荒漠河岸林涡度相关通量测定中平均时间的确定及其对通量计算的影响

摘要/Abstract

摘要： 极端干旱区在全球生态系统中具有重要的地位而越来越被人们所重视。涡度相关技术是研究极端干旱区生态系统水热和CO2交换的有力工具之一。而涡度相关数据在实际应用中需要根据研究区的实际情况选择适宜于该地区的采样和计算参数（如采样频率和平均时间等）。根据2011年9月22日～10月8日（17个白天）原始数据（采样频率为10 Hz），采用不同平均时间（1～120 min）对塔河下游柽柳河岸林生态系统的潜热通量[（LE）]、感热通量[（H）]和CO2通量[（Fc）]进行了重新计算，比较分析各通量不同平均时间的计算值与30 min通量值，以揭示平均时间对该地区通量计算结果的影响。结果发现：（1）平均时间在120 min以内，17个白天湍流通量及能量平衡比率[（EBR）]均值随平均时间的延长而增大，当平均时间>120 min后，湍流通量（及[EBR]）均值随平均时间的延长大幅减小，其中15～60 min的[EBR]增幅较小，仅在2%左右。（2）平均时间>60 min后，[LE]、[H]和[FC]各通量计算值发生了不同程度的变异。通过进一步对上午[EBR]较为接近的5个样本日进行对比分析，发现当平均时间取15～60 min之间时，样本日的上午[EBR]值变化趋势一致，样本日间[EBR]差异较小；而当平均时间取>60 min或<15 min时，样本日间[EBR]差异明显增大。结合Ogive函数计算分析，我们的结论是，对于通量的长期观测研究而言，该地区适宜平均时间为60 min；而对通量的日变化研究而言，该地区适宜平均时间为15 min。通过分析15、30和60 min平均时间对小时通量的影响，发现当通量为增加趋势时，平均时间延长能够进一步增大通量绝对值，而当通量为减小趋势时，平均时间延长能够进一步减小通量绝对值。

关键词: 极端干旱区, 荒漠河岸林, 涡度相关, 平均时间, 能量平衡闭合

Abstract: Eddy covariance technology is one of the most powerful tools for research about water and carbon exchange in extremely arid region. The eddy covariance data normally need to be regulated based on the actual situation of the study area for application. Some of the regulations are selecting the suitable sampling and calculation parameters such as sampling frequency and averaging period. In this paper，the impact of averaging period on eddy flux calculation in desert riparian forest has been analyzed. The methodology that the research has adopted was recalculating the latent heat flux（LE），sensible heat flux （H），and CO₂ fluxes（FC） in different averaging period （1~120 min），cooperating and analyzing the calculations of flux values in different averaging periods and 30 min averaging period，and revealing the influences of the averaging period on the calculation of fluxes in the research area，based on the original data（sampling frequency was 10 Hz）from Sep 22 to Oct 17. And the Ogive function is applied to determine the low-frequency contribution to eddy fluxes. The results showed as follows：（1）the changing trend of diurnal mean fluxes and diurnal mean energy balance closure rates（EBR）of 17 researching days were different in different length of averaging period. When the averaging period was shorter than 120 min，both values increased as the averaging period rising；when the averaging period was longer than 120 min，both values decreased substantially as the averaging period rising. And when the averaging period was changing from 15 to 60 min，the two values varied slightly，just about 2%. （2）LE, H and FC flux values had a different degree of variation when the averaging period is longer than 60 min．With further analysis on the forenoon EBR of the 5 samples with similar EBR，it is found that either the averaging period was longer than 60 min or shorter than 15 min，the changes of EBR between the sampling days were much larger than those under other averaging periods. Our research showed that the averaging period 60 min was able to promote the energy balance closure，while 15 min was able to gain more information in this region. （3）The Ogive function showed the similar results that the optimal averaging period should be within the period from 15 to 60 min. The influences of averaging period（15-60 min）were also analyzed on the calculation of hourly eddy fluxes. The results showed that the flux densities were further increased as the averaging period extending when the flux was an upward trend，while the flux densities were further decreased with the averaging period extending when the flux was an downward trend. The innovation point of this article is to evaluate eddy covariance data quality in the extremely arid region in the Tarim Basin. According to this analysis，an averaging period that captures the low-frequency transport may improve the energy balance problem.

Key words: extremely arid region, desert riparian vegetation, Eddy covariance, averaging period, energy balance closure

中图分类号:

P422.4

张佩，袁国富，朱治林. 荒漠河岸林涡度相关通量测定中平均时间的确定及其对通量计算的影响[J]. 干旱区地理, 2013, 36(3): 400-408.

ZHANG Pei，YUAN Guo-fu，ZHU Zhi-lin. Determination of the averaging period of Eddy covariance measurement and its influences on the calculation of fluxes in desert riparian forest[J]. , 2013, 36(3): 400-408.

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