HEC-HMS
The US Army Corps standard for rainfall-runoff modelling — event and continuous simulation, free to use.
Stochastic storm transposition in Python — probabilistic extreme rainfall scenarios from remote-sensing data.
by University of Wisconsin-Madison
RainyDay, from Daniel Wright's Hydroclimate Extremes Group (University of Wisconsin-Madison), implements stochastic storm transposition: it resamples and spatially transposes observed storms from gridded rainfall archives to synthesise thousands of plausible extreme-rainfall realisations over your watershed — rainfall frequency analysis built from real storm structures rather than point statistics and area-reduction factors.
The approach shines exactly where design-storm convention is weakest: large watersheds, rare recurrence intervals and physically realistic space-time storm structure for 2D models. It underpins a growing body of probabilistic flood work, including FEMA-adjacent probabilistic frameworks, and remains the reference open implementation of SST.
Other hydrology & catchment analysis tools covering similar workflow stages.
The US Army Corps standard for rainfall-runoff modelling — event and continuous simulation, free to use.
FAO's classic tool for crop water requirements and irrigation scheduling from climate and crop data.
Browser-based rainfall frequency analysis — fit and rank 11 distributions with confidence intervals.
Statistical hydrology from HEC: Bulletin 17C flood frequency, volume-duration and general frequency analysis.
Deltares' Python framework that builds ready-to-run hydrological models from global and local datasets.
DHI's integrated hydrological model — coupled overland, unsaturated, groundwater and channel flow.