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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/62156489:43210/21:43919933

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40101 - Agriculture

Projekt

<a href="/cs/project/EF16_019%2F0000797" target="_blank" >EF16_019/0000797: SustES - Adaptační strategie pro udržitelnost ekosystémových služeb a potravinové bezpečnosti v nepříznivých přírodních podmínkách</a><br>

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Journal of Agricultural Science

ISSN

0021-8596

e-ISSN

1469-5146

Svazek periodika

159

Číslo periodika v rámci svazku

1-2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

21

Strana od-do

S0021859621000216

Kód UT WoS článku

000721282400010

EID výsledku v databázi Scopus

2-s2.0-85107362839