The Importance of Lake Littoral Zones for Estimating Arctic-Boreal Methane Emissions

Abstract

Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are underrepresented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ˜1.5 m deep and can be estimated through synthetic aperture radar (SAR) mapping. To assess the importance of lake emergent vegetation (LEV) zones to landscape-scale methane emissions, we combine airborne SAR mapping with field measurements of vegetated and open-water methane flux. First, we use Uninhabited Aerial Vehicle SAR (UAVSAR) data from the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) to map LEV in 4,572 lakes across four Arctic-boreal study areas and find it comprises ˜16% of lake area, exceeding previous estimates, and exhibiting strong regional differences (averaging 59 [50-68]%, 22 [20-25]%, 1.0 [0.8-1.2]%, and 7.0 [5.0-12]% of lake areas in the Peace-Athabasca Delta, Yukon Flats, and northern and southern Canadian Shield, respectively). Next, we account for these vegetated areas through a simple upscaling exercise using paired methane fluxes from regions of open water and LEV. After excluding vegetated areas that could be accounted for as wetlands, we find that inclusion of LEV increases overall lake emissions by 21 [18-25]% relative to estimates that do not differentiate lake zones. While LEV zones are proportionately greater in small lakes, this relationship is weak and varies regionally, underscoring the need for methane-relevant remote sensing measurements of lake zones and a consistent criterion for distinguishing wetlands. Finally, Arctic-boreal lake methane upscaling estimates can be improved with more measurements from all lake zones.

A Closer Look at the Effects of Lake Area, Aquatic Vegetation, and Double‐Counted Wetlands on Pan‐Arctic Lake Methane Emissions Estimates

“…The following publicly‐available data sets were used in this analysis: HydroLAKES (Messager et al., 2016) from the World Wildlife Fund; GSW (Pekel et al., 2016) from the European Commission's Joint Research Centre; BAWLD (Olefeldt et al., 2021a) and BAWLD‐CH4 (Kuhn et al., 2021a) from the National Science Foundation Arctic Data Center; WBD (Feng & Sui, 2020) from the Chinese National Tibetan Plateau/Third Pole Environment Data Center, available in English; LEV (Kyzivat et al., 2021) from the Oak Ridge National Lab (ORNL) Distributed Active Archive Center (DAAC); HR lakes (Kyzivat et al., 2019a; Mullen et al., 2022; Muster et al., 2017a) from ORNL DAAC, ORNL DAAC, and PANGEA, respectively; and ERA5 (Muñoz Sabater, 2019) from Copernicus Climate Change Service Climate Data Store. New data and a python toolbox generated for this manuscript are archived in the Arctic Data Center (Kyzivat & Smith, 2023).…”