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Modification of a Wavelet-Based Method for Detecting Ebullitive Methane Fluxes in Eddy-Covariance Observations: Application at Two Rice Fields

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Abstract

Ebullition, the release of gas bubbles, is an important pathway of methane emission in many ecosystems, yet its high spatio–temporal variability makes it challenging to quantify. In this work, a methane-flux partitioning method based on scalar similarity in the wavelet domain is applied to eddy-covariance data collected at two flooded rice fields. Inspection of initial results indicates that several modifications are needed for robust ebullition detection. With these modifications, our objectives are to compare the original and modified methods, conduct a sensitivity analysis of the program’s empirical parameters, characterize the importance of ebullition in rice across growth stages, and identify the primary drivers of ebullition. The modified method’s ebullitive fluxes are significantly lower and show lower variance than those from the original method. Furthermore, the two methods produce distinct patterns of diel variation. While partitioning estimates show non-trivial sensitivity to the program parameters, this sensitivity is lower in magnitude than the random error in the ebullitive flux estimates. Ebullitive fluxes make up 9% of the total flux on average, with ebullition increasing in importance as plants develop. Ebullitive fluxes are best predicted by wind speed (negative effect), ecosystem respiration (positive effect), and sensible heat flux (positive effect), suggesting an indirect effect of plant-mediated transport, a link with temperature and methane production, and a potential effect of water column turnover, respectively. In addition to validating the method with independent ebullition observations, we recommend its application at more natural and managed wetlands to improve understanding of this highly variable transport pathway.

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Acknowledgements

This work was funded by the U.S. National Science Foundation CBET division CAREER Award 1752083 and NASA award 80NSSC20K0923 to support Atmospheric Carbon and Transport (ACT)—America, a NASA Earth Venture Suborbital 2 project funded by the NASA Earth Science Division. This research was also supported by the USDA Agricultural Research Service National Program 211. We would like to thank Kosana Suvočarev, Colby Reavis, S. Faye Smith, Yin-Lin Chiu, and Bryant Fong for their assistance with field data collection. We thank the Isbell family and Zero Grade Farms for hosting our team and instrumentation and for managing these fields. Code for the modified partitioning program presented in this study is freely available at https://github.com/richardsonwillp/Wetland-CH4-partition. The datasets generated and analyzed in this study are available from the corresponding author on reasonable request.

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  1. Department of Biological and Agricultural Engineering, University of Arkansas, Fayetteville, AR, 72701, USA

    Will P. Richardson & Benjamin R. K. Runkle

  2. United States Department of Agriculture – Agricultural Research Service, Delta Water Management Research Unit, Jonesboro, AR, 72401, USA

    Michele L. Reba

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Richardson, W.P., Reba, M.L. & Runkle, B.R.K. Modification of a Wavelet-Based Method for Detecting Ebullitive Methane Fluxes in Eddy-Covariance Observations: Application at Two Rice Fields. Boundary-Layer Meteorol 184, 71–111 (2022). https://doi.org/10.1007/s10546-022-00703-y

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