Simulation of growth and yield and evaluation of rice production productivity under irrigation management and planting date using Aquacrop model

Subject Areas : Farm water management with the aim of improving irrigation management indicators

Pooya Aalaee Bazkiaee ¹ , ‌‌‌‌Behnam Kamkar ² , Ebrahim Amiri ³ , Hossein Kazemi ⁴ , Mojtaba Rezaei ⁵ , Soheil Akbarzadeh ⁶

1 - PhD student, Department of Agriculture, Plant production College, Gorgan University of Agricultural Sciences and Natural Resources, Iran.
2 - Prof., Agronomy Dept., Gorgan University of Agricultural Sciences and Natural Resources & Agrotechnology Dept. Faculty of Agriculture, Ferdowsi University of Mashhad, Iran.
3 - Department of Water Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran.
4 - Associate. Prof., Department of Agriculture, Plant production College, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
5 - Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran.
6 - Former undergraduate student, Department of Agriculture, Plant production College, Gorgan University of Agricultural Sciences and Natural Resources, Iran.

Received: 2019-03-13 Accepted : 2019-12-10 Published : 2020-01-21

Keywords: water productivity, Planting date, Rice, Aquacropmodel, irrigation,

Abstract :

In order to evaluate the Aquacrop model and investigate the productivity of rice production under irrigation management and planting date, a split plot experiment based on a randomized complete blocks design with three replications was carried out on a local cultivar (Hashemi) in Rice Research Institute of Iran, in Rasht during 2016-2017. Irrigation interval was considered as the main factor in four levels including full flooding, 5, 10 and 15 days irrigation intervals, and transplanting date was assigned to subplots at three levels (April, 21st, May, 11th and May, 31st). Simulated and observed values of grain yield and biological yield were evaluated based on coefficient of determination, T-test, root mean square error (RMSE), Model efficiency (EF), mean bias error (MBE) and normalized root mean square error (RMSEn). The results showed that normalized root mean square error of the grain yield and biological yield were 9% and 5%, respectively. Based on the productivity and reduction in the yield of rice, flooding irrigation was the most efficient in April, 21th planting date. According to the correlation coefficient upper than 0.7 and Model efficiency upper than 0.6, the AquaCrop model had a good accuracy in simulating grain yield and biological yield, therefore AquaCrop model can be used to support the results of experiments under irrigation management conditions and different planting dates.

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