Roches Beach coastal hazard probabilistic assessment

Workflow

1. Open anaconda prompt.

Double-click anaconda-prompt.bat
(All further commands should be entered into this prompt)

2. Generate ZSA and ZRFC recession tables.

The package required to calculate setbacks based on Nielsen et al. (1992) can be found here:
http://git.wrl.unsw.edu.au:3000/coastal/nielsen

  > cd lidar  
  > python generate_recession_tables.py

The setback chainages are saved here:

lidar/
├── recession_results_zrfc.csv
└── recession_results_zsa.csv

The profile cross-sections are plotted here:

lidar/
└── png
    ├── P1.png
    ├── P2.png
    └── ...

3. Prepare input files

Update values in adopted-input-values.xlsx
Generate yaml files:

  > cd ../inputs
  > python get_adopted_input_values.py

The yaml files are saved here:

probabilistic-analysis/
├── Roches P1.yaml
├── Roches P2.yaml
└── ...

4. Run probabilistic simulation

  > cd ../probabilistic-analysis
  > python probabilistic_assessment.py

Chainage setbacks are saved in csv files, and diagnostics are saved in csv/png files here:

probabilistic-analysis/
└── output_csv
│   ├── Roches P1 2022 ZRFC.csv
│   ├── Roches P1 2022 ZSA.csv
│   ├── Roches P1 2050 ZRFC.csv
│   └── ...
└── diagnostics
    ├── Roches P1 2022 ZRFC.csv
    ├── Roches P1 2022 ZSA.csv
    ├── Roches P1 ZRFC scatter.png
    ├── Roches P1 ZRFC timeseries.png
    └── ...

5. Generate hazard line shapefile

  > cd ../probabilistic-analysis
  > python csv_to_shp.py

Shapefile is saved here:

probabilistic-analysis/
└── output_shp
    ├── hazard-lines.dbf
    ├── hazard-lines.prj
    └── hazard-lines.shp

6. Export maps

  > cd ../qgis
  > export.bat