pcse_notebooks: A Jupyter Notebook repository from decorouz

A collection of PCSE notebooks

This repository provides a set of notebooks that demonstrates various aspects of PCSE models.

The notebooks include introductory examples:

01 Getting Started with PCSE.ipynb provides an impression of how PCSE works and what you can do with it
02 Running with custom input data.ipynb shows how you can run a model using your own input data instead of the demonstration data.
03 running_LINTUL3.ipynb a similar example, but instead using the LINTUL3 model instead of WOFOST.
04 Running PCSE in batch mode.ipynb demonstrates how to run PCSE simulation in batch for a series of crops and year
13 Simulating grassland productivity with LINGRA demonstrates the LINGRA model for simulating productivity of grasslands

Some more advanced features of PCSE are demonstrated in:

05 Using PCSE WOFOST with a CGMS8 database.ipynb this shows how to retrieve data from a CGMS database and run crop model simulations with WOFOST using that data.
06_advanced_agromanagement_with_PCSE.ipynb demonstrates advanced aspects of the agromanagement definitions including scheduling events based on date and state variables.
07 Running crop rotations.ipynb provides insight on how to run crop rotations with PCSE models.

Finally, highly advanced subjects are treated that require quite some background knowledge and python programming skills:

08a_data_assimilation_with_the_EnKF.ipynb provides an introduction to data assimilation with the ensemble Kalman filter.
08b_data_assimilation_with_the_EnKF_Multitate.ipynb demonstrates how to effectively load multiple states into the EnKF state vector.
09 Optimizing parameters in a PCSE model.ipynb demonstrates how to do parameter optimizations in PCSE.
10 Sensitivity analysis of WOFOST demonstrates how to use SAlib for sensitivity analysis

Using these notebooks generally require a python environment that includes the following packages: