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Improved soil water deficit estimation through the integration of canopy temperature measurements into a soil water balance model

机译:通过将冠层温度测量整合到土壤水平模型中改善土壤水缺陷估计

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摘要

The total available water in the soil root zone (TAW(r)), which regulates the plant transpiration, is a critical parameter for irrigation management and hydrologic modeling studies. However, the TAW(r) was not well-investigated in current hydrologic or agricultural research for two reasons: (1) there is no direct measurement method of this parameter; and (2) there is, in general, a large spatial and temporal variability of TAW(r). In this study, we propose a framework to improve TAW(r) estimation by incorporating the crop water stress index (CWSI) from canopy temperature into the Food and Agriculture Organization of the United Nations (FAO) paper 56 water balance model. Field experiments of irrigation management were conducted for maize during the 2012, 2013 and 2015 growing seasons near Greeley, Colorado, USA. The performance of the FAO water balance model with CWSI-determined TAW(r) was validated using measured soil water deficit. The statistical analyses between modeled and observed soil water deficit indicated that the CWSI-determined TAW(r) significantly improved the performance of the soil water balance model, with reduction of the mean absolute error (MAE) and root mean squared error (RMSE) by 17 and 20%, respectively, compared with the standard FAO model (with experience estimated TAW(r)). The proposed procedure may not work under well-watered conditions, because TAW(r) may not influence the crop transpiration or crop water stress in both daily and seasonal scales under such conditions. The proposed procedure potentially could be applied in other ecosystems and with other crop water stress related measurements, such as surface evapotranspiration from remote sensing methodology.
机译:调节植物蒸腾的土根区(TAW(R))中的总可用水是灌溉管理和水文建模研究的关键参数。然而,Taw(R)在目前的水文或农业研究中没有得到很好的调查,原因如下:(1)该参数没有直接测量方法; (2)通常,Taw(R)的大量空间和时间变异性。在本研究中,我们提出了一种框架,通过将来自冠层温度的作物水分应激指数(CWSI)纳入联合国(粮农组织)纸56水平模型的食品和农业组织来改善Taw(R)估计。 2012年,2015年和2015年在美国科罗拉多州的Greeley附近的2012年和2015年生长季节进行了灌溉管理的现场试验。使用测量的土壤水缺陷验证了粮农组织水平模型与CWSI确定的Taw(R)的性能。建模和观测的土壤水分缺陷之间的统计分析表明,CWSI确定的TAW(R)显着提高了土壤水平模型的性能,减少了平均绝对误差(MAE)和根均方误差(RMSE)与标准粮农组织模型相比,分别为17和20%(具有经验估计Taw(R))。所提出的程序可能无法在含水良好的条件下工作,因为在这种条件下,Taw(R)可能不会影响每日和季节性尺度的作物蒸腾或作物水胁迫。所提出的程序可能可以应用于其他生态系统和其他作物水胁迫相关测量,例如遥感方法的表面蒸散。

著录项

  • 来源
    《Irrigation Science》 |2018年第3期|共15页
  • 作者单位

    USDA ARS Water Management &

    Syst Res Unit 2150 Ctr Ave Bldg D STE 320 Ft Collins CO 80526 USA;

    USDA ARS Water Management &

    Syst Res Unit 2150 Ctr Ave Bldg D STE 320 Ft Collins CO 80526 USA;

    Colorado State Univ Dept Civil &

    Environm Engn Campus Delivery 1372 Ft Collins CO 80523 USA;

    USDA ARS Rangeland Resources &

    Syst Res Unit 2150 Ctr Ave Bldg D Ft Collins CO 80526 USA;

    USDA ARS Water Management &

    Syst Res Unit 2150 Ctr Ave Bldg D STE 320 Ft Collins CO 80526 USA;

    USDA ARS Water Management &

    Syst Res Unit 2150 Ctr Ave Bldg D STE 320 Ft Collins CO 80526 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业科学;
  • 关键词

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