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Abstract Streams and rivers are major sources of greenhouse gases (GHGs) to the atmosphere, as carbon and nitrogen are converted and outgassed during transport. Although our understanding of drivers of individual GHG fluxes has improved with numerous site‐specific studies and global‐scale compilations, our ability to parse out interrelated physical and biogeochemical drivers of gas concentrations is limited by a lack of consistently collected, temporally continuous samples of GHGs and their associated drivers. We present a first analysis of such a dataset collected by the National Ecological Observatory Network across 27 streams and rivers across ecoclimatic domains of the United States. Average concentrations of CO2ranged from 36.9 ± 0.88 to 404 ± 33 μmol L−1, CH4from 0.003 ± 0.0003 to 4.99 ± 0.72 μmol L−1, and N2O from 0.015 to 0.04 μmol L−1and spanned ranges of previous global compilations. Both CO2and CH4were strongly affected by physical drivers including mean air temperature and stream slope, as well as by dissolved oxygen and total nitrogen concentrations. N2O was exclusively correlated with total nitrogen concentrations. Results suggested that potential for gas exchange dominated patterns in gas concentrations at the site level, but contributions of in‐stream aerobic and anaerobic metabolism, and groundwater also likely varied across sites. The highest gas concentrations as well as highest variability occurred in low‐gradient, warmer, and nonperennial systems. These results are a first step in providing unprecedented, continuous estimates of GHG flux constrained by temporally variable physical and biogeochemical drivers of GHG production.
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Improving Predictions of Stream CO 2 Concentrations and Fluxes Using a Stream Network Model: A Case Study in the East River Watershed, CO, USA
Abstract Inland waters are an important component of the global carbon budget. However, our ability to predict carbon fluxes from stream systems remains uncertain, aspCO2varies within streams at scales of 1–100 m. This makes direct monitoring of large‐scale CO2fluxes impractical. We incorporate CO2input and output fluxes into a stream network advection‐reaction model, representing the first process‐based representation of stream CO2dynamics at watershed scales. This model includes groundwater (GW) CO2inputs, water column (WC), benthic hyporheic zone (BHZ) respiration, downstream advection, and atmospheric exchange. We evaluate this model against existing statistical methods including upscaling and multiple linear regressions through comparisons to high‐resolution streampCO2data collected across the East River Watershed in the Colorado Rocky Mountains (USA). The stream network model accurately captures GW, evasion, and respiration‐drivenpCO2variability and significantly outperforms multiple linear regressions for predictingpCO2. Further, the model provides estimates of CO2contributions from internal versus external sources suggesting that streams transition from GW‐ to BHZ‐dominated sources between 3rd and 4th Strahler orders, with GW, BHZ, and WC accounting for 49.3%, 50.6%, and 0.1% of CO2fluxes from the watershed, respectively. Lastly, stream network model atmospheric CO2fluxes are 4‐12x times smaller than upscaling technique predictions, largely due to relationships between streampCO2and gas exchange velocities. Taken together, this stream network model improves our ability to predict stream CO2dynamics and efflux. Furthermore, future applications to regional and global scales may result in a significant downward revision of global flux estimates.
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- Award ID(s):
- 2103520
- PAR ID:
- 10362044
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Global Biogeochemical Cycles
- Volume:
- 35
- Issue:
- 12
- ISSN:
- 0886-6236
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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