Using the AquaCrop model to assess the cotton yield response to three irrigation schedules in the Río Dulce Irrigation System, Santiago del Estero, Argentina




irrigation, cotton, yields, AquaCrop, Argentina


This work evaluates the cotton response to irrigation scheduling using AquaCrop, in the Río Dulce Irrigation System (SRRD), Santiago del Estero, Argentina. The model was calibrated and validated to simulate the cotton´s growth and yield for the SRRD, where most of the cotton is grown in a cropping system called narrow rows (0.52 to 0.76 meter between rows, 200,000 to 220,000 plants per hectare). The model adaptation to different cultivars and agronomical practices was noteworthy. Then, the impact of three different irrigation schedules on cotton production was assessed using a series of 35 years of daily climatic data. The irrigation scenarios were defined based on the farmers’ practices and on the rotational water delivery of the SRRD. The highest yields were attained when irrigation was applied at 25 and 55 days after sowing (DAS), followed by 55 DAS, and, finally, 55 and 85 DAS. Considering both the yields and the water use, irrigating at 25 and 55 DAS would be the best option for a normal season in the SRRD. This work shows the usefulness of combining the use of crop simulation models, field measurements and long-term weather data to analyze yield trends and irrigation water use under different scenarios.


Download data is not yet available.


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:

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:

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:

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.




How to Cite

Angella GA, Prieto Angueira S, Fereres E, García-Vila M, Prieto DR. Using the AquaCrop model to assess the cotton yield response to three irrigation schedules in the Río Dulce Irrigation System, Santiago del Estero, Argentina. Agrocienc Urug [Internet]. 2024 Feb. 6 [cited 2024 Apr. 24];27(NE1):e1197. Available from:



Irrigation and water management
QR Code


Article metrics
Abstract views
Galley vies
PDF Views
HTML views
Other views