| 引用本文: | 敬峰,段爱旺,刘战东.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,0,():-. |
| jingfeng,duanaiwang,liuzhandong.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,0,():-. |
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| 摘要: |
| 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，为冬小麦田间用水管理和智慧灌溉控制决策提供理论依据。【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%田间持水量，T60:60%田间持水量，T50:50%田间持水量），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＞T60＞T50)；基于大型蒸渗仪的实测结果，采用单作物系数法，双作物系数法以及BP人工神经网络建立蒸散量估算模型，利用田间实测数据对蒸散量模拟结果进行验证，验证结果表明：重度水分胁迫处理下(T50)，仅双作物系数模型模拟结果适用(NSE=0.646，RSR=0.599)；中度水分胁迫处理下(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)；轻度水分胁迫处理下(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： |
| 分类号:S274 |
| 基金项目:河南省自然科学基金(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（2021）、中国农业科学院创新工程 (ASTIP) |
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| The Study about the Rule of Evapotranspiration and Simulation of Winter Wheat based on Large-scale lysimeters |
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jingfeng, duanaiwang, liuzhandong
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Farmland Irrigation Research Institute
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| Abstract: |
| The Study about the Rule of Evapotranspiration and Simulation of Winter Wheat based on Large-scale lysimeters
Abstract:【Objective】The estimation model of evapotranspiration of winter wheat under different soil moisture conditions was explored to provide theoretical basis for field water management and intelligent irrigation control decision of winter wheat.【Method】In the area of North China,taking winter wheat as the research object, with the help of large-scale lysimeters, three lower limit levels of soil water content irrigation control(T70:70% field water capacity, T60:60% field water capacity, T50:50% field water capacity ) were set up. The evapotranspiration was estimated by single crop coefficient method, dual crop coefficient method and stepwise regression method, and the model was evaluated with relevant statistical indicators such as NSE and RSR.【Results】With the increase of soil water stress, the total evapotranspiration and evapotranspiration at each growth stage of winter wheat gradually decreased(T70>T60>T50);Based on the measured results of large-scale lysimeter,the evapotranspiration estimation model was established by single crop coefficient modle,dual crop coefficient model and BP artificial neural network. The field measured data were used to verify the simulation results of evapotranspiration which showed that under severe water stress treatment(T50),only the simulation results of dual crop coefficient model were suitable(NSE=0.646,RSR=0.599).Under moderate water stress(T60),BP artificial neural network model was relatively optimal(NSE=0.872,RSR=0.360),and dual crop coefficient model also had good estimation effect(NSE= 0.729,RSR=0.523 ).Under mild water stress(T70),each model had good estimation effect.【Conclusion】The dual crop coefficient model is suitable for different soil water stress levels.
Key words:winter wheat;large-scale lysimeters;different water treatment;evapotranspiration estimation;model evaluation |
| Key words: winter wheat;large-scale lysimeters;different water treatment;evapotranspiration estimation;model evaluation |
