Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 30, issue 21
Articles | Volume 30, issue 21
https://doi.org/10.5194/hess-30-6843-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-6843-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 21
Research article
 | 
09 Nov 2026
Research article |  | 09 Nov 2026

A physically integrated GNN surrogate for microbially-mediated kinetic reactive transport: PHYGNET

Jinbo Wang, Kunfeng Zhang, Walter Illman, Shuai Chen, and Mingzhu Liu

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Short summary
PHYGNET, a physical AI model, designed to accelerate microbial reactive transport simulations. This new approach is over 3500 times faster than traditional methods and handles complex, large-scale simulations without crashing. By allowing "small-sample training, ultra-large-scale inference", it cuts weeks of environmental modeling work down to hours, making it practical for real-world cleanup and risk assessment projects.
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