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- Kokic, Jovana, et al.
(author)
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High spatial variability of gas transfer velocity in streams revealed by turbulence measurements
- 2018
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In: Inland Waters. - : Taylor & Francis. - 2044-2041 .- 2044-205X. ; 8:4, s. 461-473
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Journal article (peer-reviewed)abstract
- Streams are major sources of carbon dioxide (CO2) and methane (CH4) to the atmosphere, but current large-scale estimates are associated with high uncertainties because knowledge concerning the spatiotemporal control on stream emissions is limited. One of the largest uncertainties derives from the choice of gas transfer velocity (k(600)), which describes the physical efficiency of gas exchange across the water-atmosphere interface. This study therefore explored the variability in k(600 )and subsequent CO2 and CH4 emission rates within and across streams of different stream order (SO). We conducted, for the first time in streams, direct turbulence measurements using an acoustic Doppler velocimeter (ADV) to determine the spatial variability in k(600) across a variety of scales with a consistent methodology. The results show high spatial variability in k(600) and corresponding CO2 and CH4 emissions at small spatial scales, both within stream reaches and across SO, especially during high discharge. The k(600) was positively related to current velocity and Reynolds number. By contrast, no clear relationship was found between k(600) and specific stream characteristics such as width and depth, which are parameters often used in empirical models of k(600). Improved understanding of the small-scale variability in the physical properties along streams, especially during high discharge, is therefore an important step to reduce the uncertainty in existing gas transfer models and emissions for stream systems. The ADV method was a useful tool for revealing spatial variability in this work, but it needs further development. We recommend that future studies conduct measurements over shorter time periods (e.g., 10-15 min instead of 40 min) and at more sites across the reach of interest, and thereby derive more reliable mean-reach k(600) as well as more information about controls on the spatial variability in k(600).
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