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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
06/01/2022 |
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Data da última atualização: |
13/03/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MENEZES, C. T.; CASAROLI, D.; HEINEMANN, A. B.; MOSCHETTI, V. C.; BATTISTI, R. |
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Afiliação: |
CAIO TEODORO MENEZES, UFG; DERBLAI CASAROLI, UFG; ALEXANDRE BRYAN HEINEMANN, CNPAF; VINICIUS CINTRA MOSCHETTI; RAFAEL BATTISTI, UFG. |
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Título: |
The impact of gridded weather database on soil water availability in rice crop modeling. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Theoretical and Applied Climatology, v. 147, p. 1401-1414, 2022. |
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ISSN: |
1434-4483 |
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DOI: |
https://doi.org/10.1007/s00704-021-03906-4 |
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Idioma: |
Inglês |
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Conteúdo: |
In recent years, there has been an increase in studies suggesting that gridded weather database (GWD) is a suitable source for simulating crop yield. Brazil has low geospatial coverage by measured weather database (MWD). Based on that, this study aimed to compare two different GWD sources, Daily Gridded (DG) and NASA/POWER (NP), on the simulated yield of upland rice (UR) against the MWD input. The GWD and MWD were obtained for seven locations across UR Brazilian region, considering a period ranging from 1984 to 2016. GWD and MWD were used to estimate rice potential (Yp) and attainable yield (Ya), in clay soil and sandy soil, using the ORYZA (v3) model. DG had the best performance for all variables. GWD-based yields had a reasonable performance. However, DG had a slightly better performance than NP in all conditions, DG-based yields showed RMSE values of 0.57, 0.71, and 0.52 for Yp and Ya in clay and sandy soil, and NP showed RMSE values of 0.86, 0.91, and 0.64. DG also showed higher R2 and d values for yields assessed. Both GWD overestimated Ya; these overestimations in DG-based yield were 3.54, 9.61, and 21.35% for Yp and Ya in clay and sandy soil, respectively, in NP-based yield were 13.67, 18.45, 29.11%, showing that for both GWD-based yield increased as the soil type texture as well as water storage decreased. As a consequence, we do not recommend the use of precipitation data in daily time-step crop modeling. |
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Palavras-Chave: |
Daily Gridded ·; NASA/POWER; Virtual weather station. |
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Thesagro: |
Arroz; Modelo de Simulação. |
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Thesaurus Nal: |
Crop models; Oryza. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02261naa a2200277 a 4500
001 2138838
005 2023-03-13
008 2022 bl uuuu u00u1 u #d
022 $a1434-4483
024 7 $ahttps://doi.org/10.1007/s00704-021-03906-4$2DOI
100 1 $aMENEZES, C. T.
245 $aThe impact of gridded weather database on soil water availability in rice crop modeling.$h[electronic resource]
260 $c2022
520 $aIn recent years, there has been an increase in studies suggesting that gridded weather database (GWD) is a suitable source for simulating crop yield. Brazil has low geospatial coverage by measured weather database (MWD). Based on that, this study aimed to compare two different GWD sources, Daily Gridded (DG) and NASA/POWER (NP), on the simulated yield of upland rice (UR) against the MWD input. The GWD and MWD were obtained for seven locations across UR Brazilian region, considering a period ranging from 1984 to 2016. GWD and MWD were used to estimate rice potential (Yp) and attainable yield (Ya), in clay soil and sandy soil, using the ORYZA (v3) model. DG had the best performance for all variables. GWD-based yields had a reasonable performance. However, DG had a slightly better performance than NP in all conditions, DG-based yields showed RMSE values of 0.57, 0.71, and 0.52 for Yp and Ya in clay and sandy soil, and NP showed RMSE values of 0.86, 0.91, and 0.64. DG also showed higher R2 and d values for yields assessed. Both GWD overestimated Ya; these overestimations in DG-based yield were 3.54, 9.61, and 21.35% for Yp and Ya in clay and sandy soil, respectively, in NP-based yield were 13.67, 18.45, 29.11%, showing that for both GWD-based yield increased as the soil type texture as well as water storage decreased. As a consequence, we do not recommend the use of precipitation data in daily time-step crop modeling.
650 $aCrop models
650 $aOryza
650 $aArroz
650 $aModelo de Simulação
653 $aDaily Gridded ·
653 $aNASA/POWER
653 $aVirtual weather station
700 1 $aCASAROLI, D.
700 1 $aHEINEMANN, A. B.
700 1 $aMOSCHETTI, V. C.
700 1 $aBATTISTI, R.
773 $tTheoretical and Applied Climatology$gv. 147, p. 1401-1414, 2022.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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