oreopie/hydro-interpretive-dl
Interpretive deep learning for identifying flooding mechanisms
This project helps hydrologists and water resource managers understand the specific causes of flooding. By analyzing historical daily precipitation, temperature, and river discharge data, it identifies the key factors and mechanisms that lead to flood events. The output provides interpretable insights into why certain floods occurred, aiding in better flood prediction and management strategies.
No commits in the last 6 months.
Use this if you need to understand the underlying hydrological processes contributing to flooding, rather than just predicting when floods might occur.
Not ideal if you are looking for a simple flood forecasting tool without needing detailed explanations of the mechanisms involved.
Stars
22
Forks
7
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jul 11, 2024
Commits (30d)
0
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