Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985874%3A_____%2F15%3A00445334" target="_blank" >RIV/67985874:_____/15:00445334 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00020699:_____/15:N0000015

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.jhydrol.2015.07.008" target="_blank" >http://dx.doi.org/10.1016/j.jhydrol.2015.07.008</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jhydrol.2015.07.008" target="_blank" >10.1016/j.jhydrol.2015.07.008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator

Popis výsledku v původním jazyce

Ensemble Streamflow Prediction (ESP) provides an efficient tool for seasonal hydrological forecasts. In this study, we propose a new modification of input data series for the ESP system used for the runoff volume prediction with a lead of one month. These series are not represented by short historical weather datasets but by longer generated synthetic weather data series. Before their submission to the hydrological model, their number is restricted by relations among observed meteorological variables (average monthly precipitation and temperature) and large-scale climatic patterns and indices (e.g. North Atlantic Oscillation, sea level pressure values and two geopotential heights). This modification was tested over a four-year testing period using theriver basin in central Europe. The LARS-WG weather generator proved to be a suitable tool for the extension of the historical weather records. The modified ESP approach proved to be more efficient in the majority of months compared both t

Název v anglickém jazyce

Modification of input datasets for the Ensemble Streamflow Prediction based on large scale climatic indices and weather generator

Popis výsledku anglicky

Ensemble Streamflow Prediction (ESP) provides an efficient tool for seasonal hydrological forecasts. In this study, we propose a new modification of input data series for the ESP system used for the runoff volume prediction with a lead of one month. These series are not represented by short historical weather datasets but by longer generated synthetic weather data series. Before their submission to the hydrological model, their number is restricted by relations among observed meteorological variables (average monthly precipitation and temperature) and large-scale climatic patterns and indices (e.g. North Atlantic Oscillation, sea level pressure values and two geopotential heights). This modification was tested over a four-year testing period using theriver basin in central Europe. The LARS-WG weather generator proved to be a suitable tool for the extension of the historical weather records. The modified ESP approach proved to be more efficient in the majority of months compared both t

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

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

—

Svazek periodika

528

Číslo periodika v rámci svazku

September

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

14

Strana od-do

720-733

Kód UT WoS článku

000358968200059

EID výsledku v databázi Scopus

2-s2.0-84937238991