Drought Prediction System for Central Europe and Its Validation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F17%3AN0000085" target="_blank" >RIV/00020699:_____/17:N0000085 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/86652079:_____/18:00495658 RIV/62156489:43210/18:43913343

Výsledek na webu

<a href="https://www.researchgate.net/publication/323939853_Drought_Prediction_System_for_Central_Europe_and_Its_Validation" target="_blank" >https://www.researchgate.net/publication/323939853_Drought_Prediction_System_for_Central_Europe_and_Its_Validation</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/geosciences8040104" target="_blank" >10.3390/geosciences8040104</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Drought Prediction System for Central Europe and Its Validation

Popis výsledku v původním jazyce

In recent years, two drought monitoring systems have been developed in the Czech Republic based on the SoilClim and AVISO soil moisture models. The former is run by Mendel University and Global Change Research Institute (CAS), while the latter, by the Czech Hydrometeorological Institute. SoilClim is based more on real soil properties and aimed primarily at agriculture, while AVISO complements the system with more theoretical presumptions about soil, showing, rather, climatological potential. Both soil moisture models were complemented by forecasts on a daily basis, taking meteorological inputs from NWP (Numerical Weather Prediction) models and thus giving short- to mid-range outlooks up to 9 days ahead. Validation of the soil moisture and drought intensity prediction was performed and is presented in this article showing its prediction reliability and potential. In the analysis, we focus mainly on the past year, 2017. The tool has strong predictive power for soil moisture and drought intensity so it is suitable for farmers who need to make decisions about irrigation and production activities. The presented system is fully functional and can be applied in the coming years.

Název v anglickém jazyce

Drought Prediction System for Central Europe and Its Validation

Popis výsledku anglicky

In recent years, two drought monitoring systems have been developed in the Czech Republic based on the SoilClim and AVISO soil moisture models. The former is run by Mendel University and Global Change Research Institute (CAS), while the latter, by the Czech Hydrometeorological Institute. SoilClim is based more on real soil properties and aimed primarily at agriculture, while AVISO complements the system with more theoretical presumptions about soil, showing, rather, climatological potential. Both soil moisture models were complemented by forecasts on a daily basis, taking meteorological inputs from NWP (Numerical Weather Prediction) models and thus giving short- to mid-range outlooks up to 9 days ahead. Validation of the soil moisture and drought intensity prediction was performed and is presented in this article showing its prediction reliability and potential. In the analysis, we focus mainly on the past year, 2017. The tool has strong predictive power for soil moisture and drought intensity so it is suitable for farmers who need to make decisions about irrigation and production activities. The presented system is fully functional and can be applied in the coming years.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Geosciences

ISSN

2076-3263

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

20

Strana od-do

—

Kód UT WoS článku

000434860400002

EID výsledku v databázi Scopus

2-s2.0-85048313432