Assessing Extremes in Hydroclimatology: A Review on Probabilistic Methods

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Assessing Extremes in Hydroclimatology: A Review on Probabilistic Methods

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Assessing Extremes in Hydroclimatology: A Review on Probabilistic Methods

Popis výsledku anglicky

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

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10505 - Geology

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Journal of Hydrology

ISSN

0022-1694

e-ISSN

1879-2707

Svazek periodika

2022

Číslo periodika v rámci svazku

605

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

20

Strana od-do

1-20

Kód UT WoS článku

000752473800001

EID výsledku v databázi Scopus

2-s2.0-85121921987