Characteristic 'fingerprints' of crop model responses data at different spatial resolutions to weather input

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67179843%3A_____%2F13%3A00395764" target="_blank" >RIV/67179843:_____/13:00395764 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.eja.2013.04.003" target="_blank" >http://dx.doi.org/10.1016/j.eja.2013.04.003</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eja.2013.04.003" target="_blank" >10.1016/j.eja.2013.04.003</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Characteristic 'fingerprints' of crop model responses data at different spatial resolutions to weather input

Popis výsledku v původním jazyce

Crop growth simulation models are increasingly used for regionally assessing the effects of climate change and variability on crop yields. These models require spatially and temporally detailed, location-specific, environmental (weather and soil) and management data as inputs, which are often difficult to obtain consistently for larger regions. Aggregating the resolution of input data for crop model applications may increase the uncertainty of simulations to an extent that is not well understood. The present study aims to systematically analyse the effect of changes in the spatial resolution of weather input data on yields simulated by four crop models (LINTUL-SLIM, DSSAT-CSM, EPIC and WOFOST) which were utilized to test possible interactions between weather input data resolution and specific modelling approaches representing different degrees of complexity. The models were applied to simulate grain yield of spring barley in Finland for 12 years between 1994 and 2005 considering five s

Název v anglickém jazyce

Characteristic 'fingerprints' of crop model responses data at different spatial resolutions to weather input

Popis výsledku anglicky

Crop growth simulation models are increasingly used for regionally assessing the effects of climate change and variability on crop yields. These models require spatially and temporally detailed, location-specific, environmental (weather and soil) and management data as inputs, which are often difficult to obtain consistently for larger regions. Aggregating the resolution of input data for crop model applications may increase the uncertainty of simulations to an extent that is not well understood. The present study aims to systematically analyse the effect of changes in the spatial resolution of weather input data on yields simulated by four crop models (LINTUL-SLIM, DSSAT-CSM, EPIC and WOFOST) which were utilized to test possible interactions between weather input data resolution and specific modelling approaches representing different degrees of complexity. The models were applied to simulate grain yield of spring barley in Finland for 12 years between 1994 and 2005 considering five s

Druh

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

CEP obor

EH - Ekologie – společenstva

OECD FORD obor

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Projekt

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

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

European Journal of Agronomy

ISSN

1161-0301

e-ISSN

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Svazek periodika

49

Číslo periodika v rámci svazku

AUG 2013

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

104-114

Kód UT WoS článku

000320746500011

EID výsledku v databázi Scopus

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