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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
06/03/2025 |
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Data da última atualização: |
06/03/2025 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SILVA, E. H. F. M. da; KOTHARI, K.; PATTEY, E.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S. V.; CUADRA, S. V.; FAYE, B.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; MARIN, F. R.; NENDEL, C.; QIAN, B.; SMITH, W.; SRIVASTAVA, A. K.; THORP, K. R.; VIEIRA JUNIOR, N. A.; SALMERÓN, M. |
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Afiliação: |
EVANDRO H. FIGUEIREDO MOURA DA SILVA, UNIVERSIDADE DE SÃO PAULO; KRITIKA KOTHARI, UNIVERSITY OF KENTUCKY, INDIAN INSTITUTE OF TECHNOLOGY ROORKEE; ELIZABETH PATTEY, AGRICULTURE AND AGRI-FOOD CANADA; RAFAEL BATTISTI, UNIVERSIDADE FEDERAL DE GOIÁS; KENNETH J. BOOTE, UNIVERSITY OF FLORIDA; SOTIRIOS V. ARCHONTOULIS, IOWA STATE UNIVERSITY; SANTIAGO VIANNA CUADRA, CNPTIA; BABACAR FAYE, UNIVERSITÉ DU SINE SALOUM EL-HADJ IBRAHIMA NIA; BRIAN GRANT, AGRICULTURE AND AGRI-FOOD CANADA; GERRIT HOOGENBOOM, UNIVERSITY OF FLORIDA; QI JING, AGRICULTURE AND AGRI-FOOD CANADA; FÁBIO R. MARIN, UNIVERSIDADE DE SÃO PAULO; CLAAS NENDEL, UNIVERSITY OF POTSDAM, LEIBNIZ CENTRE FOR AGRICULTURAL LANDSCAPE RESEARCH; BUDONG QIAN, AGRICULTURE AND AGRI-FOOD CANADA; WARD SMITH, AGRICULTURE AND AGRI-FOOD CANADA; AMIT KUMAR SRIVASTAVA, LEIBNIZ CENTRE FOR AGRICULTURAL LANDSCAPE RESEARCH, UNIVERSITY OF BONN; KELLY R. THORP, UNITED STATES DEPARTMENT OF AGRICULTURE; NILSON A. VIEIRA JUNIOR, WAGENINGEN UNIVERSITY & RESEARCH; MONTSERRAT SALMERÓN, UNIVERSITY OF KENTUCKY. |
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Título: |
Inter-comparison of soybean models for the simulation of evapotranspiration in a humid continental climate. |
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Ano de publicação: |
2025 |
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Fonte/Imprenta: |
Agricultural and Forest Meteorology, v. 365, 110463, Apr. 2025. |
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ISSN: |
0168-1923 |
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DOI: |
https://doi.org/10.1016/j.agrformet.2025.110463 |
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Idioma: |
Inglês |
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Conteúdo: |
Accurate simulation of evapotranspiration (ET) with crop models is essential for improving agricultural water management and yield forecasting. Few studies have evaluated multiple soybean [Glycine max (L.) Merr.] models for simulating ET under conditions of low evaporative demand that is characteristic for a warm-summer humid continental climate. Six soybean crop models, encompassing 15 different modeling approaches, were evaluated for ET simulation and compared against eddy covariance data collected over five growing seasons in Ottawa, Canada. Models were first calibrated with phenology, in-season growth, and yield data, followed by calibration with measured ET and soil water content (SWC) data during the second step. After initial calibration, simulated daily ET was higher on average than measured ET, particularly during full canopy cover (normalized bias, nBias = 17.1 to 49.2% depending on the model). Following the second calibration, simulated daily ET was closer to measured values, but bias remained (nBias = 5.9 to 52.1% during full canopy). The ensemble median reduced uncertainty in the simulation of daily ET compared to most models, but DNDC remained the top-ranking model (nRMSE = 0.7 mm d-1, nBias = 11.2%). The MONICA model was most accurate simulating cumulative ET (RMSE = 39.9 mm, nBias = 11.3%), whereas the CROPGRO models excelled simulating SWC (RMSE= 0.04 to 0.05 m³ m-3, nBias = 0.10 to 0.9% depending on soil depth). This study was instrumental in evaluating the best ET methodologies and parameters in soybean models. However, there was bias across the models compared to measured eddy covariance ET in a humid environment. The results reveal the need to further investigate possible biases in ET estimates by eddy covariance over soybean canopies, and to review the role of night-time dew contributions to ET in process-based models. MenosAccurate simulation of evapotranspiration (ET) with crop models is essential for improving agricultural water management and yield forecasting. Few studies have evaluated multiple soybean [Glycine max (L.) Merr.] models for simulating ET under conditions of low evaporative demand that is characteristic for a warm-summer humid continental