ASCAT Soil Moisture (H SAF)
Near-real-time scatterometer soil moisture from EUMETSAT — hours of latency, useful for operational monitoring.
8 tools · Topic
Operational forecasting has escaped the agency basement: open frameworks now cover data assimilation, ensemble hydrology and ML-based prediction. This page collects forecasting frameworks, national-model interfaces and the ML packages pushing the field.
Near-real-time scatterometer soil moisture from EUMETSAT — hours of latency, useful for operational monitoring.
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.
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.
A flexible hydrological modelling framework — emulate GR4J, HBV, HMETS or build your own model structure.
NOAA's modelled snow depth and SWE for the CONUS — 1km daily grids from satellite, airborne and station data.
Deltares' distributed hydrological model in Julia — gridded rainfall-runoff with kinematic-wave routing.