The Greenhous Gas (GHG) emissions from inland waters (rivers, lakes, and reservoirs) remain largely uncertain at the global and continental scales. However, most of the large-scale estimates of GHGs from inland waters used empirical-based approaches, which lacks of the mechanistic representation of the physical and biogeochemical processes within terrestrial and aquatic ecosystems. Inspired this significant knowledge and technical gaps, a newly developed scale adaptive water transport model was incorporated into the Dynamic Land Ecosystem Model (DLEM) to better represent the coupled terrestrial and aquatic system, river routing, and the associated biogeochemical processes. Based on the advanced modeling framework, we developed the first process-based model that is capable of concurrently estimating CO2, CH4, and N2O emissions from inland waters. Here, we used Chesapeake Bay watershed as a testbed for testing the performance of the coupled model in simulating hydrological processes, river temperature and carbon dynamics at the land-aquatic continuum. Then we applied the coupled model to the Conterminous United States (CONUS) and the global level. Thanks to the fully process-based nature of our model, we examined how multiple changes in climate, land use/land cover, elevated CO2, nitrogen deposition and nitrogen fertilizer use that can affect the GHG emissions from inland water and the relative role of high-order streams and headwater streams in the continental carbon budget for the time period from 1860 to 2018. Our simulation results show that the emissions of CO2, CH4, and N2O from inland waters increased significantly from the pre-industry period to the recent decade. We also found that, small streams have much higher emission rate of GHGs than that of the large rivers. The total of GWP of the three GHG emissions from inland waters over the CONUS was quantified, which is comparable to a quarter of the terrestrial carbon sink over CONUS.
 

climate change, carbon export, watershed model