'Fingerprints' of four crop models as affected by soil input data aggregation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F14%3A00230502" target="_blank" >RIV/62156489:43210/14:00230502 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67179843:_____/14:00433077

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S1161030114000914" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1161030114000914</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eja.2014.07.005" target="_blank" >10.1016/j.eja.2014.07.005</a>

Jazyk výsledku

angličtina

Název v původním jazyce

'Fingerprints' of four crop models as affected by soil input data aggregation

Popis výsledku v původním jazyce

The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptakeand drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form

Název v anglickém jazyce

'Fingerprints' of four crop models as affected by soil input data aggregation

Popis výsledku anglicky

The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptakeand drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form

Druh

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

CEP obor

DG - Vědy o atmosféře, meteorologie

OECD FORD obor

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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

2014

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

61

Číslo periodika v rámci svazku

November 2014

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

14

Strana od-do

35-48

Kód UT WoS článku

344206100004

EID výsledku v databázi Scopus

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