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作 者:敬峰 段爱旺[1] 张莹莹[1] 娄和 巩文军 孙蒙强 刘战东[1] JING Feng;DUAN Aiwang;ZHANG Yingying;LOU He;GONG Wenjun;SUN Mengqiang;LIU Zhandong(Farmland Irrigation Research Institute,Chinese Academy of Agricultural Sciences/Ministry of Agriculture Key Laboratory of Crop Water Requirement and Regulation,Xinxiang 453002,China;Graduate School of the Chinese Academy of Agricultural Sciences,Beijing 100081,China;Henan Weisheng Electric Appliance Co.LTD,Xingxiang 450001,China;Henan Jiaozuo Guangli Irrigation District Administration Bureau,Qingyang 454550,China)
机构地区:[1]中国农业科学院农田灌溉研究所/农业农村部作物需水与调控重点实验室,河南新乡453002 [2]中国农业科学院研究生院,北京100081 [3]河南威盛电气有限公司,河南新乡450001 [4]河南省焦作市广利灌区管理局,河南沁阳454550
出 处:《灌溉排水学报》2022年第5期17-26,共10页Journal of Irrigation and Drainage
基 金:河南省自然科学基金项目(202300410553);国家现代农业产业技术体系岗位专项(CARS-03,CARS-02);新乡市重大科技专项(ZD2020009);河南省水利厅科技攻关计划项目(2021);中国农业科学院创新工程项目(ASTIP)。
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。【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.
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
分 类 号:S274[农业科学—农业水土工程]
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