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Full Title

Deriving a Production Rate Map of Dissolved Organic Carbon over the Contiguous U.S.

First Author

All Authors

Lingbo Li , Guta Abeshu, Jinyun Tang , Ruby Leung , Chang Liao, Zeli Tan , Hanqin Tian, Peter Thornton , Xiaojuan Yang

Topic

‘Land Land - River - Human’Human

Project

E3SM

Abstract

Dissolved organic carbon (DOC), primarily sourced from soil organic carbon (SOC), plays a vital role in regional and global carbon cycles. However, the representation of DOC conversion from SOC and leaching into rivers is still rare in land surface and earth system models. Existing process-based models often involve a plethora of complex processes that require the parameterization of numerous model parameters. This results in a computationally intensive task that makes it challenging to transfer these models to regional and global scales. As a first attempt to fill this modeling gap, we propose a single parameter, DOC production rate , to account for the processes governing SOC conversion to DOC and leaching from land (along with runoff) into headwater streams. We then derive a  map over the contiguous U.S. in five major steps: 1) selecting over 2500 headwater catchments where observed riverine DOC data are available with reasonable quality; 2) estimating catchment-average SOC for these headwater catchments based on the 1km-resolution SOC data from Harmonized World Soil Database Version 1.2 (HWSD v1.2); 3) estimating the  values for these 2500 catchments; 4) developing a predictive model of  by utilizing artificial intelligence (AI) techniques and catchment-scale climate, hydrology, geology and other attributes retrieved from the National Hydrography Dataset Plus (NHDPlus) dataset; and 5) deriving a national map of , based on the AI model (after cross-validation) and NHDPlus. The resulting  map lays a critical cornerstone for improving large-scale riverine carbon cycle modeling and prediction of the carbon budget at the regional and global scales.

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nameE3SM_DOC_Lingbo_final.pptx

Discussion Link

hli57@uh.edu

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