Performance of 13 crop simulation models and their ensemble for simulating four field crops in Central Europe

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F21%3A00549294" target="_blank" >RIV/86652079:_____/21:00549294 - isvavai.cz</a>

Alternative codes found

RIV/62156489:43210/21:43919933

Result on the web

<a href="https://www.cambridge.org/core/journals/journal-of-agricultural-science/article/abs/performance-of-13-crop-simulation-models-and-their-ensemble-for-simulating-four-field-crops-in-central-europe/AC757AB2629DC7C537C2DA9696B59CD6" target="_blank" >https://www.cambridge.org/core/journals/journal-of-agricultural-science/article/abs/performance-of-13-crop-simulation-models-and-their-ensemble-for-simulating-four-field-crops-in-central-europe/AC757AB2629DC7C537C2DA9696B59CD6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1017/S0021859621000216" target="_blank" >10.1017/S0021859621000216</a>

Result language

angličtina

Original language name

Performance of 13 crop simulation models and their ensemble for simulating four field crops in Central Europe

Original language description

The main aim of the current study was to present the abilities of widely used crop models to simulate four different field crops (winter wheat, spring barley, silage maize and winter oilseed rape). The 13 models were tested under Central European conditions represented by three locations in the Czech Republic, selected using temperature and precipitation gradients for the target crops in this region. Based on observed crop phenology and yield from 1991 to 2010, performances of individual models and their ensemble were analyzed. Modelling of anthesis and maturity was generally best simulated by the ensemble median (EnsMED) compared to the ensemble mean and individual models. The yield was better simulated by the best models than estimated by an ensemble. Higher accuracy was achieved for spring crops, with the best results for silage maize, while the lowest accuracy was for winter oilseed rape according to the index of agreement (IA). Based on EnsMED, the root mean square errors (RMSEs) for yield was 1365 kg/ha for winter wheat, 1105 kg/ha for spring barley, 1861 kg/ha for silage maize and 969 kg/ha for winter oilseed rape. The AQUACROP and EPIC models performed best in terms of spread around the line of best fit (RMSE, IA). In some cases, the individual models failed. For crop rotation simulations, only models with reasonable accuracy (i.e. without failures) across all included crops within the target environment should be selected. Application crop models ensemble is one way to increase the accuracy of predictions, but lower variability of ensemble outputs was confirmed.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

40101 - Agriculture

Project

<a href="/en/project/EF16_019%2F0000797" target="_blank" >EF16_019/0000797: SustES - Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions</a><br>

Continuities

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

Publication year

2021

Confidentiality

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

Name of the periodical

Journal of Agricultural Science

ISSN

0021-8596

e-ISSN

1469-5146

Volume of the periodical

159

Issue of the periodical within the volume

1-2

Country of publishing house

GB - UNITED KINGDOM

Number of pages

21

Pages from-to

S0021859621000216

UT code for WoS article

000721282400010

EID of the result in the Scopus database

2-s2.0-85107362839