Caravan
The open global large-sample hydrology dataset — thousands of catchments with forcing, attributes and streamflow.
Deltares' operational forecasting platform — the shell running national flood-forecast centres worldwide.
by Deltares
Delft-FEWS is not a model but the operational system around models: it ingests real-time observations and NWP forecasts, runs any model chain (HEC-RAS, Wflow, SWMM, MIKE, custom binaries) on schedule, manages state and ensembles, and presents forecasters with a unified interface with alarms and dissemination. National services — the UK, Australia, the US National Water Model display chain, Rhine and Meuse authorities — run on it.
Licensing is unusual: free to use with paid support and setup typically via Deltares. Adopting FEWS is an infrastructure decision rather than a download, but nothing else in operational hydrology matches its install base.
Ranked by the topics, categories and workflow stages they share with Delft-FEWS.
The open global large-sample hydrology dataset — thousands of catchments with forcing, attributes and streamflow.
Near-real-time scatterometer soil moisture from EUMETSAT — hours of latency, useful for operational monitoring.
Deep-learning rainfall-runoff modelling — the LSTM framework behind much of ML hydrology research.
An open-source take on Google Flood Hub — per-gauge neural network streamflow forecasting you can self-host.
NOAA's modelled snow depth and SWE for the CONUS — 1km daily grids from satellite, airborne and station data.
Planetary-scale geospatial analysis in the cloud — the data catalogue and compute behind modern water remote sensing.