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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
28/10/2025 |
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Data da última atualização: |
19/01/2026 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
KOTHARI, K.; SUYKER, A.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S.; CONSTANTIN, J.; CUADRA, S. V.; DEBAEKE, P.; ELLI, E. F.; FAYE, B.; FLEISHER, D.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; KIMBALL, B.; LEUNG, F.; MARIN, F.; NENDEL, C.; QIAN, B.; SCHOVING, C. |
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Afiliação: |
KRITIKA KOTHARI, UNIVERSITY OF KENTUCKY, INDIAN INSTITUTE OF TECHNOLOGY ROORKEE; ANDREW SUYKER, UNIVERSITY OF NEBRASKA-LINCOLN; RAFAEL BATTISTI, UNIVERSIDADE FEDERAL DE GOIÁS; KENNETH J. BOOTE, UNIVERSITY OF FLORIDA; SOTIRIOS ARCHONTOULIS, IOWA STATE UNIVERSITY; JULIE CONSTANTIN, UNIVERSITÉ DE TOULOUSE; SANTIAGO VIANNA CUADRA, CNPTIA; PHILIPPE DEBAEKE, UNIVERSITÉ DE TOULOUSE; ELVIS F. ELLI, UNIVERSITY OF ARKANSAS SYSTEM DIVISION OF AGRICULTURE; BABACAR FAYE, UNIVERSITY OF SINE SALOUM EL HÂDJ IBRAHIMA NIASS; DAVID FLEISHER, THE AGRICULTURAL RESEARCH SERVICE; BRIAN GRANT, OTTAWA RESEARCH AND DEVELOPMENT CENTRE; GERRIT HOOGENBOOM, UNIVERSITY OF FLORIDA; QI JING, OTTAWA RESEARCH AND DEVELOPMENT CENTRE; BRUCE KIMBALL, THE AGRICULTURAL RESEARCH SERVICE; FELIX LEUNG, THE CHINESE UNIVERSITY OF HONG KONG; FABIO MARIN, UNIVERSIDADE DE SÃO PAULO; CLAAS NENDEL, LEIBNIZ CENTRE FOR AGRICULTURAL LANDSCAPE RESEARCH, UNIVERSITY OF POTSDAM; BUDONG QIAN, OTTAWA RESEARCH AND DEVELOPMENT CENTRE; CELINE SCHOVING, UNIVERSITÉ DE TOULOUSE. |
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Título: |
Inter-comparison of soybean models for simulation of evapotranspiration under rainfed and irrigated conditions. |
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Ano de publicação: |
2026 |
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Fonte/Imprenta: |
Agricultural and Forest Meteorology, v. 376, 110882, Jan. 2026. |
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DOI: |
https://doi.org/10.1016/j.agrformet.2025.110882 |
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Idioma: |
Inglês |
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Conteúdo: |
Accurate estimation of evapotranspiration (ET) is crucial for agricultural water management and crop yield prediction. Crop models are frequently used to simulate ET; however, model testing against detailed ET data remains scarce. The objective of this study was to evaluate nine soybean models that incorporated various approaches to estimate ET (n = 19 methods) using high resolution, multi-season eddy flux measurements from rainfed and irrigated soybean at Mead, Nebraska. Field measurements of crop growth, leaf area index (LAI), soil water content, and ET were provided to the modelers sequentially as follows: 1) phenology data for a Blind calibration; 2) irrigated crop growth; 3) irrigated daily ET and soil water; 4) rainfed ET and soil water; and 5) rainfed crop growth. Among models and ET methods, daily ET was simulated with normalized root mean square errors (nRMSE) ranging from 21.5 to 72.8 % after Full calibration, and root mean square errors (RMSE) were 0.7–2.4 mm d−1. The ensemble median across models (E-Median) reduced error in the simulation of daily ET and ranked highly across calibration steps and developmental phases. Furthermore, the E-Median showed reasonable performance under Blind calibration, with a RMSE of 0.90 mm d−1 (nRMSE= 27.7 %) for daily ET and 70.4 mm (16.7 %) for seasonal ET, indicating it can be a valuable approach for model-based ET estimation when data is scarce. This study revealed the major sources of uncertainty in simulating ET and identified opportunities for improving associated model processes, including 1) residue effects on soil evaporation during incomplete canopy cover, 2) potential ET of soybean, particularly during full canopy, and 3) leaf senescence effects on LAI during the late reproductive phase. MenosAccurate estimation of evapotranspiration (ET) is crucial for agricultural water management and crop yield prediction. Crop models are frequently used to simulate ET; however, model testing against detailed ET data remains scarce. The objective of this study was to evaluate nine soybean models that incorporated various approaches to estimate ET (n = 19 methods) using high resolution, multi-season eddy flux measurements from rainfed and irrigated soybean at Mead, Nebraska. Field measurements of crop growth, leaf area index (LAI), soil water content, and ET were provided to the modelers sequentially as follows: 1) phenology data for a Blind calibration; 2) irrigated crop growth; 3) irrigated daily ET and soil water; 4) rainfed ET and soil water; and 5) rainfed crop growth. Among models and ET methods, daily ET was simulated with normalized root mean square errors (nRMSE) ranging from 21.5 to 72.8 % after Full calibration, and root mean square errors (RMSE) were 0.7–2.4 mm d−1. The ensemble median across models (E-Median) reduced error in the simulation of daily ET and ranked highly across calibration steps and developmental phases. Furthermore, the E-Median showed reasonable performance under Blind calibration, with a RMSE of 0.90 mm d−1 (nRMSE= 27.7 %) for daily ET and 70.4 mm (16.7 %) for seasonal ET, indicating it can be a valuable approach for model-based ET estimation when data is scarce. This study revealed the major sources of uncertainty in simulating ET and identified... Mostrar Tudo |
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Palavras-Chave: |
AgMIP; Crop model intercomparison; CROPGRO-Soybean; Eddy covariance measurements; Modelagem; Soybean evapotranspiration. |
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Thesagro: |
Evapotranspiração; Simulação; Soja. |
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Thesaurus Nal: |
Crop models; Evapotranspiration; Soybeans. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 03181naa a2200505 a 4500
001 2180655
005 2026-01-19
008 2026 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.agrformet.2025.110882$2DOI
100 1 $aKOTHARI, K.
