Calibration and validation of AquaCrop model for Barley in Pakdasht region -Iran

Document Type : Research Paper

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Abstract

Crop Simulation models are used for water management in farms and are widely used for optimization of water use efficiency. AquaCrop model is based on yield response to water that developed by FAO. The objective of this study was calibration of two parameters, including growing degree days from sowing to maturity (GDD) and water productivity normalized (WP) for barely in Pakdasht region, Iran. The experiments were done in 2014-2015 and the treatments were three crop calendars, including early, normal and late planting. Using calibration data and try and error method, GDD and BWP were calculated 1260 degree and 14.8 gram/m-2, respectively. The results showed that calibrated model provided close agreement with the reference values, with a coefficient determination of 0.99 and root mean square error of 0.59 ton ha-1.

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References

Allen R.G., Pereira L.S., Raes D., and Smith M. (1998). Crop evapotranspiration: guidelines for computing crop requirements, FAO Irrigation and Drainage Paper No. 56. FAO, Rome
Alizadeh, H.A., Nazari, B., Parsinejad, M., Ramezani, H., Eetedali, H.R. and Janbaz, H.R. (2010). Evaluation of AquaCrop Model on Wheat Deficit Irrigation in Karaj area. Iranian Journal of Irrigation & Drainage, 4(2), 273-283. (In Farsi)
Amiritabar, R., Rahimikhoob, A., Behbahani, M. R. (2014). Comparative study of temperature parameters and reference evapotranspiration at two weather stations located within the uncultivated and well-watered area- Case study in arid region of southeast of Tehran. J. of Water and Soil Conservation, 21(1), 253-270.
Babazadeh, H. and Sarai Tabrizi, M. (2012). Assessment of AquaCrop Model under Soybean Deficit Irrigation Management Conditions. Journal of Water and Soil, 26(2), 329-339. (In Farsi)
Araya,A., Habtu,S., Hadgu,K.M., Kebede,A., Dejene,T. (2010). Test of AquaCrop model in simulating biomass and yield of water deficit and irrigated barley. Agricultural Water Management, 97, 1838–1846.
Emamifar, S., Rahimikhoob, A. and Noroozi, A. A. (2014). An Evaluation of M5 Model Tree vs. Artificial Neural Network for Estimating Mean Air Temperature as Based on Land Surface Temperature Data by MODIS-Terra Sensor. Iranian, J. Soil and Water Research, 45(4), 423-433.
Farahani, H. J., Izzi, G., and Oweis, T.Y. (2009). Parameterization and evaluation of the AquaCrop model for full and deficit irrigated cotton. Agronomy journal, 101(3), 469-476.‌
Geerts,S and Raes,D. (2009). Deficit irrigation as on-farm strategy to maximize crop water productivity in dry areas. Agricultural Water Management, 96, 1275–1284.
Hsiao T.C., Steduto P., Raes D. & Fereres E. (2009) AquaCrop: the FAO crop water model to simulate yield response to water: III. Parameterization and testing for maize. Agricultural Journal, 101, 448-459.
Haydarinia, M., Naseri, A. A., and Broomabd-Nasab, S. (2012). Investigate the possibility of application of AquaCrop model for irrigation scheduling of sunflower in Ahwaz. Journal of Water Resources, 5(1), 39-41. (In Farsi)
Heng,L.k., Hsiao,T.C., Evett,S., Howell,T and Steduto,P. (2009). Validating the FAO AquaCrop Model for Irrigated and Water Deficient Field Maize.Agronomy Journal, 101(3), 488-498.
Iqbal, M.A., Shen, Y., Stricevic, R., Pei, H., Sun, H., Amiri, E., Penas, A. and Rio, S. (2014). Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation. Agricultural Water Management. 135, 61–72.
Kim, D. and Kaluarachchi, J. (2015). Validating FAO AquaCrop using Landsat images and regional crop information. Agricultural Water Management, 149, 143–155.
Mabhaudhi, T., Modi, A. T. and Beletse, Y. G. (2014). Parameterisation and evaluation of the FAO-AquaCrop model for a South African taro (Colocasia esculenta L. Schott) landrace. Agricultural and Forest Meteorology,  192–193, 132–139.
Liu,J., Wiberg,D., Zehnder,A and Yang,H. (2007). Modeling the role of irrigation in winter wheat yield, crop water productivity and production in china. Irrigation Science. 26, 21–23.
Nyakudya, I. W. and Stroosnijder, L. (2014). Effect of rooting depth, plant density and planting date on maize (Zea mays L.) yield and water use efficiency in semi-arid Zimbabwe: Modelling with AquaCrop. Agricultural Water Management, 146, 280–296.
Patrignani, A. and Ochsner, T.E. (2015). Canopeo: A Powerful New Tool for Measuring Fractional Green Canopy Cover. Agronomy Journal, 107(6), 2312-2320.
Pereira,L.S., Oweis,T and Zairi,A. (2002). Irrigation management under water scarcity. Agricultural Water Management. 57, 175–206.
Raes, D., Steduto, P., Hsiao, T.C. and Fereres, E. (2009). AquaCrop— the FAO crop model to simulate yield response to water II. Main algorithms and soft ware description. Agronomy Journal, 101, 438–447.
Raes, D., Steduto, P., Hsiao, T. C., and Fereres, E. (2009). AquaCrop-The FAO Crop Model to Simulate Yield Response to Water: Reference Manual Annexes.‌
Rahimikhoob, H., Sotoodehnia, A., and Massahbavani, A. R. (2014). Calibration and Evaluation of AquaCrop for Maize in Qazvin Region. Iranian Journal of lrrigation and Drainage, 8(1), 108-115.
Steduto, P., Hsiao, T.C., Raes, D. and Fereres, E. (2009). AquaCrop—the FAO Crop Model to Simulate Yield Response to Water I. Concepts and Underlying Principles. Agronomy Journal, 101, 426–437.
Soddu, A. Deidda, R., Marrocu, M., Meloni, R., Paniconi, C., Ludwig, R. Sodde, M., Mascaro, G., Perra, E. (2013). Climate variability and durum wheat adaptation using the AquaCrop model in southern Sardinia. Procedia Environmental Sciences, 19, 830 – 835
Todorovic, M., Albrizio, R., Zivotic, L., Saab, M.T.A., Stockle, C. and Steduto, P. (2009). Assessment of Aqua Crop, CropSyst, and WOFOST models in the simulation of sunflower growth under different water regimes. Journal of Agronomy, 101 (3), 509– 521.
Vanuytrecht, E., Raes, D., Steduto, P., Hsiao, T. C., Fereres, E., Heng, L. K. and Vila, M. G. (2014). AquaCrop: FAO's crop water productivity and yield response model. Environmental Modelling & Software, 62, 351–360.
 
Iranian Journal of Soil and Water Research
Volume 47, Issue 3
November 2016
Pages 539-549

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