Detecting Hot Spots of Methane Flux Using Footprint-Weighted Flux Maps

In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH₄) flux. In the first part of the study, we used a CH₄ release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint-Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH₄ release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH₄ flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m^-2 s^-1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m^-2 s^-1. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy-covariance towers and creates important insights for the interpretation of hot spots of CH₄ flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH₄ flux.

[Flux footprint of winter wheat farmland ecosystem in the North China Plain]

The flux data of winter wheat farmland ecosystem observed by eddy covariance system in the North China Plain from 2013 to 2014 were used to combine with the footprint model FSAM. The temporal and spatial distributions of footprint of winter wheat farmland ecosystem in the North China Plain were analyzed. The differences of footprint distribution in different atmospheric stratification and growing seasons were contrastively studied. The results indicated that in the predominant wind direction, the source areas of stable atmospheric stratification were larger than unstable atmospheric stratification during the growing season of winter wheat. When the wind direction was between 0°-90°, the source area of stable atmospheric stratification was about 17.8 m longer than unstable atmospheric stratification in initial growing season. The source area of stable atmospheric stratification was about 11 m longer than unstable atmospheric stratification in late growing season. The location of the maximum flux footprint in initial growing season was 15 m (stable atmospheric stratification) and 12.4 m (unstable atmospheric stratification) further away from the observing tower than late growing season, respectively. Meanwhile, the location of the maximum flux footprint in stable atmospheric stratification was 5 m (initial growing season) and 2.4 m (late growing season) further away from the observing tower than unstable atmospheric stratification, respectively. When the wind direction was non-dominant between 90°-180°, the location of the maximum flux footprint in diffe-rent growing seasons and atmospheric stratification were 67.8 and 53.4, 47.0 and 30.8 m away from the observing tower, respectively. When the wind direction was between 270°-360°, the location of the maximum flux footprint in different growing seasons and atmospheric stratification were 58.8 and 42.0, 41.1 and 33.1 m away from the observing tower, respectively. The flux information was mainly from the northeast, southwest and southeast, which accounted for 35.4%, 32.5% and 19.4% of the whole gro-wing season scale, respectively. The major changes of flux footprint in the whole gro-wing season of winter wheat were observed from 16.0 to 173.8 m in the northeast and from 14.7 to 209 m in the southwest. The flux information was all from the farmland ecosystem. The characteristics of diurnal variations of flux footprint in two typical dates were obvious. The source area changed with atmospheric stratification and wind direction. The flux information was all from farmland ecosystem at night, while little flux information was from residential area and orchard at daytime. The quantitative results of this study could provide basis for the research of flux footprint in farmland ecosystem.