Rice production in the world is heavily dependent on water. Therefore, increasing in water productivity with appropriate irrigation management is necessary. Simulation models that illustrate the effects of water on crop growth can apply to optimize water productivity and improve farm irrigation management. This study was conducted to simulate water productivity of paddy rice using AquaCrop model in both humid and semiarid regions of Iran. Required data for running model were gained from two field experiments: an experiment with a lowland local rice cultivar named Champa-Kamfiroozi in a semiarid climate (Kooshkak), and other experiment with two lowland local rice cultivars named Binam and Hasani in a humid climate (Rasht). Both experiments were conducted under five irrigation treatments in two consecutive years. As a result, the relative root mean square error (RRMSE) of grain yield simulation was gained between 2.28 and 15.09%. The ranges of water productivity based on transpiration (WP_T) and water productivity based on evapotranspiration (WP_ET) as affected by irrigation treatments, in dry climate were greater than wet climate. The averages of WP_T and WP_ET for continuous flooding in the humid (1.21 and 0.82 kg m⁻³, respectively) and dry (1.26 and 0.76 kg m⁻³, respectively) climates showed the role of evaporation losses in decreasing WP in dry climate. The highest ET was obtained in continuous flooding treatments that the amount of evaporation for dry climate was 88% higher than humid climate.

中文翻译：

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使用AquaCrop模型在伊朗潮湿和半干旱地区模拟灌溉制度下的水稻水分生产率

世界上的大米生产严重依赖水。因此，有必要通过适当的灌溉管理提高水生产率。说明水对作物生长的影响的仿真模型可用于优化水生产率和改善农场灌溉管理。这项研究是使用AquaCrop模型在伊朗潮湿和半干旱地区模拟水稻的水分生产率的。运行模型所需的数据来自两个田间试验：在半干旱气候下（Kooshkak）对一个名为Champa-Kamfiroozi的低地本地水稻品种进行的实验，以及对一个名为Binam和Hasani的两个低地本地水稻品种进行的其他实验。在潮湿的气候（拉什特）。连续两年在五个灌溉处理下进行了两个实验。结果，谷物产量模拟的相对均方根误差（RRMSE）在2.28％至15.09％之间。在干旱气候下，基于蒸腾作用的水分生产率（WP _T）和基于蒸散作用的水分生产率（WP _ET）的范围大于干旱气候。在潮湿（分别为1.21和0.82 kg m ^-3）和干燥（1.26和0.76 kg m ^-3）下连续浸水的WP _T和WP _ET平均值，）气候显示了蒸发损失在干燥气候下降低WP的作用。在连续驱油处理中获得最高的ET，干燥气候下的蒸发量比潮湿气候高88％。