mhpi/hydrodl2
Repository for MHPI differentiable hydrological models.
This project provides pre-built, physics-informed hydrological models that can be integrated into larger differentiable modeling workflows. It takes in various hydrological inputs like precipitation and temperature and outputs simulated water flow, enabling advanced analysis. Hydrologists, environmental scientists, and water resource managers can use these models to improve predictions, correct biases, and understand missing processes.
Available on PyPI.
Use this if you are a researcher or practitioner in hydrology looking to incorporate advanced, differentiable hydrological models (like HBV variants) into your machine learning pipelines for improved parameter learning or bias correction.
Not ideal if you are looking for a standalone, ready-to-use application for direct hydrological forecasting without needing to integrate with other differentiable machine learning frameworks.
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Language
Python
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Last pushed
Feb 09, 2026
Commits (30d)
0
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