| 引用本文: | 敬 峰,段爱旺,张莹莹,等.基于大型蒸渗仪的冬小麦蒸散规律及其模拟[J].灌溉排水学报,2022,41(5):17-26. |
| JING Feng,DUAN Aiwang,ZHANG Yingying,et al.基于大型蒸渗仪的冬小麦蒸散规律及其模拟[J].灌溉排水学报,2022,41(5):17-26. |
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| 摘要: |
| 【目的】探究不同土壤水分条件下冬小麦蒸散量适宜估算模型。【方法】在华北地区，以冬小麦为研究对象，借助大型蒸渗仪，设置3个土壤含水率灌水控制下限水平（T70：70%田间持水率，T60：60%田间持水率，T50：50%田间持水率），分别采用单作物系数法，双作物系数法以及BP人工神经网络进行蒸散量估算，并结合纳什系数（NSE）和均方根误差/观测值标准差比率（RSR）等统计指标进行模型评价。【结果】随土壤水分胁迫程度的增加，冬小麦蒸散总量和各生长阶段蒸散量逐渐减少（T70处理＞T60处理＞T50处理）；中度水分胁迫处理下（T50），仅双作物系数模型模拟结果适用（NSE=0.646，RSR=0.599）；轻度水分胁迫处理下（T60），BP人工神经网络模型相对最优（NSE=0.872，RSR=0.360），双作物系数模型估算效果良好（NSE=0.729，RSR=0.523）；适宜水分处理下（T70），各个模型均有较好的估算效果。【结论】双作物系数模型适宜于不同土壤水分胁迫水平。 |
| 关键词: 冬小麦；大型蒸渗仪；不同水分处理；蒸散量估算；模型评价 |
| DOI：10.13522/j.cnki.ggps.2021624 |
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| 基金项目: |
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| The Effects of Soil Water on Accuracy of Different Methods for Calculating Evapotranspiration from Winter Wheat Field |
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JING Feng, DUAN Aiwang, ZHANG Yingying, LOU He,
GONG Wenjun, SUN Mengqiang, LIU Zhandong
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1. Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences/
Ministry of Agriculture Key Laboratory of Crop Water Requirement and Regulation, Xinxiang 453002, China;
2. Graduate School of the Chinese Academy of Agricultural Sciences, Beijing 100081, China;
3. Henan Weisheng Electric Appliance Co. LTD, Xingxiang 450001, China;
4. Henan Jiaozuo Guangli Irrigation District Administration Bureau, Qingyang 454550, China
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| Abstract: |
| 【Objective】 Evapotranspiration from farmlands is an important component in the hydrological cycle, and it varies with many factors. The aim of this paper is to present an experimental study on the impact of soil water on reliability of different methods commonly used in the literature to calculate evapotranspiration from cropped fields.【Method】The experiment was conducted using large lysimeters with winter wheat used as the model plant. It consisted of three soil water treatments, achieved by criteria for irrigation: Resuming irrigation whenever the soil water content in the root zone dropped to 70% (T70), 60% (T60) and 50% (T50) of the field water capacity, respectively. The evapotranspiration in each treatment was calculated by methods using a single crop coefficient, dual crop coefficient, and the BP artificial neural network, respectively. 【Result】 With an increase in water stress due to the reduced irrigation, the total evapotranspiration and seasonable evapotranspiration at different growth stages decreased. Comparison with measured results from the lysimeters showed that the accuracy of the three models varied with soil water content. Under moderate water stress (T50), only did the method using dual crop coefficient reproduce the measured evapotranspiration reasonably well with NSE=0.646 and RSR=0.599. Under mild water stress (T60), the BP artificial neural network model worked better with NSE=0.872 and RSR=0.360, followed by the dual crop coefficient model with NSE=0.729, RSR=0.523. When there was a limited or without water stress (T70), all three methods accurately reproduced the measured evapotranspiration.【Conclusion】On average, the model using dual crop coefficient is more suitable for estimating evapotranspiration of winter wheat grown in soils under different water stress. |
| Key words: winter wheat; large lysimeters; water stress; evapotranspiration; crop coefficient |
