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

Abstract

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 ~ 1300m in the GSS. Spatially, the pCO2 and CO2 emissions decrease sharply from the stream head (mean 8818.4μatm for pCO2 and mean 423.4mgm-2h-1 for CO2 emission) to the site farthest downstream (mean 2752.7μatm for pCO2 and 257.0mgm-2h-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 21.75tCO2/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.