Abstract
Wetlands represent the dominant natural source of methane (CH4) to the atmosphere. Thus, substantial effort has been spent examining the CH4 budgets of global wetlands via continuous ecosystem-scale measurements using the eddy covariance (EC) technique. Robust error characterization for such measurements, however, remains a major challenge. Here, we quantify systematic, random and gap-filling errors and the resulting uncertainty in CH4 fluxes using a 3.5 year time series of simultaneous open- and closed path CH4 flux measurements over a sub-boreal wetland. After correcting for high- and low frequency flux attenuation, the magnitude of systematic frequency response errors were negligible relative to other uncertainties. Based on three different random flux error estimations, we found that errors of the CH4 flux measurement systems were smaller in magnitude than errors associated with the turbulent transport and flux footprint heterogeneity. Errors on individual half-hourly CH4 fluxes were typically 6%–41%, but not normally distributed (leptokurtic), and thus need to be appropriately characterized when fluxes are compared to chamber-derived or modeled CH4 fluxes. Integrated annual fluxes were only moderately sensitive to gap-filling, based on an evaluation of 4 different methods. Calculated budgets agreed on average to within 7% (≤1.5 g−CH4 m−2 yr−1). Marginal distribution sampling using open source code was among the best-performing of all the evaluated gap-filling approaches and it is therefore recommended given its transparency and reproducibility. Overall, estimates of annual CH4 emissions for both EC systems were in excellent agreement (within 0.6 g−CH4 m−2 yr−1) and averaged 18 g−CH4 m−2 yr−1. Total uncertainties on the annual fluxes were larger than the uncertainty of the flux measurement systems and estimated between 7–17%. Identifying trends and differences among sites or site years requires that the observed variability exceeds these uncertainties.
Original language | English (US) |
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Article number | 107638 |
Journal | Agricultural and Forest Meteorology |
Volume | 278 |
DOIs | |
State | Published - Nov 15 2019 |
Bibliographical note
Funding Information:This work was supported by NASA's Interdisciplinary Research in Earth Science program (IDS Grant # NNX17AK18G). We gratefully acknowledge advice on statistical analysis from G. Oehlert (University of Minnestoa, Twin Cities). J.D. Wood acknowledges support from the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research Program, Climate and Environmental Sciences Division through Oak Ridge National Laboratory's Terrestrial Ecosystem Science (TES) Science Focus Area (SFA); ORNL is managed by UT-Battelle, LLC, for the U.S. DOE under contract DE-AC05-00OR22725.
Funding Information:
This work was supported by NASA’s Interdisciplinary Research in Earth Science program (IDS Grant # NNX17AK18G ). We gratefully acknowledge advice on statistical analysis from G. Oehlert (University of Minnestoa, Twin Cities). J.D. Wood acknowledges support from the U.S. Department of Energy , Office of Science , Office of Biological and Environmental Research Program , Climate and Environmental Sciences Division through Oak Ridge National Laboratory’s Terrestrial Ecosystem Science (TES) Science Focus Area (SFA) ; ORNL is managed by UT-Battelle, LLC , for the U.S. DOE under contract DE-AC05-00OR22725.
Publisher Copyright:
© 2019 Elsevier B.V.
Keywords
- Budget
- Eddy covariance
- Error
- Methane
- Uncertainty