Water resources management (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11269-017-1810-7

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