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Main repository for challenge 31/2022: Flood forecasting: the power of citizen science

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CW4Floods

Main repository for challenge 31/2022: Flood forecasting: the power of citizen science

How to contribute

  • Clone the repositories
  • Create the conda environment from the requirements.txt file using conda create --name CW4F --file requirements.txt
  • Activate the conda environment using conda activate CW4F
  • Set the data folder structure
  📦CW4F_data
  ┣ 📂efas
  ┃ ┣ 📜efas_2017_2020.grib
  ┣ 📂image
  ┣ 📂plots
  ┣ 📜image.zip
  ┣ shortlisted_stations_v1.csv
  ┗ station_ind_v1.tsv
   
  • To make changes
    • Added it in the task for github
    • Link it to an issue
    • Create a branch for the same
    • Make changes to your branch
    • Push your code
  • Happy coding!

Cheat sheet

  • To generate the requirements.txt conda env export > environment.yaml

BUGS

If you have issue with cfgrib

This might not be required.

  • pip uninstall cfgrib
  • conda install ecmwflibs
  • conda install eccodes==1.3.1
  • conda install cfgrib
  • conda install -e .

and only this might be required

  • conda install -c conda-forge cfgrib

To-DO

  • Improve the readme file.

Step by step guide

  • Make sure that efas, and the crowd water data is already present in the folder directories mentioned on the top.
  • Running the script 3_s_find_efas_id_cw.py would generate station_ind.tsv. This will in default setting have all the station index inside which we have a crowdwater station.

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Main repository for challenge 31/2022: Flood forecasting: the power of citizen science

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