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Registro Completo |
Biblioteca(s): |
Embrapa Clima Temperado; Embrapa Meio Ambiente. |
Data corrente: |
02/12/2011 |
Data da última atualização: |
28/10/2014 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
CUADRA, S. V.; COSTA, M. H.; KUCHARIK, C. J.; ROCHA, H. R. da; TATSCH, J. D.; INMAN-BAMBER, G.; ROCHA, R. P. da; LEITE, C. C.; CABRAL, O. M. R. |
Afiliação: |
SANTIAGO VIANNA CUADRA, CPACT; M. H. COSTA; C. J. KUCHARIK; H. R. DA ROCHA; J. D. TATSCH; G . INMAN-BAMBER; R. P. DA ROCHA; C. C . L E I T E; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA. |
Título: |
A biophysical model of Sugarcane growth. |
Ano de publicação: |
2012 |
Fonte/Imprenta: |
Global Change Biology. Bioenergy, v. 4, n. 1, p. 36-48, 2012. |
Idioma: |
Inglês |
Conteúdo: |
Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in cropbased biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/ overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and kE, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and ?12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sa?o Paulo, Brazil, over a period of 16 years, with a yield relative bias of 0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields. |
Palavras-Chave: |
Biophysical; Cana-de-açúcar; Ciclos biogeoquímicos; Land surface model; Sugarcane model. |
Thesagro: |
Biocombustível; Impacto ambiental. |
Thesaurus Nal: |
Biofuels; Climate change; Sugarcane. |
Categoria do assunto: |
-- P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02371naa a2200337 a 4500 001 1940240 005 2014-10-28 008 2012 bl uuuu u00u1 u #d 100 1 $aCUADRA, S. V. 245 $aA biophysical model of Sugarcane growth.$h[electronic resource] 260 $c2012 520 $aScientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in cropbased biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/ overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and kE, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and ?12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sa?o Paulo, Brazil, over a period of 16 years, with a yield relative bias of 0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields. 650 $aBiofuels 650 $aClimate change 650 $aSugarcane 650 $aBiocombustível 650 $aImpacto ambiental 653 $aBiophysical 653 $aCana-de-açúcar 653 $aCiclos biogeoquímicos 653 $aLand surface model 653 $aSugarcane model 700 1 $aCOSTA, M. H. 700 1 $aKUCHARIK, C. J. 700 1 $aROCHA, H. R. da 700 1 $aTATSCH, J. D. 700 1 $aINMAN-BAMBER, G. 700 1 $aROCHA, R. P. da 700 1 $aLEITE, C. C. 700 1 $aCABRAL, O. M. R. 773 $tGlobal Change Biology. Bioenergy$gv. 4, n. 1, p. 36-48, 2012.
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