Version 1.0.0: Initial public release

Initial public release of the code for base modeling, pretraining, ensemble learning, and process-guided loss design for lake water temperature prediction in Lake Mendota.

This repository includes:

• Base model training and evaluation
• Pretraining on GLM simulation data and finetuning on observations
• Depth-wise ensemble modeling
• Process-guided loss with energy conservation constraint
• GLM simulation scripts
• Monthly energy balance validation scripts

Notes:

• The repository was developed primarily for Google Colab + Google Drive.
• The current implementation is intended mainly for comparative evaluation across model settings.
• Some paths may need to be adapted for a different local or cloud environment.

Citation:
Please cite this repository using the information provided in CITATION.cff.