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

eHYD Tools

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 intensitydurationfrequency_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.

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

```

Fresh install

bash 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

• https://github.com/hydrogeology-graz/ehyd
• https://github.com/joha1/ehyd_reader

Usage for general time-series data

Examples Jupyter notebooks for Extended python API

links only work on GitHub!

• the design rainfall
• model rain creator
• the general data-reader
• the gis extract

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.

bash 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 --addgaps save a gaps-table as a csv-file --tocsv 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!