Open source hydrology modeling framework for flood forecasting
Google's open-sourced hydrology model framework for AI-based flood forecasting.
A Python package implementing a river forecast model using PyTorch and LSTM networks.
Enabling National Meteorological and Hydrological Services to integrate advanced AI-based flood forecasting into their workflows, allowing researchers and forecasters to train models with similar architecture and data as Google's Flood Hub.
Free
https://github.com/google-research-datasets/caravan
Google has open-sourced its hydrology modeling framework, built with PyTorch and LSTM networks. This Python package allows researchers and forecasters to train AI flood forecasting models using similar architectures and data as Google's Flood Hub, empowering local experts to refine models with specialized datasets.
It allows researchers and forecasters to train AI flood forecasting models with the same architecture and similar training data to what is used to power riverine flood forecasts on Google’s Flood Hub. It is developed to allow hydrological scientists to build on what we have done at Google Research by adding and testing new models, data, and approaches.
- The next chapter in flood resilience: Open sourcing Google’s hydrology framework ↗Google Research · Google Research Blog · Jun 3, 2026 · paraphrased
First seen on Subvolts Jun 3, 2026. Updated Sep 11, 2026. Spotted a problem? Tell us.
- The next chapter in flood resilience: Open sourcing Google’s hydrology frameworkGoogle · Google Research Blog · Jun 3, 2026
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
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Questions people ask
- Which AI tools does this work with?
- Any current model. It was seen with in the sources.
- Where did this come from?
- Google Research (Google Research Blog). Subvolts collected, normalized and credited it; the link above opens the original.