Hou Qiong, Wang Haimei, Yun Wenli, et al. Experimental study on crop coefficient of spring maize in hetao irrigation district of Inner Mongolia. J Appl Meteor Sci, 2016, 27(4): 417-425. DOI:  10.11898/1001-7313.20160404.
Citation: Hou Qiong, Wang Haimei, Yun Wenli, et al. Experimental study on crop coefficient of spring maize in hetao irrigation district of Inner Mongolia. J Appl Meteor Sci, 2016, 27(4): 417-425. DOI:  10.11898/1001-7313.20160404.

Experimental Study on Crop Coefficient of Spring Maize in Hetao Irrigation District of Inner Mongolia

DOI: 10.11898/1001-7313.20160404
  • Received Date: 2015-10-27
  • Rev Recd Date: 2016-05-24
  • Publish Date: 2016-07-31
  • The crop coefficient curve is an important parameter for estimating the change of water consumption in growing season, and it plays an important role in water management, such as the simulation of evapotranspiration, irrigation forecasting and irrigation decision-making. Previous crop coefficient studies mainly concentrate on the average value of growth period, while rarely focus on daily changes. A crop coefficient simulation method is in need to improve spring maze irrigation forecasting business in Hetao area. Based on the field moisture test data and meteorological station historical observations, the crop coefficient of spring maize is calculated with water balance method, and a dynamic simulation equation is established considering the variation during growing season. It's then evaluated using results of the United Nations Food and Agriculture Organization (FAO) piecewise linear method, and daily rolling estimation of crop evapotranspiration is achieved. At the same time, the leaf area correction method is put forward to estimate the soil moisture content under the water stress, which can provide basis for the development of maize irrigation forecast. Results show that the crop coefficient of spring maize can be described by three curves of the development process, and the change trend of crop coefficient has nothing to do with the output level, but the variation range increases with the increase of output. Considering heat index can reduce the influence of geographical factors on crop coefficient, the simulation equation of maize coefficient are established based on relative accumulative temperature as time variable after emergence, and the decision coefficient are all above 0.92. The maximum (1.30-1.48) and average (0.831-0.919) maize coefficients of each site are calculated by simulation, results are basically the same as the 3 typical values and interval values got by FAO segmentation method, and the range of averaged relative error during growth period is 3.4%-7.2%. Through the analysis, it is concluded that Kc and relative leaf area index are better described by exponential function, and the calculation method of the standard leaf area index is proposed, which can calculate the crop coefficient in any production condition. The simulated soil moisture is consistent with the measured value with average relative error of 6.3%, and less than 15% for 95.8% circumstance, indicating good application prospects. As the soil moisture supply below 1 m is not considered yet, the model should be improved in the future to explore the calculation method of the lower layer water supply.
  • Fig. 1  ILA time variation curve under water suitable conditions

    Fig. 2  The crop coefficient curve of spring maize with the variable of ten days (a) or cumulative growing degree (b) after emergence

    Fig. 3  Comparison results of Kc calculated by 2 methods in different regions

    Fig. 4  Comparison of relative error of soil moisture simulation

    Table  1  The emergence date of 4 developmental stages and the average height of the plant

    地区 气象观测 生长初期 快速生长期 生长中期 生长末期
    临河试验田 时间段 05-06—05-31 06-01—05-07 07-06—08-20 08-21—09-15
    平均株高/cm 18 110 260 250
    临河区 时间段 05-10—06-04 06-05—07-10 07-11—08-25 08-26—09-20
    平均株高/cm 110 275 270
    准格尔旗 时间段 05-15—06-09 06-10—07-15 07-16—08-25 08-26—09-25
    平均株高/cm 120 240 225
    土左旗 时间段 05-08—06-02 06-03—07-08 07-09—08-20 08-21—09-15
    平均株高/cm 100 266 260
    DownLoad: Download CSV

    Table  2  Simulation equations and main parameters of crop coefficient of maize in growing season under water suitable conditions (n=15)

    地区 表达式 R2 Kc
    最大值
    Kc
    平均值
    产量水平/
    (kg·hm-2)
    临河试验田 Kcb=-5.14Tx3+3.84Tx2+1.795Tx+0.1461 0.9332 1.48 0.919 13501.1
    临河区 Kcb=-4.95Tx3+3.59Tx2+1.635Tx+0.2135 0.9208 1.43 0.900 12753.8
    准格尔旗 Kcb=-6.91Tx3+7.18Tx2-0.123Tx+0.2912 0.9356 1.38 0.868 11105.2
    土左旗 Kcb=-5.36Tx3+4.82Tx2+0.866Tx+0.2128 0.9478 1.30 0.831 10755.3
    注:Kcb为水分适宜时的作物系数;Tx表示生长过程相对积温, 单位:℃·d,计算方法为出苗后逐旬积温与生长季总积温的比值。
    DownLoad: Download CSV

    Table  3  The duration and emergence date of development stages and the comparison between modified crop coefficient and FAO value

    地区 生长期/d Kc
    生长
    初期
    快速
    生长期
    生长
    中期
    生长
    末期
    生育期 生长
    初期
    快速
    生长期
    生长
    中期
    生长
    末期
    FAO推荐值[2] 30 40 50 30 150 0.15 0.15~1.2 1.2 1.2~0.6
    临河试验田 25 35 45 25 130 0.2 0.2~1.27 1.27 1.27~0.69
    临河区 25 35 45 25 130 0.2 0.2~1.25 1.25 1.25~0.65
    准格尔旗 25 35 40 30 130 0.2 0.2~1.22 1.22 1.22~0.62
    土左旗 25 35 42 25 127 0.2 0.2~1.19 1.19 1.19~0.60
    DownLoad: Download CSV

    Table  4  The comparison results of Kc calculated by polynomials of different development stages

    地区 生长初期 快速生长期 生长中期 生长末期
    平均值 区间 平均值 区间 平均值 区间 平均值 区间
    FAO推荐值[2] 0.15 1.20 1.05~1.4 0.60
    临河试验田 0.29 0.15~0.45 0.87 0.67~1.08 1.35 1.20~1.48 0.81 1.10~0.47
    临河区 0.36 0.20~0.53 0.82 0.61~1.03 1.34 1.22~1.43 0.83 1.12~0.53
    准格尔旗 0.40 0.30~0.51 0.84 0.65~1.03 1.27 1.15~1.38 0.89 1.18~0.59
    土左旗 0.35 0.25~0.48 0.81 0.63~0.99 1.23 1.14~1.30 0.78 1.00~0.56
    DownLoad: Download CSV
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    • Received : 2015-10-27
    • Accepted : 2016-05-24
    • Published : 2016-07-31

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