Uso do modelo AquaCrop para avaliar a resposta da produtividade do algodão a três programas de irrigação no Sistema de Irrigação Rio Dulce, Santiago del Estero, Argentina

Autores

DOI:

https://doi.org/10.31285/AGRO.27.1197

Palavras-chave:

irrigação, algodão, produtividade, AquaCrop, Argentina

Resumo

Esse trabalho avaliou a resposta do algodoeiro ao manejo da irrigação com AquaCrop, no Sistema de Irrigação Río Dulce (SRRD), Santiago del Estero, Argentina. O modelo foi calibrado e validado para simular o crescimento e rendimento do algodão para o SRRD, onde é cultivado em um sistema de cultivo denominado “linha estreita” (0,52 a 0,76 metros entre linhas, 200,000 a 220,000 plantas por hectare). Destacou-se a adaptação do modelo a diferentes cultivares e práticas agronômicas. Logo, avaliou-se o impacto de três programas de irrigação no rendimento de algodão utilizando 35 anos de dados climáticos diários. Os cenários de irrigação foram definidos considerando as práticas dos agricultores e a metodologia de entrega de água do SRRD. As maiores produtividades foram obtidas quando irrigadas aos 25 e 55 dias após a semeadura (DAS), seguida de 55 DAS e, finalmente, 55 e 85 DAS. Irrigar aos 25 e 55 DAS foi a a melhor opção em um ano con chuvas médias. Esse trabalho mostra a utilidade de combinar o uso de modelos de simulação, medições de campo e dados meteorológicos de longo prazo para analisar tendências de rendimentos e o uso de água de irrigação em diferentes cenários.

Downloads

Não há dados estatísticos.

Referências

Abedinpour M, Sarangi A, Rajput T, Singh M.Prediction of maize yield under future water availability scenarios using the AquaCrop model. J Agric Sci. 2014;152:558-74. Doi: 10.1017/S0021859614000094.

AllenRG, PereiraLS, RaesD, SmithM.Crop evapotranspiration:guidelines for computing crop water requirements.Rome: FAO; 2006. 322p.

Angella G. Sistema de Riego del Río Dulce, Santiago del Estero, Argentina:brecha de rendimientos y productividad del agua en los cultivos de maíz y algodón[doctoral’s thesis on Internet].Códoba(ES): Universidad de Córdoba; 2015 [cited 2023 Nov 28]. 134p. Available from: http://hdl.handle.net/10396/13217

Angella G, García-Vila M, López JM, Barraza G, Salgado R, Prieto Angueira S, Tomsic P, Fereres E. Quantifying yield and water productivity gaps in an irrigation district under rotational delivery Schedule. Irrig Sci. 2016:34:71-83.Doi: 10.1007/s00271-015-0486-0.

Angella G, Urbina Urbina L, García C, Garay R, Frías C. Sistema de asesoramiento al regante (SAR): ¿Cuándo regar y cuánto regar? Las tecnologías de la información y comunicación (TICs) como herramientas para fortalecer la capacidad de la toma de decisiones de la agricultura familiar:Producto 1. Informe técnico del diagnóstico inicial de las áreas de estudio [Internet]. [place unknown]: FONTAGRO; 2022 [cited 2023 Nov 28]. 39p. Available from: https://bit.ly/3uuxazE

Baker DN, Larnbert JN,McKinionJM.GOSSYM: a simulator of cotton growth and yield. Clemson:South Carolina Agricultural Experiment Station; 1983. 135p.

Boogaard HL, Van Diepen CA, Rötter RP, Cabrera JMCA, Van Laar HH.User's guide for the WOFOST 7.1 crop growth simulation model and WOFOST control center 1.5. Wageningen: Winand Staring Centre; 1998. 144p.

Constable GA, BangeMP. The yield potential of cotton (Gossypium Hirsutum L). Field Crops Res. 2015;182:98-106. Doi: 10.1016/j.fcr.2015.07.017.

Farahani HJ, IzziG, Oweis T. Parameterization and evaluation of the AquaCrop Model for full and deficit irrigated cotton.Agron J. 2009;101:469-76. Doi: 10.2134/agronj2008.0182s.

García-Vila M, Fereres E, Mateos L, Orgaz F, Steduto P.Deficit irrigation optimization of cotton with AquaCrop. Agron J. 2009;101:477-87.

