Scaled-dependence and seasonal variations of carbon cycle through development of an advanced eco-hydrologic and biogeochemical coupling model

Abstract

Recent research has shown that inland water may play some role in carbon cycling, although the extent of its contribution has remained uncertain due to the limited amount of reliable data available. In this study, the author developed a new model coupling original eco-hydrology model and five biogeochemical cycle models (NICE-BGC), which incorporates complex coupling of hydrologic-carbon cycle in terrestrial-aquatic linkages and interplay between inorganic and organic carbon during the whole process of carbon cycling. This improved model was applied to Eurasian wetland by using three types of river network data to evaluate scaled-dependence of carbon cycle there. The model improved accuracy of low pH and alkalinity and DOC flux increase in the wetland in the northern part of study area with the finer river network data. The model showed that the difference in the carbon flux between different river network data becomes larger in downstream region, and that this difference is more predominant in the stream channel than in the hillslope, implying the importance of dry watercourses and intermittent rivers. The model was then extended to the global scale to evaluate seasonal variations of carbon cycle both in hillslope and river. The result extended from the previous studies to clarify that; (i) soil temperature has some effect on the carbon transport by biologic process responsible for carbon production in addition to clear relationship between runoff and carbon export, (ii) the high runoff during April to June and the large DOC and POC flux (about 458.38±474.41 TgC/season and 239.25±289.90 TgC/season) during January to March in hillslope, (iii) CO2 evasion becomes maximum about 294.66±93.80 TgC/season during January to June primarily affected by Amazon River, and (iv) sediment storage is larger and takes about 76.80±13.19 TgC/season during July to September particularly in Asian and North American rivers. This scaled-dependence and seasonal variations of carbon cycle helps to bridge the gap between carbon transport to the longitudinal direction and gas emission to the atmosphere in previous researches. This simulation system would also help for the further field observations, remotely-sensed imagery, and satellite datasets, and play important role in improvement in biogeochemical activity in spatio-temporal hot spots.