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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
20/09/2023 |
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Data da última atualização: |
03/10/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
DIAS, H. B.; CUADRA, S. V.; BOOTE, K. J.; LAMPARELLI, R. A. C.; FIGUEIREDO, G. K. D. A.; SUYKER, A. E.; MAGALHÃES, P. S. G.; HOOGENBOOM, G. |
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Afiliação: |
HENRIQUE BORIOLO DIAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; SANTIAGO VIANNA CUADRA, CNPTIA; KENNETH J. BOOTE, UNIVERSITY OF FLORIDA; RUBENS AUGUSTO CAMARGO LAMPARELLI, UNIVERSIDADE ESTADUAL DE CAMPINAS; GLEYCE KELLY DANTAS ARAÚJO FIGUEIREDO, UNIVERSIDADE ESTADUAL DE CAMPINAS; ANDREW E. SUYKER, UNIVERSITY OF NEBRASKA; PAULO SÉRGIO GRAZIANO MAGALHÃES, UNIVERSIDADE ESTADUAL DE CAMPINAS; GERRIT HOOGENBOOM, UNIVERSITY OF FLORIDA. |
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Título: |
Coupling the CSM-CROPGRO-Soybean crop model with the ECOSMOS Ecosystem Model: an evaluation with data from an AmeriFlux site. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Agricultural and Forest Meteorology, v. 342, 109697, 2023. |
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ISSN: |
0168-1923 |
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DOI: |
http://dx.doi.org/10.1016/j.agrformet.2023.109697 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Process-based simulation models, such as land surface (LSM) and crop models, are useful tools for studying the impacts of the environment, management and genotype on agricultural production. LSM are capable of simulating crop development and growth, but not in as much detail as the processes embedded in crop models. Crop models, on the other hand, do not usually have the ability to solve the surface water, energy and carbon balances, which can help to assess the feedbacks between climate and agricultural systems. The goals of this study were first to implement the well-known Cropping System Model (CSM)-CROPGRO-Soybean model of the Decision Support System for Agrotechnology Transfer (DSSAT) into the Ecosystem Model Simulator (ECOSMOS) LSM and then to evaluate this coupling to simulate surface fluxes and crop performance of irrigated and rainfed soybean agroecosystems with comprehensive data from an AmeriFlux site. After model coupling, simulations were benchmarked against multiple flux (carbon dioxide, energy, and water), phenology, growth, and yield observations obtained from field scale experiments across 14 seasons from irrigated and rainfed fields near Mead, Nebraska. Calibration of the physiological parameters of ECOSMOS and of the CROPGRO-Soybean genetic coefficients was conducted. Common metrics were employed to assess model performance. Overall, the coupled model reproduced both the magnitude and seasonal patterns of the energy balance, carbon dioxide exchange, evapotranspiration and soil water balance. The crop model coupling into ECOSMOS preserves the known high skill of the CROPGRO-Soybean model in simulating soybean phenology and growth dynamics. The simulated yields were consistent with the observations at field level. Although the ECOSMOS-CROPGRO-Soybean model is sufficiently robust to simulate surface fluxes and crop performance of soybean agroecosystems at field scale for the environments of eastern Nebraska, further evaluation for a wide range of climatic and soil conditions and management practices is warranted. MenosAbstract: Process-based simulation models, such as land surface (LSM) and crop models, are useful tools for studying the impacts of the environment, management and genotype on agricultural production. LSM are capable of simulating crop development and growth, but not in as much detail as the processes embedded in crop models. Crop models, on the other hand, do not usually have the ability to solve the surface water, energy and carbon balances, which can help to assess the feedbacks between climate and agricultural systems. The goals of this study were first to implement the well-known Cropping System Model (CSM)-CROPGRO-Soybean model of the Decision Support System for Agrotechnology Transfer (DSSAT) into