245 $aInter-comparison of soybean models for simulation of evapotranspiration under rainfed and irrigated conditions.$h[electronic resource]
260 $c2026
520 $aAccurate estimation of evapotranspiration (ET) is crucial for agricultural water management and crop yield prediction. Crop models are frequently used to simulate ET; however, model testing against detailed ET data remains scarce. The objective of this study was to evaluate nine soybean models that incorporated various approaches to estimate ET (n = 19 methods) using high resolution, multi-season eddy flux measurements from rainfed and irrigated soybean at Mead, Nebraska. Field measurements of crop growth, leaf area index (LAI), soil water content, and ET were provided to the modelers sequentially as follows: 1) phenology data for a Blind calibration; 2) irrigated crop growth; 3) irrigated daily ET and soil water; 4) rainfed ET and soil water; and 5) rainfed crop growth. Among models and ET methods, daily ET was simulated with normalized root mean square errors (nRMSE) ranging from 21.5 to 72.8 % after Full calibration, and root mean square errors (RMSE) were 0.7–2.4 mm d−1. The ensemble median across models (E-Median) reduced error in the simulation of daily ET and ranked highly across calibration steps and developmental phases. Furthermore, the E-Median showed reasonable performance under Blind calibration, with a RMSE of 0.90 mm d−1 (nRMSE= 27.7 %) for daily ET and 70.4 mm (16.7 %) for seasonal ET, indicating it can be a valuable approach for model-based ET estimation when data is scarce. This study revealed the major sources of uncertainty in simulating ET and identified opportunities for improving associated model processes, including 1) residue effects on soil evaporation during incomplete canopy cover, 2) potential ET of soybean, particularly during full canopy, and 3) leaf senescence effects on LAI during the late reproductive phase.
650 $aCrop models
650 $aEvapotranspiration
650 $aSoybeans
650 $aEvapotranspiração
650 $aSimulação
650 $aSoja
653 $aAgMIP
653 $aCrop model intercomparison
653 $aCROPGRO-Soybean
653 $aEddy covariance measurements
653 $aModelagem
653 $aSoybean evapotranspiration
700 1 $aSUYKER, A.
700 1 $aBATTISTI, R.
700 1 $aBOOTE, K. J.
700 1 $aARCHONTOULIS, S.
700 1 $aCONSTANTIN, J.
700 1 $aCUADRA, S. V.
700 1 $aDEBAEKE, P.
700 1 $aELLI, E. F.
700 1 $aFAYE, B.
700 1 $aFLEISHER, D.
700 1 $aGRANT, B.
700 1 $aHOOGENBOOM, G.
700 1 $aJING, Q.
700 1 $aKIMBALL, B.
700 1 $aLEUNG, F.
700 1 $aMARIN, F.
700 1 $aNENDEL, C.
700 1 $aQIAN, B.
700 1 $aSCHOVING, C.
773 $tAgricultural and Forest Meteorology$gv. 376, 110882, Jan. 2026.
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Embrapa Agricultura Digital (CNPTIA) |
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| 1. |  | ARSIC, M.; ABDALLA, A. L.; DONG, H.; LOYON, L.; PACKER, A. P.; SAHA, C. K.; SI, B.; ZILIO, D. M.; AMON, B. R. Circular bioeconomy approaches for livestock manure and post-consumer wastes: opportunities for biofertilizers and bioenergy. Animal Frontiers, v. 15, n. 4, p. 54-64, 2025.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Meio Ambiente. |
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| 2. | | GAVRILOVA, O.; LEIP, A.; DONG, H.; MACDONALD, J. D.; GOMEZ BRAVO, C. A.; AMON, B.; BARAHONA ROSALES, R.; PRADO, A. del; LIMA, M. A. de; OYHANTÇABAL, W.; WEERDEN, T. J. van der; WIDIAWATI, Y. Emissions from livestock and manure management. In: CALVO BUENDIA, E.; TANABE, K.; KRANJC, A.; BAASANSUREN, J.; FUKUDA, M.; NGARIZE, S.; OSAKO, A.; PYROSHENKO, Y. SHERMANAU, P.; FEDERICI, S. (Ed.). 2019 Refinement to the 2006 guidelines for National Greenhouse Gas Inventories. Agriculture, forestry and other land use. Geneve: IPCC, 2019. v. 4. cap. 10. p. 10.9-10.167.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Meio Ambiente. |
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| Registros recuperados : 2 | |
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