Welcome to eWaterCycle-DataAssimilation’s documentation!

eWaterCycle-DA is a python package which adds data assimilation functionality to the eWaterCycle platform.

More info to be added…

There are two ways in this package of running data assimilation. The easiest & most user friendly is method 1 where you define the parameters used in DA upfront.

The more advanced, but more powerful is method 2 where you define the parameters used in DA as you go. You can run the model, then decide to assimilate on the go.

The added benefit of this model structure is that the package can also be used for ensembles which don’t assimilate, like a collection of model comparisons:

Contents:

• 1. Example running HBV for particle filter pre defining DA parameters (WIP)
  • setup packages
  • set up paths
  • Add parameter info
  • Forcing
  • Import observations
  • setup DA
  • Run algorithm
  • Plotting
• 2. Example running HBV for particle filter defining DA parameters on the go (WIP)
  • setup packages
  • set up paths
  • Add parameter info
  • Forcing
  • Import observations
  • setup DA
  • Run algorithm
  • Plotting
• Example running HBV for EnKF (WIP)
  • setup packages
  • set up paths
  • Add parameter info
  • Forcing
  • setup model
  • Import observations
  • setup DA
  • Run algorithm
  • Plotting
• Ensemble without assimilating
  • Marrmot
• Tutorial: Implementing your own Data Assimilation Scheme
• API Reference
  • ewatercycle_DA