Upscaling Wetland Methane Emissions From the FLUXNET–CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Journal Article · Wed Sep 06 00:00:00 EDT 2023 · AGU Advances

DOI:https://doi.org/10.1029/2023av000956· OSTI ID:1999187

McNicol, Gavin ^[1]; Fluet‐Chouinard, Etienne ^[2]; Ouyang, Zutao ^[3]; Knox, Sara ^[4]; Zhang, Zhen ^[5]; Aalto, Tuula ^[6]; Bansal, Sheel ^[7]; Chang, Kuang‐Yu ^[8]; Chen, Min ^[9]; Delwiche, Kyle ^[10]; Feron, Sarah ^[11]; Goeckede, Mathias ^[12]; Liu, Jinxun ^[13]; Malhotra, Avni ^[14]; Melton, Joe R. ^[15]; Riley, William ^[8]; Vargas, Rodrigo ^[16]; Yuan, Kunxiaojia ^[8]; Ying, Qing ^[5]; Zhu, Qing ^[8] ; Alekseychik, Pavel ^[17]; Aurela, Mika ^[6]; Billesbach, David P. ^[18]; Campbell, David I. ^[19]; Chen, Jiquan ^[20]; Chu, Housen ^[8]; Desai, Ankur R. ^[9]; Euskirchen, Eugenie ^[21]; Goodrich, Jordan ^[19]; Griffis, Timothy ^[22]; Helbig, Manuel ^[23]; Hirano, Takashi ^[24]; Iwata, Hiroki ^[25]; Jurasinski, Gerald ^[26]; King, John ^[27]; Koebsch, Franziska ^[28]; Kolka, Randall ^[29]; Krauss, Ken ^[30]; Lohila, Annalea ^[31]; Mammarella, Ivan ^[32]; Nilson, Mats ^[33]; Noormets, Asko ^[34]; Oechel, Walter ^[35]; Peichl, Matthias ^[33]; Sachs, Torsten ^[36]; Sakabe, Ayaka ^[37]; Schulze, Christopher ^[38]; Sonnentag, Oliver ^[38]; Sullivan, Ryan C. ^[39]; Tuittila, Eeva‐Stiina ^[40]; Ueyama, Masahito ^[41]; Vesala, Timo ^[32]; Ward, Eric ^[29]; Wille, Christian ^[36]; Wong, Guan Xhuan ^[42]; Zona, Donatella ^[43]; Windham‐Myers, Lisamarie ^[44]; Poulter, Benjamin ^[45]; Jackson, Robert B. ^[3]

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1. Stanford University, CA (United States); University of Illinois, Chicago, IL (United States)
2. Stanford University, CA (United States); ETH Zurich (Switzerland)
3. Stanford University, CA (United States)
4. University of British Columbia, Vancouver, BC (Canada)
5. University of Maryland, College Park, MD (United States)
6. Finnish Meteorological Institute, Helsinki (Finland)
7. U.S. Geological Survey, Jamestown, ND (United States)
8. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
9. University of Wisconsin‐Madison, WI (United States)
10. University of California, Berkeley, CA (United States)
11. University of Groningen (The Netherlands)
12. Max Planck Institute for Biogeochemistry, Jena (Germany)
13. U.S. Geological Survey, Moffett Field, CA (United States)
14. University of Zurich (Switzerland)
15. Environment and Climate Change Canada, Victoria, BC (Canada)
16. University of Delaware, Newark, DE (United States)
17. Natural Resources Institute Finland (LUKE), Helsinki (Finland)
18. University of Nebraska‐Lincoln, NE (United States)
19. University of Waikato, Hamilton (New Zealand)
20. Michigan State University, East Lansing, MI (United States)
21. University of Alaska, Fairbanks, AK (United States)
22. University of Minnesota Twin Cities, St. Paul, MN (United States)
23. Dalhousie University, Halifax, NS (Canada)
24. Hokkaido University, Sapporo (Japan)
25. Shinshu University, Matsumoto (Japan)
26. University of Rostock (Germany); University of Greifswald (Germany)
27. North Carolina State University, Raleigh, NC (United States)
28. University of Göttingen (Germany)
29. USDA Forest Service Northern Research Station, Grand Rapids, MN (United States)
30. USGS Wetland and Aquatic Research Center, Lafayette, LA (United States)
31. Finnish Meteorological Institute, Helsinki (Finland); University of Helsinki (Finland)
32. University of Helsinki (Finland)
33. Swedish University of Agricultural Sciences, Umeå (Sweden)
34. Texas A&M University, College Station, TX (United States)
35. San Diego State University, CA (United States)
36. GFZ German Research Centre for Geosciences, Potsdam (Germany)
37. Kyoto University (Japan)
38. Université de Montréal, QC (Canada)
39. Argonne National Laboratory (ANL), Argonne, IL (United States)
40. University of Eastern Finland, Joesnuu (Finland)
41. Osaka Metropolitan University, Sakai (Japan)
42. Sarawak Tropical Peat Research Institute, Kota Samarahan (Malaysia)
43. San Diego State University, CA (United States); University of Sheffield (United Kingdom)
44. U.S. Geological Survey Water Mission Area, Menlo Park, CA (United States)
45. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)

Wetlands are responsible for 20%–31% of global methane (CH₄) emissions and account for a large source of uncertainty in the global CH₄ budget. Data-driven upscaling of CH₄ fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH₄ emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH₄ flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH₄ fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ~0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH₄ emissions of 146 ± 43 TgCH₄ y^–1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH₄ y^–1) and overlaps with top-down atmospheric inversion models (155–200 TgCH₄ y^–1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH₄ fluxes has the potential to produce realistic extra-tropical wetland CH₄ emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions.

• Research Organization: Argonne National Laboratory (ANL), Argonne, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). ARM Data Center
• Sponsoring Organization: USGS; National Aeronautics and Space Administration (NASA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Contributing Organization: Argonne National Laboratory (ANL); Brookhaven National Laboratory (BNL); Oak Ridge National Laboratory (ORNL); Pacific Northwest National Laboratory (PNNL)
• Grant/Contract Number: AC02-06CH11357
• OSTI ID: 1999187
• Alternate ID(s): OSTI ID: 2323333
• Journal Information: AGU Advances, Journal Name: AGU Advances Journal Issue: 5 Vol. 4; ISSN 2576-604X
• Publisher: Wiley
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
eddy covariance
flux
global
methane
random forest
wetland