Storage and Transit Time Data and Code

Author: Andrew J. Felton
Date: 7/11/2023

This R project contains the primary code and data used for data production, manipulation,
and analysis and figure production for the study entitled:

"Global estimates of the storage and transit time of water through vegetation"

Please note that 'turnover' and 'transit' are used interchangeably in this project.

Data information:

The data folder contains key data sets used for analysis. In particular:

"data/turnover_from_python/annual/annual_turnover.nc" contains a global array
summarizing annual transit, storage, canopy transpiration, and number of
months of data. This data is also available is separate .csv files for each land
cover type. The same can be found for the minimum, monthly, and seasonal transit
time found in their respective folders. These data were produced using the python
code found in the "supporting_code" folder. The remaining files in the "data" and
"data/supporting_data"" folder primarily contain ground-based estimates of
storage and transit found in public databases or through a literature search.

#Code information

Python scripts can be found in the "supporting_code" folder.

Each R script in this project has a particular function:

01_start.R: This script loads the R packages used in the analysis, sets the
directory, and imports the user-created functions for the project in the 

02_functions.R script. This script can also download the annual and minimum 
transit datasets, which are core to the analyses.

03_generate_data.R This script is not necessary to run and is primarily
for documentation. The main role of this code was to import and wrangle
the data needed to calculate ground-based estimates of aboveground water storage.

04_annual_turnover_storage_import.R: This script imports the annual turnover and
storage data for each landcover type.

05_minimum_turnover_storage_import.R: This script imports the minimum turnover and
storage data for each landcover type. Minimum is defined as the lowest monthly
estimate.

06_figures_tables.R: This is the main workhouse. This script generates the key 
figures and summary statistics used in the study that the get saved in the 
manuscript_figures folder. Maps were produced using Python code found in the
"supporting_code"" folder