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Flux measurements and sampling strategies: Applications to methane emissions from rice fields

机译:通量测量和采样策略:稻田甲烷排放的应用

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The emissions of methane from rice fields and other sources are often measured by placing chambers on the surface and taking sequential samples. Although static chambers pose several problems that affect the accuracy of the data, there are a few parameters that, if carefully chosen, can improve the reliability of the data and reduce the uncertainties. These parameters are the length of time the chamber is kept on the rice plants, the number of samples that are drawn to estimate the flux, the basal area and height of the chamber, the frequency of measurements during the growing season, and the number of plots sampled. In this paper we analyze a large data set to determine how these parameters can be chosen to improve data quality. The results show that, for individual flux measurements, extending the time the chambers are left on the plots improves precision more effectively than taking more sequential samples for each flux measurement. The exposure time cannot be extended too far, however, as it leads to a saturation effect so that the rate of accumulation in the chamber slows down, This can compromise the accuracy of the measurement. There is an optimum exposure time that balances these two effects. Many individual measurements are needed to characterize the emissions from the larger area of the fields and the seasonal patterns. For methane emissions from rice fields, the amplitude of the systematic seasonal cycle is usually large compared to the variability on shorter timescales. Consequently, reducing the sampling frequency increases the uncertainty of the seasonal flux very slowly. The spatial variability is large and random on the small scales of the basal area of the chambers. Reducing the number of plots sampled, therefore, has a major effect on the uncertainty of the seasonal average flux. [References: 3]
机译:稻田和其他来源的甲烷排放量通常是通过在表面上放置小室并进行连续采样来测量的。尽管静态腔室存在一些影响数据准确性的问题,但是如果谨慎选择,仍有一些参数可以提高数据的可靠性并减少不确定性。这些参数包括将室放置在水稻植物上的时间长度,为估计通量而抽取的样本数量,室的基础面积和高度,生长期期间的测量频率以及样地。在本文中,我们分析了一个大型数据集,以确定如何选择这些参数以提高数据质量。结果表明,对于单独的通量测量,延长腔室在图中的停留时间比对每个通量测量获取更多顺序的样本更有效地提高了精度。但是,曝光时间不能延长太多,因为它会导致饱和效应,从而使腔室中的累积速率变慢,这可能会损害测量的准确性。有一个最佳的曝光时间可以平衡这两种效果。需要进行许多单独的测量来表征更大面积的田地和季节模式的排放。与稻田甲烷排放相比,与较短时间尺度上的变化相比,系统性季节周期的幅度通常较大。因此,降低采样频率会非常缓慢地增加季节性通量的不确定性。室的基础区域的空间变异性大且随机。因此,减少样地数量对季节平均通量的不确定性有重大影响。 [参考:3]

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