Caravan
The open global large-sample hydrology dataset — thousands of catchments with forcing, attributes and streamflow.
Python toolbox for calibrating and uncertainty-analysing any environmental model — SCE-UA, DREAM, GLUE and more.
Install
pip install spotpySPOTPY (Statistical Parameter Optimization Tool for Python) wraps a model — any model you can call from Python — in a consistent interface and throws a library of algorithms at its parameters: SCE-UA, DREAM, Monte Carlo, Latin hypercube, GLUE, simulated annealing and more, with likelihood and objective-function utilities included.
For hydrologists it is the pragmatic route to defensible calibration and uncertainty bounds without writing samplers from scratch. If your rainfall-runoff model runs from a function call, SPOTPY can calibrate it this afternoon.
Ranked by the topics, categories and workflow stages they share with SPOTPY.
The open global large-sample hydrology dataset — thousands of catchments with forcing, attributes and streamflow.
Jupyter notebook suite for batch HEC-RAS and HEC-HMS runs — parallel execution and calibration statistics.
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.
USGS Precipitation-Runoff Modeling System — distributed continuous simulation with strong snow physics.
Python water-resource network simulator — fast LP-based allocation for reservoir systems and supply networks.