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    <titleInfo>
        <title>Revisiting flood peak distributions: A pan-Canadian investigation</title>
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    <name type="personal">
        <namePart type="given">Mohanad</namePart>
        <namePart type="family">Zaghloul</namePart>
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    <name type="personal">
        <namePart type="given">S</namePart>
        <namePart type="family">Papalexiou</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Amin</namePart>
        <namePart type="family">Elshorbagy</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Paulin</namePart>
        <namePart type="family">Coulibaly</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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        <dateIssued>2020</dateIssued>
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            <title>Advances in Water Resources, Volume 145</title>
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            <issuance>continuing</issuance>
            <publisher>Elsevier BV</publisher>
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        <genre authority="marcgt">periodical</genre>
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    <abstract>\bullet Analysis shows the G E V distribution might not be the best choice for flood frequency analysis. \bullet Burr type III and XII are consistent and robust models to describe annual flood peaks. \bullet Pan-Canadian investigation of annual streamflow peaks. Safe and cost-effective design of infrastructures, such as dams, bridges, highways, often requires knowing the magnitude and frequency of peak floods. The Generalized Extreme Value distribution ( G E V ) prevailed in flood frequency analysis along with distributions comprising location, scale, and shape parameters. Here we explore alternative models and propose power-type models, having one scale and two shape parameters. The Burr type III ( Ɓr III) and XII ( Ɓ rXII) distributions are compared against the G E V in 1088 streamflow records of annual peaks across Canada. A generic L-moment algorithm is devised to fit the distributions, also applicable to distributions without analytical L-moment expressions. The analysis shows: (1) the models perform equally well when describing the observed annual peaks; (2) the right tail appears heavier in the Ɓr III and Ɓr XII models leading to larger streamflow predictions when compared to those of G E V ; (3) the G E V predicts upper streamflow limits in 39.1% of the records—these limits have realistic exceedance probabilities based on the other two models; (4) the tail heaviness estimation seems not robust in the G E V case when compared to the Ɓr III and Ɓr XII models and this could challenge G E V ’s reliability in predicting streamflow at large return periods; and, (5) regional variation is observed in the behaviour of flood peaks across different climatic regions of Canada. The findings of this study reveal potential limitations in using the G E V for flood frequency analysis and suggest the Ɓr III and Ɓr XII as consistent alternatives worth exploring.</abstract>
    <identifier type="citekey">Zaghloul-2020-Revisiting</identifier>
    <identifier type="doi">10.1016/j.advwatres.2020.103720</identifier>
    <location>
        <url>https://gwf-uwaterloo.github.io/gwf-publications/G20-21001</url>
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    <part>
        <date>2020</date>
        <detail type="volume"><number>145</number></detail>
        <detail type="page"><number>103720</number></detail>
    </part>
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%0 Journal Article
%T Revisiting flood peak distributions: A pan-Canadian investigation
%A Zaghloul, Mohanad
%A Papalexiou, S.
%A Elshorbagy, Amin
%A Coulibaly, Paulin
%J Advances in Water Resources, Volume 145
%D 2020
%V 145
%I Elsevier BV
%F Zaghloul-2020-Revisiting
%X \bullet Analysis shows the G E V distribution might not be the best choice for flood frequency analysis. \bullet Burr type III and XII are consistent and robust models to describe annual flood peaks. \bullet Pan-Canadian investigation of annual streamflow peaks. Safe and cost-effective design of infrastructures, such as dams, bridges, highways, often requires knowing the magnitude and frequency of peak floods. The Generalized Extreme Value distribution ( G E V ) prevailed in flood frequency analysis along with distributions comprising location, scale, and shape parameters. Here we explore alternative models and propose power-type models, having one scale and two shape parameters. The Burr type III ( Ɓr III) and XII ( Ɓ rXII) distributions are compared against the G E V in 1088 streamflow records of annual peaks across Canada. A generic L-moment algorithm is devised to fit the distributions, also applicable to distributions without analytical L-moment expressions. The analysis shows: (1) the models perform equally well when describing the observed annual peaks; (2) the right tail appears heavier in the Ɓr III and Ɓr XII models leading to larger streamflow predictions when compared to those of G E V ; (3) the G E V predicts upper streamflow limits in 39.1% of the records—these limits have realistic exceedance probabilities based on the other two models; (4) the tail heaviness estimation seems not robust in the G E V case when compared to the Ɓr III and Ɓr XII models and this could challenge G E V ’s reliability in predicting streamflow at large return periods; and, (5) regional variation is observed in the behaviour of flood peaks across different climatic regions of Canada. The findings of this study reveal potential limitations in using the G E V for flood frequency analysis and suggest the Ɓr III and Ɓr XII as consistent alternatives worth exploring.
%R 10.1016/j.advwatres.2020.103720
%U https://gwf-uwaterloo.github.io/gwf-publications/G20-21001
%U https://doi.org/10.1016/j.advwatres.2020.103720
%P 103720

Markdown (Informal)

[Revisiting flood peak distributions: A pan-Canadian investigation](https://gwf-uwaterloo.github.io/gwf-publications/G20-21001) (Zaghloul et al., GWF 2020)

• Revisiting flood peak distributions: A pan-Canadian investigation (Zaghloul et al., GWF 2020)

ACL

• Mohanad Zaghloul, S. Papalexiou, Amin Elshorbagy, and Paulin Coulibaly. 2020. Revisiting flood peak distributions: A pan-Canadian investigation. Advances in Water Resources, Volume 145, 145:103720.