越冬期麦田根区水热耦合模型参数原位估算与检验
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  • 英文篇名:Validation and in-situ Parameter Estimation for Model of Water Transport and Energy Exchange in Root Zone of Winter Wheat in Winter
  • 作者:程强 ; 徐嫱 ; 陈超 ; 薛绪掌 ; 王忠义 ; 孙宇瑞
  • 英文作者:CHENG Qiang;XU Qiang;CHEN Chao;XUE Xuzhang;WANG Zhongyi;SUN Yurui;College of Information and Electrical Engineering,China Agricultural University;Beijing Research Centre of Intelligent Equipment for Agriculture;
  • 关键词:麦田根区 ; 水热耦合运移 ; 地表蒸发量 ; 数值模拟 ; 参数估算
  • 英文关键词:roots zone of wheat;;coupled heat and water transport;;soil surface evaporation;;numerical simulation;;parameter estimation
  • 中文刊名:NYJX
  • 英文刊名:Transactions of the Chinese Society for Agricultural Machinery
  • 机构:中国农业大学信息与电气工程学院;北京农业智能装备技术研究中心;
  • 出版日期:2018-06-04 10:55
  • 出版单位:农业机械学报
  • 年:2018
  • 期:v.49
  • 基金:国家自然科学基金项目(31501231);; 北京市优秀人才培养(青年骨干个人)项目(2015000020124G124)
  • 语种:中文;
  • 页:NYJX201808026
  • 页数:9
  • CN:08
  • ISSN:11-1964/S
  • 分类号:226-234
摘要
越冬期根区充足的蓄水量有利于春季冬小麦的生长并有助于增产,而冬季作物根区水分运移规律通常借助土壤冻融过程水热耦合模型来描述,但该模型的预测精度受参数确定方法与边界条件等多种因素的影响。为了提高模型预测精度,提出了一种改进型的土壤冻融过程水热耦合模型参数估算方法,即运用土壤冻融特征曲线(冻土未冻水含量和土壤温度的关系)来原位估算土壤水热耦合模型参数,并检验该方法的适用性。在此基础上,评价地表蒸发量对模型预测精度的影响。大田试验在北京市昌平区小汤山精准农业示范基地开展,历经两个越冬期(2011—2012年和2012—2013年),利用管式介电传感器、温度传感器和蒸渗仪分别采集了土壤剖面未冻水含量、土壤温度和地表蒸发量数据。利用第1个越冬期(2011—2012年)的数据拟合土壤冻融特征曲线,对土壤水热参数进行最优估算,利用第2个越冬期(2012—2013年)的数据评价估算参数和地表蒸发量对模型预测精度的影响。结果表明:利用估算参数的模型预测值整体上与实测值相符。考虑到地表蒸发量对模型水热上边界的影响,第2个越冬期10 cm处未冻水含量与温度预测值和实测值的RMSE分别为0.046 m3/m3和1.883℃,20 cm深度RMSE分别为0.071 m3/m3和2.347℃。相比之下,在未考虑地表蒸发量影响下,第2个越冬期10 cm处未冻水含量与温度的模拟值和实测值的RMSE为0.059 m3/m3和2.149℃,20 cm深度RMSE为0.081 m3/m3和2.666℃。提出的改进型模型参数估算方法能够保证模型的预测精度,且考虑地表蒸发量的影响能够进一步提高模型的预测精度,随着深度的增加,蒸发量对水分与温度的影响逐渐减小。
        Sufficient water storage in root zone during winter time not only benefits crop growth in next spring,but also potentially increases the yield. Water movement in root zone was often simulated by using the coupled water and heat transport(CWHT) model during soil freezing-thawing process and influenced by multiple factors such as boundary conditions,parameters determination method,and so on. An improved method based on in-situ measured data was proposed to optimally estimate the parameters in the CWHT model. The applicability of this method was validated as well. The hydraulic parameters in the model were estimated in-situ by fitting soil freezing-thawing characteristic curve(SFC),which showed the relationship between the unfrozen soil water content(USWC) and soil temperature(ST). Then,the effect of surface evaporation(Es) on prediction accuracy in winter was evaluated. The field experiment was conducted over two winters(2011—2012 and 2012—2013) in an experimental farm at Changping County,Beijing,China. The USWC,ST and Eswere monitored with dielectric tube sensors,temperature sensors and lysimeter,respectively. The data obtained in 2011—2012 were used to fit SFC to optimize the hydraulic parameters,whereas those in 2012—2013 were used to verify the model. The resultsshowed that the model simulations were agreed well with the field measurements. When considering the effects of Eson USWC and ST,the root mean square errors(RMSE) of USWC and ST predictions in2012—2013 were 0. 046 m3/m3 and 1. 883℃ at 10 cm and 0. 071 m3/m3 and 2. 347℃ at 20 cm,respectively. In contrast to the condition without Es,the RMSE for USWC and ST predictions in 2012—2013 were 0. 059 m3/m3 and 2. 149℃ at 10 cm and 0. 081 m3/m3 and 2. 666℃ at 20 cm,respectively.Thus,the improved method of parameters determination based on in-situ measured data can ensure the prediction accuracy of the CWHT model. In addition,the accuracy could be further improved with considering the effects of surface evaporation and the effect of surface evaporation on USWC and ST was gradually decreased as the depth increased.
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