Simulating the Production of Rice Genotypes by Flood Management and End-Season Water Stress Conditions Using AquaCrop Model

Abstract

ABSTRACT The present study was conducted to assess the ability of AquaCrop model in predicting of grain and biological yield of rice genotypes in water management. A two-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran from 2016 to 2017. The experiment was established in a split-plot design with two irrigation management (continuous submergence and end season water stress) as the main plot, fourth rice genotypes as the sub-plot and three replications. The goodness-of-fit between observed and simulated grain yield and final biomass was assessed by means of the coefficient of determination (R 2), the absolute and normalized root mean square errors (RMSE). The RMSEn of predicting grain yield at calibration and evaluation stages was in the range of 6–12% and 6–8% for biological yield. The results indicated that AquaCrop model is suitable to predict grain yield and biological yield of rice genotypes in northern Iran. AquaCrop model can be used to determine optimization strategies to improve the water consumption of rice genotypes.