Abstract
Inland waters are an important component of the global carbon budget,
emitting CO2 to the atmosphere. However, our ability to
predict carbon fluxes from stream systems remains uncertain as small
scales of pCO2 variability within streams
(100-102 m), which makes efforts
relying on monitoring data uncertain. We incorporate CO2
input and output fluxes into a stream network advection-reaction model,
representing the first process-based representation of stream
CO2 dynamics at watershed scales. This model includes
groundwater (GW) CO2 inputs, water column (WC), and
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 stream pCO2 data
collected across the East River Watershed in the Colorado Rocky
Mountains (USA). The stream network model accurately captures
topography-driven pCO2 variability and significantly
outperforms multiple linear regressions for predicting
pCO2. Further, the model provides estimates of
CO2 contributions 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
CO2 fluxes from the watershed, respectively. Lastly,
stream network model CO2 fluxes are 4-12x times smaller
than upscaling technique predictions, largely due to inverse
correlations between stream pCO2 and atmosphere exchange
velocities. Taken together, this stream network model improves our
ability to predict stream CO2 dynamics and efflux.
Furthermore, future applications to regional and global scales may
result in a significant downward revision of global flux estimates.