Transport / flooding

The flooding risk analysis pipeline starts by creating an infrastructure network (road or rail) as described previously. Please refer to this section to configure the network creation.

Description

The pipeline has the following core steps:

  1. Download the raster files for the hazard dataset.
  2. Crop the raster files to the extent of the network in question.
  3. Split the network edges on the raster grid, so no edge resides in more than one pixel.
  4. Find the pixel value / hazard intensity (e.g. flood depth) for every hazard raster, for each split edge.
  5. For each asset type (e.g. unpaved road) where a damage curve is defined, calculate the damage fraction for each split edge, for each raster.
  6. Using rehabilitation cost estimates, calculate the expected monetary loss due to the calculated damage fraction.
  7. Concatenate the previously split edges, summing the expected monetary loss.
  8. Given hazard rasters at various return periods, calculate the Expected Annual Damages (EAD).
  9. Aggregate EAD to desired regional level.

Configuration

The hazard component of the analysis is configurable in config/config.yaml:

  • hazard_datasets contains hazard names pointing to files of hazard layers. These layers are currently flood rasters (inundation depths for a given return period). Add or amend an entry pointing to file containing the rasters you wish to consider.
  • Ensure hazard_types contains an identical key referencing the hazard types. This is currently limited to flood only.
  • Configure the damage curves:
    • Check and amend direct_damages.asset_types contains any assets you wish to calcuate direct damage costs for. Currently implemented assets are available in src/open_gira/assets.py as the classes inheriting from Assets.
    • Ensure direct_damages.curves_dir is set to a path containing damages functions per asset type, organised by hazard type. See bundled_data/damage_curves for an example.
    • These damage function files should be named <asset_type>.csv, e.g. road_unpaved.csv. Their format is exemplified by bundled_data/damage_curves/flood/road_unpaved.csv

Outputs

Rasterised network (per slice)

To generate a network, split by the hazard raster grid we might issue something like:

snakemake --cores all -- results/splits/<dataset_name>_filter-<network_type>/hazard-<hazard_name>/slice-<slice_number>.geoparquet

For the egypt-latest OSM dataset, road network, aqueduct-river hazard set and slice 0, that would be:

snakemake --cores all -- results/splits/egypt-latest_filter-road/hazard-aqueduct-river/slice-0.geoparquet

Expected Annual Damages (per slice)

To request an evaluation of Expected Annual Damages (EAD) as a function of hazard Return Period (RP) for a given slice, we can request something like:

For example (with a config.slice_count of 9):

snakemake --cores all -- results/direct_damages/egypt-latest_filter-road/hazard-aqueduct-river/EAD_and_cost_per_RP/slice-5.geoparquet

Expected Annual Damages (per admin region)

And to compute all the slices for a given domain and then aggregate to country level (admin level 0):

snakemake --cores all -- results/egypt-latest_filter-road/hazard-aqueduct-river/EAD_and_cost_per_RP/agg-sum/admin-level-0.geoparquet

For more possible outputs please refer to the detailed documentation and the rules defined in workflow/rules/.