Evaluation of Boundless Biogeochemical Cycle through Development of Process-Based Eco-Hydrological and Biogeochemical Cycle Model to Incorporate Terrestrial-Aquatic Continuum

Abstract:

Inland water might act as important transport pathway for continental biogeochemical cycle although its contribution has remained uncertain yet due to a paucity of data (Battin et al. 2009). The author has developed process-based National Integrated Catchment-based Eco-hydrology (NICE) model (Nakayama, 2008a-b, 2010, 2011a-b, 2012a-c, 2013; Nakayama and Fujita, 2010; Nakayama and Hashimoto, 2011; Nakayama and Shankman, 2013a-b; Nakayama and Watanabe, 2004, 2006, 2008a-b; Nakayama et al., 2006, 2007, 2010, 2012), which incorporates surface-groundwater interactions, includes up- and down-scaling processes between local-regional-global scales, and can simulate iteratively nonlinear feedback between hydrologic-geomorphic-ecological processes. Because NICE incorporates 3-D groundwater sub-model and expands from previous 1- or 2-D or steady state, the model can simulate the lateral transport pronounced at steeper-slope or riparian/floodplain with surface-groundwater connectivity. River discharge and groundwater level simulated by NICE agreed reasonably with those in previous researches (Niu et al., 2007; Fan et al., 2013) and extended to clarify lateral subsurface also has important role on global hydrologic cycle (Nakayama, 2011b; Nakayama and Shankman, 2013b) though the resolution was coarser. NICE was further developed to incorporate biogeochemical cycle including reaction between inorganic and organic carbons in terrestrial and aquatic ecosystems. The missing role of carbon cycle simulated by NICE, for example, CO2 evasion from inland water (global total flux was estimated as about 1.0 PgC/yr), was relatively in good agreement in that estimated by empirical relation using previous pCO2 data (Aufdenkampe et al., 2011; Laruelle et al., 2013). The model would play important role in identification of greenhouse gas balance of the biosphere and spatio-temporal hot spots, and bridging gap between top-down and bottom-up approaches (Cole et al. 2007; Frei et al. 2012).