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# Roches Beach coastal hazard probabilistic assessment
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## Workflow
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#### 1. Open anaconda prompt.
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Double-click `anaconda-prompt.bat`
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(All further commands should be entered into this prompt)
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#### 2. Generate ZSA and ZRFC recession tables.
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The package required to calculate setbacks based on Nielsen et al. (1992) can be found here:
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http://git.wrl.unsw.edu.au:3000/coastal/nielsen
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```shell
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> cd lidar
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> python generate_recession_tables.py
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```
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The setback chainages are saved here:
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lidar/
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├── recession_results_zrfc.csv
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└── recession_results_zsa.csv
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The profile cross-sections are plotted here:
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lidar/
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└── png
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├── P1.png
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├── P2.png
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└── ...
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#### 3. Prepare input files
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Update values in `adopted-input-values.xlsx`
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Generate `yaml` files:
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```shell
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> cd ../inputs
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> python get_adopted_input_values.py
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```
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The `yaml` files are saved here:
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probabilistic-analysis/
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├── Roches P1.yaml
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├── Roches P2.yaml
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└── ...
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#### 4. Run probabilistic simulation
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```shell
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> cd ../probabilistic-analysis
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> python probabilistic_assessment.py
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```
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Chainage setbacks are saved in csv files, and diagnostics are saved in csv/png files here:
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probabilistic-analysis/
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└── output_csv
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│ ├── Roches P1 2022 ZRFC.csv
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│ ├── Roches P1 2022 ZSA.csv
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│ ├── Roches P1 2050 ZRFC.csv
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│ └── ...
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└── diagnostics
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├── Roches P1 2022 ZRFC.csv
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├── Roches P1 2022 ZSA.csv
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├── Roches P1 ZRFC scatter.png
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├── Roches P1 ZRFC timeseries.png
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└── ...
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#### 5. Generate hazard line shapefile
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```shell
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> cd ../probabilistic-analysis
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> python shorelines_to_shapefiles.py
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```
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Shapefile is saved here:
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probabilistic-analysis/
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└── output_shp
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├── hazard-lines.cpg
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├── hazard-lines.dbf
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├── hazard-lines.prj
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├── hazard-lines.shp
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└── hazard-lines.shx
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