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Reading and analyzing hydro(geo)logic time series from the Austrian government's "ehyd.gv.at" platform.

Project description

© Institute of Urban Water Management and Landscape Water Engineering, Graz University of Technology and Markus Pichler

eHYD Tools

license PyPI Buymeacoffee

Reading and analyzing hydro(geo)logic time series from the Austrian government's "ehyd.gv.at" platform.

Various tools for exporting and analyzing >10a rain time-series from the ehyd.gv.at platform of the Austian government.

If you are interested in a statistical heavy rain analysis like on (Ö)Kostra, take a look at my other python package intensity_duration_frequency_analysis which is compatible with this package.

Install

The script is written in Python3. (use a version > 3.5)

Windows

You have to install python (i.e. the original python from the website).

The following commands show the usage for Linux/Unix systems.

To use these features on Windows you have to add python -m before each command and you have to add the path to your python binary to the environment variables ^path1.

There is also an option during the installation to add python to the PATH automatically. ^path2

Linux/Unix

Python is pre-installed on most operating systems (as you probably knew).

Required python packages

Packages required for this program will be installed with pip during the installation process and can be seen in the requirements.txt file.

flowchart TD
    classDef missing stroke-dasharray: 5
    argh["argh<br>0.31.3"]
    certifi["certifi<br>2023.7.22"]
    charset-normalizer["charset-normalizer<br>3.3.0"]
    contourpy["contourpy<br>1.3.0"]
    cycler["cycler<br>0.12.1"]
    fonttools["fonttools<br>4.43.1"]
    idna["idna<br>3.4"]
    kiwisolver["kiwisolver<br>1.4.5"]
    matplotlib["matplotlib<br>3.8.0"]
    numpy["numpy<br>1.26.1"]
    packaging["packaging<br>24.1"]
    pandas["pandas<br>2.2.3"]
    pillow["Pillow<br>10.1.0"]
    pyparsing["pyparsing<br>3.1.1"]
    python-dateutil["python-dateutil<br>2.8.2"]
    pytz["pytz<br>2023.3.post1"]
    requests["requests<br>2.31.0"]
    six["six<br>1.16.0"]
    tzdata["tzdata<br>2023.3"]
    urllib3["urllib3<br>2.0.6"]
    contourpy -- "&ge;1.23" --> numpy
    matplotlib -- "&ge;0.10" --> cycler
    matplotlib -- "&ge;1.0.1" --> contourpy
    matplotlib -- "&ge;1.0.1" --> kiwisolver
    matplotlib -- "&ge;1.21,&lt;2" --> numpy
    matplotlib -- "&ge;2.3.1" --> pyparsing
    matplotlib -- "&ge;2.7" --> python-dateutil
    matplotlib -- "&ge;20.0" --> packaging
    matplotlib -- "&ge;4.22.0" --> fonttools
    matplotlib -- "&ge;6.2.0" --> pillow
    pandas -- "&ge;1.26.0" --> numpy
    pandas -- "&ge;2.8.2" --> python-dateutil
    pandas -- "&ge;2020.1" --> pytz
    pandas -- "&ge;2022.7" --> tzdata
    python-dateutil -- "&ge;1.5" --> six
    requests -- "&ge;1.21.1,&lt;3" --> urllib3
    requests -- "&ge;2,&lt;4" --> charset-normalizer
    requests -- "&ge;2.5,&lt;4" --> idna
    requests -- "&ge;2017.4.17" --> certifi

Fresh install

pip install ehyd-tools

Add the following tags to the command for special options:

  • --user: To install the package only for the local user account (no admin rights needed)
  • --upgrade: To update the package

Alternative Repositories

Usage for general time-series data

Examples Jupyter notebooks for Extended python API

links only work on GitHub!

Usage for high-res precipitation time-series

To start the script use following commands in the terminal/Prompt

ehyd_tools

Commandline tool

With the -h (help) flag you can see the complete functionality of the tool.

ehyd_tools -h
usage: __main__.py [-h] [-id ID] [--input INPUT] [--max10a] [--start START]
                   [--end END] [--add_gaps] [--to_csv] [--to_parquet] [--plot]
                   [--statistics] [--meta] [--unix]

optional arguments:
  -h, --help     show this help message and exit
  -id ID         the id number for the station from the ehyd.gv.at platform
  --input INPUT  path to the rain input file including the filename
  --max10a       consider only 10 years with the most availability (for
                 clipping the data)
  --start START  custom start time (Format="YYYY-MM-DD") for clipping the data
  --end END      custom end time (Format="YYYY-MM-DD") for clipping the data
  --add_gaps     save a gaps-table as a csv-file
  --to_csv       save the time-series as csv-file (to the current directory if
                 the id is used or in the directory of the input-file)
  --to_parquet   save the time-series as parquet-file (to the current
                 directory if the id is used or in the directory of the input-
                 file) - parquet is a much faster as csv to read and write
  --plot         save a bar-plot with monthly sums and availability as a png-
                 file
  --statistics   save the basic statistics (sum, max & min) as a txt-file
  --meta         save the meta-data presented in ehyd as a txt-file
  --unix         export the csv files with a "," as separator and a "." as
                 decimal sign (otherwise ";" as separator and a "," as decimal
                 sign will be used)

The high-res precipitation stations

links only work on GitHub!

List of ehyd-stations with the id-number and the label

Examples

links only work on GitHub!

Example Jupyter notebook for the commandline

Example Jupyter notebook for the python api

Example python skript

Example results files

links only work on GitHub!

Data-gaps in the series

Meta-data of the series

Example Plot

links only work on GitHub!

Regenhöhenlinien

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