Development of Advanced Eco-hydrologic and Biogeochemical Coupling Model to Re-evaluate Greenhouse Gas Budget of Biosphere

Abstract:

Inland waters including rivers, lakes, and groundwater are suggested to act as a transport pathway for water and dissolved substances, and play some role in continental biogeochemical cycling (Cole et al., 2007; Battin et al., 2009). The authors have developed process-based National Integrated Catchment-based Eco-hydrology (NICE) model (2014, 2015, etc.), which includes feedback between hydrologic-geomorphic-ecological processes. In this study, NICE was further developed to couple with various biogeochemical cycle models in biosphere, those for water quality in aquatic ecosystems, and those for carbon weathering. The NICE-biogeochemical coupling model incorporates connectivity of the biogeochemical cycle accompanied by hydrologic cycle between surface water and groundwater, hillslopes and river networks, and other intermediate regions. The model also includes reaction between inorganic and organic carbons, and its relation to nitrogen and phosphorus in terrestrial-aquatic continuum. The coupled model showed to improve the accuracy of inundation stress mechanism such as photosynthesis and primary production, which attributes to improvement of CH4 flux in wetland sensitive to fluctuations of shallow groundwater. The model also simulated CO2 evasion from inland water in global scale, and was relatively in good agreement in empirical relation (Aufdenkampe et al., 2011) which has relatively an uncertainty in the calculated flux because of pCO2 data missing in some region and effect of small tributaries, etc. Further, the model evaluated how the expected CO2 evasion might change as inland waters become polluted with nutrients and eutrophication increases from agriculture and urban areas (Pacheco et al., 2013). This advanced eco-hydrologic and biogeochemical coupling model would play important role to re-evaluate greenhouse gas budget of the biosphere, and to bridge gap between top-down and bottom-up approaches (Battin et al., 2009; Regnier et al., 2013).