climate. Six soybean crop models, encompassing 15 different modeling approaches, were evaluated for ET simulation and compared against eddy covariance data collected over five growing seasons in Ottawa, Canada. Models were first calibrated with phenology, in-season growth, and yield data, followed by calibration with measured ET and soil water content (SWC) data during the second step. After initial calibration, simulated daily ET was higher on average than measured ET, particularly during full canopy cover (normalized bias, nBias = 17.1 to 49.2% depending on the model). Following the second calibration, simulated daily ET was closer to measured values, but bias remained (nBias = 5.9 to 52.1% during full canopy). The ensemble median reduced uncertainty in the simulation of daily ET compared to most models, but DNDC remained the top-ranking model (nRMSE = 0.7 mm d-1, nBias = 11.2%). The MONICA model was most accurate simulating cumulative ET (RMSE = 39.9 mm, nBias = 11.3%), whereas the CROPGRO models excelled simulating SWC (RMSE= 0.04 to 0.05 m³ m-3, nBias = 0.10 to 0.9% depending on soil depth). This study was instrumental in evaluating the... Mostrar Tudo |
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Palavras-Chave: |
Covariância eddy; Crop transpiration; Evaporação da água do solo; FAO-56 Penman-Monteith; Priestley-Taylor; Soil water evaporation; Transpiração; Uso da água; Water use. |
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Thesagro: |
Glycine Max. |
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Thesaurus Nal: |
Eddy covariance. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 03288naa a2200493 a 4500
001 2173621
005 2025-03-06
008 2025 bl uuuu u00u1 u #d
022 $a0168-1923
024 7 $ahttps://doi.org/10.1016/j.agrformet.2025.110463$2DOI
100 1 $aSILVA, E. H. F. M. da
245 $aInter-comparison of soybean models for the simulation of evapotranspiration in a humid continental climate.$h[electronic resource]
260 $c2025
520 $aAccurate simulation of evapotranspiration (ET) with crop models is essential for improving agricultural water management and yield forecasting. Few studies have evaluated multiple soybean [Glycine max (L.) Merr.] models for simulating ET under conditions of low evaporative demand that is characteristic for a warm-summer humid continental climate. Six soybean crop models, encompassing 15 different modeling approaches, were evaluated for ET simulation and compared against eddy covariance data collected over five growing seasons in Ottawa, Canada. Models were first calibrated with phenology, in-season growth, and yield data, followed by calibration with measured ET and soil water content (SWC) data during the second step. After initial calibration, simulated daily ET was higher on average than measured ET, particularly during full canopy cover (normalized bias, nBias = 17.1 to 49.2% depending on the model). Following the second calibration, simulated daily ET was closer to measured values, but bias remained (nBias = 5.9 to 52.1% during full canopy). The ensemble median reduced uncertainty in the simulation of daily ET compared to most models, but DNDC remained the top-ranking model (nRMSE = 0.7 mm d-1, nBias = 11.2%). The MONICA model was most accurate simulating cumulative ET (RMSE = 39.9 mm, nBias = 11.3%), whereas the CROPGRO models excelled simulating SWC (RMSE= 0.04 to 0.05 m³ m-3, nBias = 0.10 to 0.9% depending on soil depth). This study was instrumental in evaluating the best ET methodologies and parameters in soybean models. However, there was bias across the models compared to measured eddy covariance ET in a humid environment. The results reveal the need to further investigate possible biases in ET estimates by eddy covariance over soybean canopies, and to review the role of night-time dew contributions to ET in process-based models.
650 $aEddy covariance
650 $aGlycine Max
653 $aCovariância eddy
653 $aCrop transpiration
653 $aEvaporação da água do solo
653 $aFAO-56 Penman-Monteith
653 $aPriestley-Taylor
653 $aSoil water evaporation
653 $aTranspiração
653 $aUso da água
653 $aWater use
700 1 $aKOTHARI, K.
700 1 $aPATTEY, E.
700 1 $aBATTISTI, R.
700 1 $aBOOTE, K. J.
700 1 $aARCHONTOULIS, S. V.
700 1 $aCUADRA, S. V.
700 1 $aFAYE, B.
700 1 $aGRANT, B.
700 1 $aHOOGENBOOM, G.
700 1 $aJING, Q.
700 1 $aMARIN, F. R.
700 1 $aNENDEL, C.
700 1 $aQIAN, B.
700 1 $aSMITH, W.
700 1 $aSRIVASTAVA, A. K.
700 1 $aTHORP, K. R.
700 1 $aVIEIRA JUNIOR, N. A.
700 1 $aSALMERÓN, M.
773 $tAgricultural and Forest Meteorology$gv. 365, 110463, Apr. 2025.
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