Gowda P, Sunil A, Satyareddy S, Manjunath B. Crop growth modeling: a review. Res Rev J Agric Allied Sci [Internet]. 2013 [cited 2023 Nov 28];2:11p. Available from: https://www.rroij.com/open-access/crop-growth-modeling-a-review.php?aid=33776

Greaves G, Wang Y-M. Assessment of FAO AquaCrop Model for simulating maize growth and productivity under deficit irrigation in a tropical environment. Water. 2016;8:557. Doi: 10.3390/w8120557.

Heidariniya M, NaseriA, BoroumandnasabS, Sohrabi MoshkabadiB, NasrolahiAH.Evaluation of AquaCrop model application in irrigation management of Cotton. World Rural Observ. 2012;4(2):55-9.

Heng L, Hsiao T, Evett S, Howell T, Steduto P. Validating the FAO AquaCrop Model for irrigated and water deficient field maize. Agron J. 2009;101:488-98. Doi: 10.2134/agronj2008.0029xs.

Hsiao TC, Heng L, Steduto P, Rojas Lara B, Raes D, Fereres E. AquaCrop-the FAO crop model to simulate yield response to water: III. parameterization and testing for maize. Agron J. 2009;101:448-59. Doi: 10.2134/agronj2008.0218s.

Iqbal MA, Shena Y, Stricevic R, Pei H, Suna H, Amiri E, Penas A, del Rio S. Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation. Agric Water Manag. 2014;135:61-72.

Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT. The DSSAT cropping system model. Eur J Agron. 2003;18:235-65. Doi: 10.1016/S1161-0301(02)00107-7.

Kale S. Assessment of AquaCrop model in the simulation of wheat growth under different water regimes. Sci Papers Ser A Agron. 2016;59:308-14.

Kumar P, Sarangi A, Singh D, Parihar S. Evaluation of AquaCrop Model in predicting wheat yield and water productivity under irrigated saline regimes. IrrigDrain. 2014;63:474-87. Doi: 10.1002/ird.1841.

Li F, Yu D, Zhao Y. Irrigation scheduling optimization for cotton based on the AquaCrop Model. Water Resour Manag. 2019;33:39-55. Doi: 10.1007/s11269-018-2087-1.

Linker R, IoslovichI, SylaiosG, PlauborgF, BattilaniA.Optimal model-based deficit irrigation scheduling using AquaCrop: a simulation study with cotton, potato and tomato. Agric Water Manag. 2016;163:236-43. Doi: 10.1016/j.agwat.2015.09.011.

Linker R, Sylaios G, Tsakmakis I. Optimal irrigation of cotton in northern Greece using AquaCrop: a multi-year simulation study. In: Stafford JV, editor. Precision agriculture '15. Wageningen: Wageningen Academic Publishers; 2015.pp. 717-24. Doi: 10.3920/978-90-8686-814-8_89.

Liu J, Pattey E, Admiral S.Assessment of in situ crop LAI measurement using unidirectional view digital photography. Agric For Meteorol. 2012;169:25-34.

Masasi B, Taghvaeian S, Gowda PH, Marek G, Boman R.Validation and application of AquaCrop for irrigated cotton in the Southern Great Plains of US. Irrig Sci. 2020;38:593-607. Doi: 10.1007/s00271-020-00665-4.

Mebane VJ, Day RL, Hamlett JM, Watson JE, Roth GW. Validating the FAO AquaCrop Model for rainfed maize in Pennsylvania. Agron J. 2013;105:419-27. Doi: 10.2134/agronj2012.0337.

Mondino M, Peterlin O, Garay F, Gómez N. La producción en surcos estrechos y ultra-estrechos: un cambio de paradigma en el cultivo de algodón. In: Albanesi A, Paz R, Sobrero MT, Helman S, Rodríguez S, editors. Hacia la construcción del desarrollo agropecuario y agroindustrial: de la FAyA al NOA. Tucumán: Magna; 2013. pp. 21-40.

Paredes P, de Melo-Abreu JP, Alves I, Pereira LS. Assessing the performance of the FAO AquaCrop model to estimate maize yields and water use under full and deficit irrigation with focus on model parameterization. Agric Water Manag.2014;144:81-97.Doi: 10.1016/j.agwat.2014.06.002.

Perry C, Barnes E. Cotton irrigation management for humid regions. [place unknown]:Cotton Incorporated; 2012. 63p.

