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首页> 外文期刊>Agricultural Water Management >A crop coefficient -based water use model with non-uniform root distribution
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A crop coefficient -based water use model with non-uniform root distribution

机译：具有非均匀根分布的作物系数基础的水模型

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摘要

Uncertainties in the estimation of evapotranspiration (ET1) using the crop coefficient (K-c)-reference ET method arise for deeply rooted crops and severe water stress. We expanded upon the crop coefficient-based model by modifying plant available water via a nonuniform root distribution that limited deep water extraction using daily estimated soil profile water contents. The model was calibrated to predict maize (Zea mays L.) ET over a wide range in crop water deficits. In addition, maize grain yield was calibrated with model-predicted ET using a multiplicative water production function. The calibrated model with optimized crop and stress response coefficients predicted actual maize ET for a wide range in water deficits with a daily and growing season prediction root mean square error (RMSE) of 1.16 mm d(-1) and 25.6 mm, respectively. A nonuniform root distribution functioned similarly to stress response coefficients reducing soil water extraction deeper in the profile with a resultant 18% reduction in the prediction RMSE compared with the optimized stress response conventionally used with the K-c approach. The largest uncertainties in predicted crop ET resulted from an underestimation of runoff and an overestimation of crop water use during stress-induced early senescence. Measured and predicted soil water contents averaged over the entire rooting depth agreed closely, however root water extraction was overestimated deeper in the profile. Calibration of the water production function using data exhibiting a wide range in measured grain yield resulted in a RMSE of 2.1 Mg ha(-1). Including an additive high temperature stress response expression improved the calibration. Because of the limited input requirements and robustness over a wide range in crop water stress levels, the model would be suitable for evaluating deficit irrigation strategies.
机译：使用作物系数（K-C）-REFERSTET方法估计蒸发（ET1）估计的不确定性，因此为深生根作物和严重的水胁迫而产生。我们通过使用日常估计的土壤剖面水含量来改变植物可用水通过改变植物可用水来扩展植物系数的模型。该模型被校准以预测玉米（Zea Mays L.）等在繁殖的作物水缺陷范围内。此外，使用倍增水生产功能，用模型预测的ET校准玉米籽粒产量。具有优化的作物和应力响应系数的校准模型预测了实际玉米ET，在水缺陷范围内，每天和生长季节预测根均线（RMSE）分别为1.16mm D（-1）和25.6毫米。类似地与应力响应系数相似的不均匀根分布在轮廓水中的压力响应系数减少在轮廓中更深，因此与常规与K-C方法一起使用的优化应力反应相比，预测RMSE减少了18％。预测作物ET中的最大不确定性因低估径流而导致在应激诱导的早期衰老期间对农作物使用的过度估计。测量和预测的土壤水含量在整个生根深度上平均得分，但是根水萃取在概况中深度深度升高。使用具有测量谷物产量宽范围的数据校准水产生函数导致RMSE为2.1mg HA（-1）。包括添加剂高温应激响应表达改善校准。由于在农作物水胁迫水平范围内的广泛范围内有限，该模型适用于评估赤字灌溉策略。

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