the Ecosystem Model Simulator (ECOSMOS) LSM and then to evaluate this coupling to simulate surface fluxes and crop performance of irrigated and rainfed soybean agroecosystems with comprehensive data from an AmeriFlux site. After model coupling, simulations were benchmarked against multiple flux (carbon dioxide, energy, and water), phenology, growth, and yield observations obtained from field scale experiments across 14 seasons from irrigated and rainfed fields near Mead, Nebraska. Calibration of the physiological parameters of ECOSMOS and of the CROPGRO-Soybean genetic coefficients was conducted. Common metrics were employed to assess model performance. Overall, the coupled model reproduced both the magnitude and seasonal patterns of the energy balance, carbon dioxide exchan... Mostrar Tudo |
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Palavras-Chave: |
CO2 exchange; Crop modelling. |
|
Thesagro: |
Dióxido de Carbono; Evapotranspiração; Fenologia; Modelo de Simulação; Produtividade; Soja. |
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Thesaurus NAL: |
Crop models; Eddy covariance; Evapotranspiration; Plant growth; Simulation models; Soybeans. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 03263naa a2200397 a 4500
001 2156796
005 2023-10-03
008 2023 bl uuuu u00u1 u #d
022 $a0168-1923
024 7 $ahttp://dx.doi.org/10.1016/j.agrformet.2023.109697$2DOI
100 1 $aDIAS, H. B.
245 $aCoupling the CSM-CROPGRO-Soybean crop model with the ECOSMOS Ecosystem Model$ban evaluation with data from an AmeriFlux site.$h[electronic resource]
260 $c2023
520 $aAbstract: Process-based simulation models, such as land surface (LSM) and crop models, are useful tools for studying the impacts of the environment, management and genotype on agricultural production. LSM are capable of simulating crop development and growth, but not in as much detail as the processes embedded in crop models. Crop models, on the other hand, do not usually have the ability to solve the surface water, energy and carbon balances, which can help to assess the feedbacks between climate and agricultural systems. The goals of this study were first to implement the well-known Cropping System Model (CSM)-CROPGRO-Soybean model of the Decision Support System for Agrotechnology Transfer (DSSAT) into the Ecosystem Model Simulator (ECOSMOS) LSM and then to evaluate this coupling to simulate surface fluxes and crop performance of irrigated and rainfed soybean agroecosystems with comprehensive data from an AmeriFlux site. After model coupling, simulations were benchmarked against multiple flux (carbon dioxide, energy, and water), phenology, growth, and yield observations obtained from field scale experiments across 14 seasons from irrigated and rainfed fields near Mead, Nebraska. Calibration of the physiological parameters of ECOSMOS and of the CROPGRO-Soybean genetic coefficients was conducted. Common metrics were employed to assess model performance. Overall, the coupled model reproduced both the magnitude and seasonal patterns of the energy balance, carbon dioxide exchange, evapotranspiration and soil water balance. The crop model coupling into ECOSMOS preserves the known high skill of the CROPGRO-Soybean model in simulating soybean phenology and growth dynamics. The simulated yields were consistent with the observations at field level. Although the ECOSMOS-CROPGRO-Soybean model is sufficiently robust to simulate surface fluxes and crop performance of soybean agroecosystems at field scale for the environments of eastern Nebraska, further evaluation for a wide range of climatic and soil conditions and management practices is warranted.
650 $aCrop models
650 $aEddy covariance
650 $aEvapotranspiration
650 $aPlant growth
650 $aSimulation models
650 $aSoybeans
650 $aDióxido de Carbono
650 $aEvapotranspiração
650 $aFenologia
650 $aModelo de Simulação
650 $aProdutividade
650 $aSoja
653 $aCO2 exchange
653 $aCrop modelling
700 1 $aCUADRA, S. V.
700 1 $aBOOTE, K. J.
700 1 $aLAMPARELLI, R. A. C.
700 1 $aFIGUEIREDO, G. K. D. A.
700 1 $aSUYKER, A. E.
700 1 $aMAGALHÃES, P. S. G.
700 1 $aHOOGENBOOM, G.
773 $tAgricultural and Forest Meteorology$gv. 342, 109697, 2023.
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