Prieto D, AngueiraC.Water stress effect on different growing stages for cotton and its influence on yield reduction. In: Kirda C, Moutonnet P, Hera C, NielsenDR, editors. Crop yield response to deficit irrigation. Dordrecht: Kluwer Academic Publishers; 1996. pp. 13-32.

Prieto Angueira S, Prieto Garra D, Angella G. Evaluación de diferentes estrategias de riego deficitario controlado en el cultivo de algodón (Gossypium hirsutum). In: XXV Congreso Nacional del Agua;15 al 19 de junio de 2015;Paraná, Entre Ríos, Argentina. Paraná: Asociación Internacional de Hidrogeólogos; 2015. pp. 219.

Qiao X. Parameterization of FAO AquaCrop Model for irrigated cotton in the Humid Southeast USA[master’s thesis]. Clemson (US): Clemson University, Graduate School; 2012. 127p.

Qiao X, Farahani H, Khalilian A, Barnes E. Cotton water productivity and growth parameters in the humid southeast: Experimentation and modeling. Trans ASABE. 2016;59(3):949-62.Doi: 10.13031/trans.59.11601.

Raes D, StedutoP, HsiaoT, FereresE.AquaCrop Version 6.0-6.1:reference manual. Rome: FAO; 2018. 85p.

Ritchie JT, GodwinDC, Otter-NackeS. CERES-Wheat:a simulation model of wheat growth and development. Texas:Texas A&M University Press; 1985.

Shrestha N, Raes D, Kumar S. Strategies to improve cereal production in the Terai region (Nepal) during dry season: simulations with aquacrop. Procedia Environ Sci. 2013;19:767-75. Doi: 10.1016/j.proenv.2013.06.085.

Steduto P, Hsiao TC, Fereres E, Raes D. Crop yield response to water. Rome: FAO; 2012. 510p.

Steduto P, Hsiao TC, Raes D, Fereres E. AquaCrop-the FAO crop model to simulate yield response to water: I. concepts and underlying principles. Agron J. 2009;101:426-37. Doi: 10.2134/agronj2008.0139s.

Stockle C, Donatelli M, Nelson R. CropSyst, a cropping systems simulation model. Eur J Agron. 2003;18:289-307. Doi: 10.1016/S1161-0301(02)00109-0.

Tan S, WangQ, ZhangJ, ChenY, ShanY, XuD. Performance of AquaCrop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China. Agric Water Manag. 2018;196:99-113.

Ünlü M, Kanber R, Levent Koc D, Tekin S, Kapur B. Effects of deficit irrigation on the yield and yield components of drip irrigated cotton in a mediterranean environment. Agric Water Manag.2011;98:597-605. Doi: 10.1016/j.agwat.2010.10.020.

Voloudakis D,Karamanos A, Economou G, Kalivas D, Vahamidis P, Kotoulas V, Kapsomenakis J, Zerefos C. Prediction of climate change impacts on cotton yields in Greece under eight climatic models using the AquaCrop crop simulation model and discriminant function analysis. Agric Water Manag. 2015;147:116-28. Doi: 10.1016/j.agwat.2014.07.028.

Wang E, Robertson MJ, Hammer GL, Carberry PS, Holzworth D, Meinke H, Chapman SC, Hargreaves JNG, Huth NI, McLean G.Development of a generic crop model template in the cropping system model APSIM. Eur J Agron. 2002;18:121-40. Doi: 10.1016/S1161-0301(02)00100-4.

Willmott CJ. Some comments on the evaluation of model performance. Bull Am Meteorol Soc. 1982;63:1309-13.

Downloads

Publicado

2024-02-06

Como Citar

1.
Angella GA, Prieto Angueira S, Fereres E, García-Vila M, Prieto DR. Uso do modelo AquaCrop para avaliar a resposta da produtividade do algodão a três programas de irrigação no Sistema de Irrigação Rio Dulce, Santiago del Estero, Argentina. Agrocienc Urug [Internet]. 6º de fevereiro de 2024 [citado 6º de julho de 2024];27(NE1):e1197. Disponível em: http://mail.revista.asocolderma.org.co/index.php/agrociencia/article/view/1197

Edição

Seção

Irrigation and water management
QR Code

Métricas

Métricas do artigo
Vistas abstratas
Visualizações da cozinha
Visualizações de PDF
Visualizações em HTML
Outras visualizações