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Agronomy Journal Abstract - WHEAT

Estimation of Winter Wheat Evapotranspiration under Water Stress with Two Semiempirical Approaches


This article in AJ

  1. Vol. 96 No. 1, p. 159-168
    Received: Oct 31, 2002

    * Corresponding author(s): zhangyq@igsnrr.ac.cn
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  1. Yongqiang Zhang *ab,
  2. Qiang Yua,
  3. Changming Liua,
  4. Jie Jiangc and
  5. Xiying Zhangab
  1. a Luancheng Agroecosyst. Stn., Inst. of Geogr. Sci. and Nat. Resour. Res., Chinese Acad. of Sci., Bldg. 917, Datun Rd., Beijing 100101, China
    b Xiying Zhang, Shijiazhuang Inst. of Agric. Modernization, Chinese Acad. of Sci., 286 Huaizhong Rd., Shijiazhuang 050021, P.R. China
    c Inst. of Environ. Sci., Beijing Normal Univ., Beijing 100875, P.R. China


Winter wheat (Triticum aestivum L.) is one of most important crops in the North China Plain. However, soil water deficit (SWD) often occurs due to lack of precipitation in its growing season. In this study, we introduce two semiempirical approaches, a recharge model and the crop coefficient (K c)–reference evapotranspiration (ET0) approach, to estimate wheat actual evapotranspiration (ETa) under no SWD and slight and severe SWD conditions. The recharge model allocated ET0 to reference evaporation and reference transpiration as a function of leaf area index. In the model, ETa is limited by soil water content, and crop water extraction for ETa is distributed through the soil profile as exponential functions of soil and root depth. The K c–ET0 approach regarded ETa under the SWD condition as a logarithmic function of soil water availability. Under no SWD condition, the recharge model simulated 10-d ETa with a root mean square error (RMSE) of 5.58 mm and a bias of 0.95 mm compared with measurements from a large-scale weighing lysimeter. The two approaches both estimated seasonal evapotranspiration (ET) well compared with the adjusted ET (from the soil water balance and the recharge model–simulated deep drainage). The recharge model, which simulated the seasonal ET with the RMSE of 27.8 mm and the bias of −8.0 mm, was better than the K c–ET0 approach (RMSE = 31.7 mm and bias = −33.1 mm). The seasonal pattern of soil water stress coefficient (K s) showed that there were faster water losses at grain-filling stage than at other stages.

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