Coupling process-based models with machine learning for the prediction of soil carbon and nitrogen cycling

Xiang Zhang

doi:10.1016/j.envsoft.2026.107089

Coupling process-based models with machine learning for the prediction of soil carbon and nitrogen cycling

2026-06-20

0

PRE

AI

X

Xiang Zhang

L

Liman Wei

C

Changming Yang

T

Tian Li *

Q

Qixing Zhou *

DOI：10.1016/j.envsoft.2026.107089

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Abstract

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1. GNNs identified as critical, underutilized tool for spatial soil modeling 2. Hybrid models systematized into parallel, sequential, and integrated modes 3. Causal AI and foundation models proposed to tackle black-box and data limits

Coupling process-based models with machine learning for the prediction of soil carbon and nitrogen cycling

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