李 兴, 勾芒芒, 程满金, 王 勇. 集雨补灌条件下的玉米作物-水模型[J]. 农业工程学报, 2010, 26(8): 80-84.
    引用本文: 李 兴, 勾芒芒, 程满金, 王 勇. 集雨补灌条件下的玉米作物-水模型[J]. 农业工程学报, 2010, 26(8): 80-84.
    Maize crop-water model under condition of supplemental irrigation with harvested rainwater[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(8): 80-84.
    Citation: Maize crop-water model under condition of supplemental irrigation with harvested rainwater[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(8): 80-84.

    集雨补灌条件下的玉米作物-水模型

    Maize crop-water model under condition of supplemental irrigation with harvested rainwater

    • 摘要: 黄土高原半干旱区生态环境恶劣、水土流失严重、年内降雨分配极不平衡,集雨蓄水工程收集的雨水十分有限,每次补灌量仅为18 mm。为探讨集雨补灌条件下,各生育期补充灌溉对产量的影响程度,找出玉米需水敏感期,该文建立了集雨补灌条件下能够反映产量和阶段水分关系的数学模型。该模型以ETmin/ETa为相对腾发量(以Jensen模型为基础进行了变形),采用相对产量和相对腾发量可以消除部分因素对模型的影响,因此,以相对腾发量和相对产量作为BP神经网络的输入样本和输出样本,经过反复训练分析比较,建立了基于集雨补灌条件下的BP神经网络作物-水模型,并用实测值和变形的Jensen模型与其进行了验证比较。结果表明:该模型模拟精度明显高于变形的Jensen模型,且能够反映出玉米各生育阶段需水的敏感程度并能较好地预测集雨补灌条件下的玉米产量。同时,也探讨了模型存在的问题和不足。

       

      Abstract: There are some ecological problems in semi-arid areas of the Loess Plateau,such as abominable ecological environment, heavy soil and water loss,unbalanced annual rainfall. Meanwhile rainwater is very limit to collect and store by using rainwater—harvesting engineering and the amount of supplementary irrigation was 18 mm each time. The purposes of this paper were to study the influence degree about supplementary irrigation on maize yield in very independent growth period and find out sensitive period of under supplemental irrigation with water harvesting, to response relationships between yield and water under different stages by mathematical model. Taking ETmin/ETa as relative evapotranspiration (deformed based on Jensen Model), the effects of some factors on model were eliminated by using relative yield and relative evapotranspiration. Relative yield and evapotranspiration were taken as input and output sample of BP Neural Network model, through a large number of compared training and analyzing, to establish model of maize response to water under supplemental irrigation with water harvesting. Meanwhile, compared and verified among the measured value, BP Neural Network model and the deformed Jensen model were coupled in this model. The results showed that simulation accuracy of the BP Neural Network model was higher obviously than the deformed Jensen model, which could reflect sensitivity of water demand in each growing stage and forecast maize yield. The disadvantages of the model were also discussed in the paper.

       

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