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Assessing Extremes in Hydroclimatology: A Review on Probabilistic Methods

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F22%3A91617" target="_blank" >RIV/60460709:41330/22:91617 - isvavai.cz</a>

  • Result on the web

    <a href="https://www-sciencedirect-com.cyber.usask.ca/science/article/pii/S0022169421013524?via%3Dihub" target="_blank" >https://www-sciencedirect-com.cyber.usask.ca/science/article/pii/S0022169421013524?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.jhydrol.2021.127302" target="_blank" >10.1016/j.jhydrol.2021.127302</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Assessing Extremes in Hydroclimatology: A Review on Probabilistic Methods

  • Original language description

    Here we review methods used for probabilistic analysis of extreme events in Hydroclimatology. We focus on streamflow, precipitation, and temperature extremes at regional and global scales. The review has four thematic sections: 1 probability distributions used to describe hydroclimatic extremes, 2 comparative studies of parameter estimation methods, 3 non stationarity approaches, and 4 model selection tools. Synthesis of the literature shows that: 1 recent studies, in general, agree that precipitation and streamflow extremes should be described by heavy tailed distributions, 2 the Method of Moments is typically the first choice in estimating distribution parameters but it is outperformed by methods such as L Moments LM, Maximum Likelihood ML, Least Squares LS, and Bayesian Markov Chain Monte Carlo BMCMC, 3 there are less popular parameter estimation techniques such as the Maximum Product of Spacings MPS the Elemental Percentile EP, and the Minimum Density Power Divergence Estimator MDPDE that have s

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10505 - Geology

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Hydrology

  • ISSN

    0022-1694

  • e-ISSN

    1879-2707

  • Volume of the periodical

    2022

  • Issue of the periodical within the volume

    605

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    20

  • Pages from-to

    1-20

  • UT code for WoS article

    000752473800001

  • EID of the result in the Scopus database

    2-s2.0-85121921987