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基于涡度相关法的黄河小浪底人工混交林CH4通量平均周期的确定

原文文, 张劲松, 孟平, 同小娟, 周宇, 李朋兴

原文文, 张劲松, 孟平, 同小娟, 周宇, 李朋兴. 基于涡度相关法的黄河小浪底人工混交林CH4通量平均周期的确定[J]. 北京林业大学学报, 2020, 42(10): 55-61. DOI: 10.12171/j.1000-1522.20200003
引用本文: 原文文, 张劲松, 孟平, 同小娟, 周宇, 李朋兴. 基于涡度相关法的黄河小浪底人工混交林CH4通量平均周期的确定[J]. 北京林业大学学报, 2020, 42(10): 55-61. DOI: 10.12171/j.1000-1522.20200003
Yuan Wenwen, Zhang Jinsong, Meng Ping, Tong Xiaojuan, Zhou Yu, Li Pengxing. Determination of the average period of CH4 flux in a mixed plantation in Xiaolangdi Area of the Yellow River based on eddy covariance method[J]. Journal of Beijing Forestry University, 2020, 42(10): 55-61. DOI: 10.12171/j.1000-1522.20200003
Citation: Yuan Wenwen, Zhang Jinsong, Meng Ping, Tong Xiaojuan, Zhou Yu, Li Pengxing. Determination of the average period of CH4 flux in a mixed plantation in Xiaolangdi Area of the Yellow River based on eddy covariance method[J]. Journal of Beijing Forestry University, 2020, 42(10): 55-61. DOI: 10.12171/j.1000-1522.20200003

基于涡度相关法的黄河小浪底人工混交林CH4通量平均周期的确定

基金项目: 中央公益性科研院所基本科研业务费专项(CAFYBB2017ZX002-1)
详细信息
    作者简介:

    原文文,博士生。主要研究方向:林业气象。Email:yw7198205@163.com 地址:100091 北京市海淀区东小府1号中国林业科学研究院林业研究所

    责任作者:

    张劲松,研究员,博士生导师。主要研究方向:复合农林业、林业生态工程及农林气象。Email:zhangjs@caf.ac.cn 地址:同上

  • 中图分类号: S718.55+7; S716

Determination of the average period of CH4 flux in a mixed plantation in Xiaolangdi Area of the Yellow River based on eddy covariance method

  • 摘要:
      目的  随着涡度相关法长期连续观测CH4通量的研究在国际上日渐增加,准确计算CH4通量成为相关研究人员关注的热点问题之一。根据研究区实际情况,探究涡度相关数据在实际应用中适宜的采样频率和平均计算周期,为准确计算CH4通量提供理论依据。
      方法  采用不同的平均周期(15 ~ 720 min)对黄河小浪底人工混交林生态系统2016年7—8月CH4通量原始数据(采样频率10 Hz)进行计算,以30 min为准标准,比较不同平均周期计算的CH4通量日变化特征,分析不同平均周期对CH4通量计算的影响。
      结果  不同平均周期导致计算的CH4通量结果发生变化。15、60、120、240、360和720 min平均周期与30 min计算的CH4通量日变化特征趋势差异正午前后较大,而在早晨或傍晚差别较小;平均周期小于120 min时,其计算CH4通量日变化趋势与30 min一致,CH4的通量值随平均周期的增加而增大,当平均周期大于240 min,通量计算出现明显误差。结合Ogive函数计算分析,当平均周期小于15 min时,Ogive函数逐渐增大,当平均周期为60 min时,ogive函数逐渐平稳。
      结论  不同计算周期对CH4的计算结果有一定的影响,在本研究区下垫面情况下,计算月及其以上尺度的CH4通量采用60 min的平均周期,而研究日及其以下尺度的CH4通量变化特征时采用平均计算周期为15 min。
    Abstract:
      Objective  The eddy covariance technique provides a useful tool to directly measure CH4 exchange between the vegetation and atmosphere. The eddy covariance data normally need to be regulated based on the actual situation of the study area for its application. An inappropriate average period can lead to the inaccurate estimation on CH4 flux. Therefore, some of the regulations were selected to obtain the suitable sampling frequency and average period.
      Method  In this paper, the impact of average period on CH4 flux calculation had been analyzed in a mixed plantation in the Xiaolangdi Area of the Yellow River from July to August of 2016. CH4 flux was calculated in different average periods (15−720 min). CH4 flux obtained in different periods was analyzed, and the calculation of CH4 flux in different average periods was compared with that of 30 min average period. The influences of average period on the calculation of CH4 flux based on the original data (sampling frequency was 10 Hz) were examined. In addition, the Ogive function was applied to determine the low-frequency contribution to CH4 flux.
      Result  The diurnal variations of CH4 flux were different in the average period of 15, 60, 120, 240, 360 and 720 min. Large differences occurred at noon and small differences occurred in the morning or evening. When the average period was shorter than 120 min, CH4 flux had same diurnal variation characteristics with 30 min value, and increased with the increase of the average period. The calculation of CH4 flux was estimated significantly inaccurately when the average period was longer than 240 min. The Ogive function increased when the averaging period was less than 15 min, and the Ogive function became gradually stable when the period was 60 min.
      Conclusion  Different average periods have different influences in calculating CH4 flux. In this study, the optimal average period should be 60 min during the long-term observation, whereas the average period should be 15 min to obtain accurate CH4 flux at the daily time scale.
  • 图  1   不同平均周期与30 min平均周期计算CH4通量的日变化特征(2016−07−24—2016−07−30)

    Figure  1.   Diurnal variation characteristics of CH4 flux calculated by different average periods and 30 min average time ( July 24 to 30, 2016)

    图  2   典型晴天(7月25日10:00—14:00 )CH4通量的Ogive函数图

    Figure  2.   Ogive function diagram for typical sunny daytime (25th July from 10:00 to 14:00)

    表  1   不同平均周期与30 min平均周期计算CH4通量之间的统计关系(2016−08)

    Table  1   Statistical relationship in calculating CH4 flux between different average periods (15−720 min) and 30 min average period (August, 2016)

    平均时间
    Average time/min
    回归方程
    Regression equation
    R2
    15 y = 0.845x 0.967
    30 y = x 1
    60 y = 1.022x 0.899
    120 y = 1.298x 0.812
    240 y = 1.571x 0.94
    360 y = 1.873x 0.871
    720 y = 1.2433x 0.657
    下载: 导出CSV
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  • 收稿日期:  2020-01-15
  • 修回日期:  2020-03-10
  • 网络出版日期:  2020-10-08
  • 发布日期:  2020-10-24

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