Open-source models, tools, and analysis workflows for hydrology, ecohydrology, and Earth system science.
HydrosHub hosts research software developed by the Machine Learning for Hydrological and Earth Systems group at the Max Planck Institute for Biogeochemistry. Our work combines machine learning with hydrological, ecological, and physical process knowledge to study water, energy, and carbon dynamics across land, atmosphere, and watershed systems.
🌿 ADELM |
🌱 MOREDO |
HydrosHub projects focus on hybrid and differentiable Earth system modeling, root-zone ecohydrology, soil-plant-atmosphere interactions, watershed hydrology, hydro-biogeochemistry, and land-atmosphere coupling.
These repositories provide code, analysis workflows, or reproducibility material associated with specific manuscripts.
| Repository | Associated study | Paper |
|---|---|---|
| aSrz hybrid model | Spatiotemporal dynamics of active root zone storage revealed from hybrid machine learning | Water Resources Research · Link |
| lateral TOC modelling | Hydroclimate controls when riverine organic carbon transport matters for terrestrial carbon accounting | Preprint available: link |
| transport-informed attribution model | Upwind terrestrial influences on soil moisture variability across South America | Nature Communications · Link |
Each repository contains its own documentation, environment information, license, and usage notes.
For questions, bugs, or suggestions, please open an issue in the relevant repository.
