Critical Loads (DSToolkit workflow)

Improved data handling for the Critical Loads project. All core datasets are now centralised on the JupyterHub/Data Science Toolkit.

Key datasets include:

• Atmospheric deposition of N and S supplied by NILU using a 0.1 degree resolution grid

• Raster vegetation data with a cell resolution of 30 m

• Water- and soil-related parameters, aggregated to the level of the old "BLR" grid

Exceedances of critical loads are calculated following the method described by the Manual for Modelling and Mapping Critical Loads & Levels (see especially Chapter 5).

To make it easier to update and re-calculate critical loads for water, an Excel template is also available here. This can be used in conjunction with the Python function here to estimate critical loads for any sites/catchments/regions of interest.

Workflow

1. Data migration to the DSToolkit. Migrate all relevant datasets from NIVA's internal servers to a new database structure on the JupyterHub/DSToolkit

2. Deposition. Process deposition datasets from NILU, supplied using the 0.1 degree grid

3. Vegetation. Workflow for calculating exceedances of critical loads for vegetation using the 0.1 degree deposition data and raster land cover

4. Water. Workflow for calculating exceedances of critical loads for water using the 0.1 degree deposition data and two different exceedance models (SSWC and FAB)

5. Soil. Workflow for calculating exceedances of critical loads for soil using the 0.1 degree deposition data and the "old" (BLR-based) soil critical loads

Development code

• Prototype data migration. Initial migration of key project datasets into a Dockerised PostGIS workflow