High spatial and seasonal heterogeneity of pCO2 and CO2 emissions in a karst groundwater-stream continuum, southern China

Accurate quantification of the emission of CO₂ from streams and rivers is one of the primary challenges in determining the global carbon budget because our knowledge of the spatial and seasonal heterogeneity on these CO₂ emissions is limited. In karst areas, the groundwater-stream continuum is likely ubiquitous because the carbon-rich groundwater discharges into some of the streams through springs or subterranean streams, which results in more complex spatial and seasonal variations in the CO₂ emissions. To address this issue, the spatial and seasonal characteristics of partial pressure of CO₂ (pCO₂), the δ¹³CDIC, and the CO₂ emission flux of the Guancun surface stream (GSS) karst groundwater-stream continuum in southern China were investigated from the stream head (groundwater outlet) to the downstream mouth during the 2014–2017 period. Our results reveal that the pCO₂ and CO₂ emissions exhibit high spatial and seasonal heterogeneities over ~ 1300 m in the GSS. Spatially, the pCO₂ and CO₂ emissions decrease sharply from the stream head (mean 8818.4 μatm for pCO₂ and mean 423.4 mg m⁻² h⁻¹ for CO₂ emission) to the site farthest downstream (mean 2752.7 μatm for pCO₂ and 257.0 mg m⁻² h⁻¹ for CO₂ emission). Except for the dates when extreme rainfall occurred, the pCO₂ and CO₂ emission values were higher in the rainy season than in the dry season. This suggests that in a groundwater-stream continuum, CO₂ emission occurs very soon after the water is transferred from the karst groundwater to the surface water. We estimate that the total amount of CO₂ released to the atmosphere from the GSS is 21.75 t CO₂/year, which is only 1.71–5.62% of the dissolved inorganic carbon loss flux in the GSS during the study period. It is important to note that the measured CO₂ emission and pCO₂ levels decrease farther downstream, so carbon loss is underestimated when it is calculated using downstream sampling points. Therefore, accurate assessments of the CO₂ emission flux need to take into consideration the high spatio-temporal heterogeneity in order to reduce the bias of the entire CO₂ emission flux.