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Eddy covariance measurements quantify the magnitude and temporal variability of land-atmosphere exchanges of water, heat, and carbon dioxide (CO 2 ) among others. However, they also carry information regarding the influence of spatial heterogeneity within the flux footprint, the temporally dynamic source/sink area that contributes to the measured fluxes. A 25 m tall eddy covariance flux tower in Central Illinois, USA, a region where drastic seasonal land cover changes from intensive agriculture of maize and soybean occur, provides a unique setting to explore how the organized heterogeneity of row crop agriculture contributes to observations of land-atmosphere exchange. We characterize the effects of this heterogeneity on latent heat ( LE ), sensible heat ( H ), and CO 2 fluxes ( F c ) using a combined flux footprint and eco-hydrological modeling approach. We estimate the relative contribution of each crop type resulting from the structured spatial organization of the land cover to the observed fluxes from April 2016 to April 2019. We present the concept of a fetch rose, which represents the frequency of the location and length of the prevalent upwind distance contributing to the observations. The combined action of hydroclimatological drivers and land cover heterogeneity within the dynamic flux footprint explain interannual flux variations. We find that smaller flux footprints associated with unstable conditions are more likely to be dominated by a single crop type, but both crops typically influence any given flux measurement. Meanwhile, our ecohydrological modeling suggests that land cover heterogeneity leads to a greater than 10% difference in flux magnitudes for most time windows relative to an assumption of equally distributed crop types. This study shows how the observed flux magnitudes and variability depend on the organized land cover heterogeneity and is extensible to other intensively managed or otherwise heterogeneous landscapes.
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This content will become publicly available on April 1, 2027
Flux Footprints: A Critical Link to Bridge Eddy‐Covariance Measurements With Models, Remote Sensing, and Other Observations
ABSTRACT Global networks of eddy‐covariance flux towers play a pivotal role in enhancing our predictive understanding of carbon and water cycling of biological systems in response to regional and global environmental change. Despite their broad application in numerous studies, the spatial aspects of the flux measurements have often been ignored or treated ambiguously, thereby remaining a primary source of uncertainty. The area contributing to the flux—referred to as the flux footprint—varies over time depending on wind direction, atmospheric turbulence, effective measurement heights, surface characteristics, and mesoscale forcings. The footprint dynamics, along with underlying source‐sink heterogeneity, lead to spatial and temporal variability in the sensed fluxes, complicating the interpretation of flux data and their integration with a range of observations and models. This article addresses this critical link by reviewing the most up‐to‐date research, identifying knowledge gaps and challenges, and pointing out future research needs and opportunities. We begin with an overview of the current state of footprint modeling and its applications, from single‐site studies to large‐scale syntheses, summarizing how flux footprints have been used to interpret spatial flux variability and to integrate flux data with models, remote sensing, and other observations. We highlight how this critical spatial aspect could complicate the processing of eddy‐covariance fluxes, the definition of mass and energy continuity, and the interpretation of flux response functions and parameters, all of which have significant implications for numerous applications and research. We then point out potential opportunities and future research needs to bridge this knowledge gap, highlighting both readily available and prominent emerging ones. We conclude by urging the scientific community to (re)consider the spatiotemporal dynamics of eddy‐covariance flux measurements, and to investigate and evaluate potential approaches across scales, applications, and disciplines.
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- Award ID(s):
- 2217817
- PAR ID:
- 10686186
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 32
- Issue:
- 4
- ISSN:
- 1354-1013
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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