Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 21
Articles | Volume 19, issue 21
https://doi.org/10.5194/gmd-19-10699-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-10699-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 21
Model description paper
 | 
11 Nov 2026
Model description paper |  | 11 Nov 2026

PLSTM-Reg v1.0: a regional physics-encoded LSTM model for simulating reservoir operations without site-specific training

Bin Yu, Yanan Chen, and Yi Zheng

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Short summary
We introduce a deep learning approach that extracts shared operating patterns from diverse, data-rich reservoirs and transfers this knowledge to limited-data reservoirs, yielding skillful simulations of storage and release. Using satellite observations, the model also reconstructs historical behavior in no-data reservoirs. Together, this work provide a scalable foundation for addressing pressing data gaps in reservoir operations and better supporting large-scale and long-term water management.
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