Global integrated modeling framework of riverine dissolved inorganic nitrogen with seasonal variation
Yizhou Huang, Daisuke Tokuda, Xudong Zhou, Taikan Oki
Received 2021/03/09, Accepted 2021/05/22, Published 2021/07/15
Yizhou Huang1)2), Daisuke Tokuda2), Xudong Zhou2), Taikan Oki3)4)
1) Department of Multidisciplinary Science, Graduate School of Arts and Sciences, The University of Tokyo, Japan
2) Institute of Industrial Science, The University of Tokyo, Japan
3) Department of Civil Engineering, Graduate School of Engineering, The University of Tokyo, Japan
4) Rector’s Office, United Nations University, Japan
Understanding patterns and seasonal variations of excessive nutrients in surface water from anthropogenic activities is important for pollution control. In this study, we developed an integrated biogeochemical modeling framework for nitrogen exchanges among the atmosphere, terrestrial, and aquatic ecosystems. A land surface model, a terrestrial nitrogen cycle model, and a riverine hydrodynamics model incorporated with a river temperature model were consolidated and driven by multiple nitrogen sources related to anthropogenic activities. We estimated the global nitrogen loading and transporting in global rivers, with consideration of seasonal variations, and the validation demonstrates the reliability of the proposed model. The total dissolved inorganic nitrogen (DIN) flow rate is accumulated following rivers and it has high total DIN loads even in regions with low population density but large basin area, such as those at high latitudes. This study successfully improves estimation of nitrogen loading on global scale with consideration of seasonal variation. Our results show consistent trends with the observed data of DIN concentrations in global rivers, where all above variables are greatly affected by seasonal variations. The results also reflect the monthly-variant nitrogen inputs help produce closer DIN concentration estimates to observations, which will possibly stress the need for further study on seasonal variability of anthropogenic emissions.
Copyright (c) 2021 The Author(s) CC-BY 4.0