4.3 Article

Headwater gas exchange quantified from O2 mass balances at the reach scale

Journal

LIMNOLOGY AND OCEANOGRAPHY-METHODS
Volume 16, Issue 10, Pages 696-709

Publisher

WILEY
DOI: 10.1002/lom3.10281

Keywords

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Funding

  1. National Environmental Research Council (NERC) Macronutrient Cycles Programme [NE/J012106/1, NE/J011681/1, NE/J011738/1]
  2. European Research Council Advanced Investigator Grant [669947]
  3. European Union's Horizon 2020 research and innovation programme [678760]
  4. NERC [NE/J012106/1, NE/J011681/1, NE/F018614/1, NE/F012691/1]
  5. Commission for Scientific Research in Greenland (KVUG) [GCRC6507]
  6. Danish Council for Independent Research [FNU-12-125843]
  7. ERC Advanced Grant [ERC-2010-AdG_20100224]
  8. Danish National Research Foundation [DRNF53]
  9. NERC [NE/J011738/1, NE/J011681/1, NE/J012106/1] Funding Source: UKRI
  10. Natural Environment Research Council [NE/J011738/1] Funding Source: researchfish

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Headwater streams are important in the carbon cycle and there is a need to better parametrize and quantify exchange of carbon-relevant gases. Thus, we characterized variability in the gas exchange coefficient (k(2)) and dissolved oxygen (O-2) gas transfer velocity (k) in two lowland headwaters of the River Avon (UK). The traditional one-station open-water method was complemented by in situ quantification of riverine sources and sinks of O-2 (i.e., groundwater inflow, photosynthesis, and respiration in both the water column and benthic compartment) enabling direct hourly estimates of k(2) at the reach-scale (similar to 150 m) without relying on the nighttime regression method. Obtained k(2) values ranged from 0.001 h(-1) to 0.600 h(-1). Average daytime k(2) were a factor two higher than values at night, likely due to diel changes in water temperature and wind. Temperature contributed up to 46% of the variability in k on an hourly scale, but clustering temperature incrementally strengthened the statistical relationship. Our analysis suggested that k variability is aligned with dominant temperature trends rather than with short-term changes. Similarly, wind correlation with k increased when clustering wind speeds in increments correspondent with dominant variations (1 m s(-1)). Time scale is thus an important consideration when resolving physical drivers of gas exchange. Mean estimates of k(600) from recent parametrizations proposed for upscaling, when applied to the settings of this study, were found to be in agreement with our independent O-2 budget assessment (within < 10%), adding further support to the validity of upscaling efforts aiming at quantifying large-scale riverine gas emissions.

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