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Application of AquaCrop model for maize under water and nitrogen managements in a humid environment

机译:AquaCrop模型在潮湿环境中水和氮管理下在玉米中的应用

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Globally, it is well debated fact that the water productivity in agriculture needs to be raised in order to meet the increasing demand for the feed and food production, which will double by 2050. Simulation models have been developed for predicting the effects of soil, water and nutrients on growth and water productivity of different crops. In this study, AquaCrop model was calibrated for grain maize (Single Cross 260) using drip irrigation system under varying irrigation and nitrogen levels. The intervals of irrigation were 6 days (F1), 12 days (F2) and 18 days (F3) which combined with different nitrogen levels of 0 (N1), 120 (N2), 180 (N3) and 240 kg ha-1. Root Mean Square Error (RMSE), normalized Root Mean Square Error (RMSEn), Mean Absolute Error (MAE), Prediction error (Pe) and coefficient of determination (R2) were used to test the model performance. The model was calibrated for simulating maize grain and biomass yield for all treatment levels with the prediction error 0.372-1. The results of the study showed that the AquaCrop model simulated aboveground biomass and grain yield in normal conditions more accurately than moderate and severe water stress conditions.
机译:在全球范围内,一个有争议的事实是,为了满足对饲料和粮食生产不断增长的需求,需要提高农业的水生产率,到2050年,这将翻一番。已经开发了模拟模型来预测土壤,水的影响和营养对不同作物的生长和水分生产力的影响。在这项研究中,使用滴灌系统在变化的灌溉水平和氮水平下,针对谷物玉米(Single Cross 260)对AquaCrop模型进行了校准。灌溉间隔为6天(F 1 ),12天(F 2 )和18天(F 3 ),不同灌溉时间相结合。氮水平为0(N 1 ),120(N 2 ),180(N 3 )和240 kg ha -1 。均方根误差(RMSE),归一化均方根误差(RMSE n ),均方根绝对误差(MAE),预测误差(Pe)和确定系数(R 2 )来测试模型性能。对该模型进行校正,以模拟所有处理水平下的玉米籽粒和生物量产量,预测误差为0.372 -1 。研究结果表明,与中度和重度水分胁迫条件相比,AquaCrop模型在正常条件下模拟地上生物量和谷物产量更为准确。

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