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A cross-scale modeling framework of organic matter biochemistry in river corridor system: Scaling biogeochemical reaction kinetics from molecular to reach scales


EMSL Project ID
51917

Abstract

Predicting the decomposition of organic matter in biochemical processes driven by microbes at reach scale remains challenging. These challenges are deeply rooted in the scarcity of rate measurements and non-transferability of reaction kinetic variables. Here we propose to develop a machine-learning informed multiscale modeling framework across the molecular, cell and reach scales that comprised of a machine-learning model for reaction free energy prediction at molecular scale, a biogeochemical thermodynamic-kinetic model at cell scale and a macroscopic hydrodynamics model at reach scale. Combining realistic riverbed topography from field surveys, the hydrodynamic component can predict the microbially driven fluxes of various organic matters and their decomposition products across mm to km scales in river corridors. And the machine-learning aided biogeochemical thermodynamic-kinetic model is essentially independent of kinetic parameters in traditional biogeochemical kinetic model. The integrated model can be used to investigate the cycling of organic matters and their decomposition products between surface water and soil. Our work will open up new ways for linking the processes at macroscale with reach scales without knowledge of kinetic parameters and without laborious chemical profile measurements.

Project Details

Project type
Large-Scale EMSL Research
Start Date
2021-10-01
End Date
2023-09-30
Status
Closed

Team

Principal Investigator

Peiyuan Gao
Institution
Pacific Northwest National Laboratory

Team Members

Jing Li
Institution
Pacific Northwest National Laboratory

Jianqiu Zheng
Institution
Pacific Northwest National Laboratory

Yunxiang Chen
Institution
Pacific Northwest National Laboratory

Jie Bao
Institution
Pacific Northwest National Laboratory

Xuehang Song
Institution
Pacific Northwest National Laboratory

Yilin Fang
Institution
Pacific Northwest National Laboratory