Python programming for Hydrology students

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The art of Python programming...

Why use a programming language to process data?

Most students do their calculations in Excel or, if you do not have a license, the alternative open source spreadsheet programme Calc from OpenOffice. However, suppose that you have long time series of meteorological data. In Excel the maximum row lenght would then be reached very quickly so that you would have to divide your data over different sheets. This would be very inefficient. It is also complicated to build a computer model in a spreadsheet program to simulate processes, such as groundwater flow, erosion, or release of greenhouse gases.

In this case, professionals often revert to writing of a dedicated program that can do the processing of data and do model calculations automatically. The most common languages for programming are C programming language and its derivatives and Java and Fortran to name just a few. These languages are very powerful but have the disadvantage that you have to write the program and then compile it to work with it.

Another branch of programming languages are the interpreted languages. Commands can then typed in and are directly evaluated by the interpreter, without compilation. A number of commands can be saved in a text file, which is then called a script. Interpreted languages are Matlab, Python and GNU Octave. As a Matlab license is very costly we prefer to use the open source Python language to work with. Python is a very versatile programming langauge that can be used to process data in a rather easy way and this web page will give you some hints and examples on how to use Python in your scientific carreer.

How to install Python

If you are working with MS Windows (or Ubuntu Linux) go to the Python(xy) download page at and under the Windows XP/Vista installer/administrator account, download the full edition. Once downloaded, double-click on the installer and choose next or I agree a couple of times until Python(xy) is installed.

Please note that if you intend to print equations or special characters in any graphs that you want to plot with Python, you will need to install LaTeX first.

Python(x,y) also makes several useful tools and programs available, including the Scientific PYthon Development EnviRonment (spyder), which is designed for interactive computing and data visualisation and has a simple and intuitive user interface.

An alternative is the Anaconda Python distribution from Continuum Analytics. This is also a free Python distribution (including for commercial use and redistribution) that contains about 300 popular Python packages.

A third alternative distribution for MS Windows, MacOS or RedHat Linux platforms, is the Enthought Python Distribution, which contains all the programs and tools that you will need. However, before you can download this distribution you will have to register and the trial version of this distribution is only of unlimited duration for educational purposes, so you cannot use this commercially.

If you use the Debian or Ubuntu Linux platforms you can just install Python from a shell command line using the command: apt-get install python python-matplotlib.

Learning Python

A short Python tutorial - Python programming for Hydrology students manual - was written by M.J. Waterloo for the Hydrology MSc course "Soil Vegetation Atmosphere Exchange". You can also download the accompanying example script file, which creates an image with Python. For one of the assignments in this manual you can download the water level data text file (wl.txt) with date, time and water level logger data of the Rio Boco River near Aveiro in Portugal.

There are many online tutorials. See, for instance, the Python Tutorials web site at

Python modules and scripts for Hydrologists and Earth Scientists

Several useful scripts are given below. You can in most cases easily adapt these to your needs.


Python scripts and function libraries

GPS and GIS scripts
  • Python GIS: various Python modules for working with GIS - Python GPS, MapView, LatLongUTMconversion.
  • Paul Inkenbrandt from the Utah Geological Survey has made several scripts that work with ArcGIS. The scripts include Stiff diagrams, Box and Whisker and Piper plots. His scripts scan be downloaded from
NetCDF file operations
  • txt2netcdf: various Python functions for importing text into NetCDF data files (creating files, adding variables, listing structure, etc.), developed by Ko van Huissteden.
  • meteolib: Python library containing meteorological functions for calculation of atmospheric vapour pressures, air density, latent heat of vapourisation, heat capacity at constant pressure, psychrometric constant, day length, extraterrestrial radiation input, potential temperature and wind vector. The documentation for this module is presented at here (meteolib module functions web site). Functions to convert event-based data records to equidistant time-spaced records (event2time) and to convert date values to day-of-year values (date2doy) are now in a separate meteo_util module. Documentation is presented here (meteo_util module functions web site). Module documentation is also available as a PDF document. Author: M.J. Waterloo.
  • evaplib: Python library containing functions for calculation of evaporation rates. Functions include Penman open water evaporation, Makkink reference evaporation, Priestley Taylor evaporation Penman Monteith (1965) evaporation and FAO's Penman Monteith ET0 reference evaporation for short, well-watered grass. In addition there is a function to calculate the sensible heat flux from temperature fluctuation measurements. View documentation of evaplib module functions. Module documentation is also available as a PDF document. Author: M.J. Waterloo.
  • Groundwater flow modelling manual for Python written by Vincent post
Workshop meteorological data processing
  • Meteodata processing assignment manual: Meteorological data processing manual for the script and data listed below. It also contains a section on how to report on these data using LaTeX.
  • This script file is used for processing of meteorological data collected during the hydrological field courses in Twente and Portugal. Author: M.J. Waterloo. The script reads the ASCII data, calculates state variables and actual evaporation (temperature variance energy balance method) and potential evaporation. It also plots time series of several weather variables. The script contains questions that should be answered by the student to better understand what the script does. It makes use of the meteolib and evaplib modules presented above. Create an ecohydrology/pyscript directory and download and save the script and modules in this directory.
  • slowtable.dat: File containing meteorological data collected in Portugal during the hydrological field course in Aveiro, 2014. This is the output file of the Campbell Scientific CR1000 data logger. Create an ecohydrology/data directory and download and save the data file in this directory./li>
Statistical Resources for Hydrologists
  • R Resources for Hydrologists: This weblog lists a lot of programs for statistics in hydrology using R, which is a computer language for statistical computing and graphics. Statistical functions of R can be accessed in Python, for instance through Rpy
Hydrological modelling
  • Sat Kumar Tomer from the Department of Civil Engineering - Indian Institute of Science has written an excellent Python in Hydrology handbook and also made several hydrology and earth sciences scripts available from his Ambhas project that can be downloaded from
  • Jaap Schellekens from Deltares in Delft, The Netherlands, has his WFLOW distributed hydrological modelling platform - part of the Openstreams project - available at

Webmaster: M.J. Waterloo

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Last modified: Mon Dec 29 11:27:40 CET 2014