PRMS
USGS Precipitation-Runoff Modeling System — distributed continuous simulation with strong snow physics.
A flexible hydrological modelling framework — emulate GR4J, HBV, HMETS or build your own model structure.
by University of Waterloo
Raven, from the University of Waterloo, treats model structure as user input: instead of shipping one fixed conceptual model, it lets you assemble process representations (infiltration, baseflow, snow, routing) into whatever structure the catchment demands — and it ships templates that emulate GR4J, HBV-EC, HMETS, UBCWM and others.
That flexibility makes Raven popular for research and for operational forecasting in Canada, where it drives several flood-forecast systems. It is fast C++ with clean text input, active development and a growing Python ecosystem (RavenPy) for scripted workflows.
Ranked by the topics, categories and workflow stages they share with Raven.
USGS Precipitation-Runoff Modeling System — distributed continuous simulation with strong snow physics.
Deltares' distributed hydrological model in Julia — gridded rainfall-runoff with kinematic-wave routing.
The open global large-sample hydrology dataset — thousands of catchments with forcing, attributes and streamflow.
Deep-learning rainfall-runoff modelling — the LSTM framework behind much of ML hydrology research.
Python automation for HEC-HMS — batch and parallel runs, design storms, and DSS handoff to HEC-RAS.
Deltares' Python framework that builds ready-to-run hydrological models from global and local datasets.