hydropandas 0.14.0

Module by Artesia for loading observation data into custom DataFrames.

HydroPandas

Hydropandas is a Python package for reading, analyzing and writing (hydrological) timeseries.

Reading

The HydroPandas package provides convenient read functions from various sources. The table below lists all API-accessible sources. Click a link in the first column for the documentation. The "API available" column indicates current availability (updated weekly).

source	observations	API available	location
BRO	Groundwater		Netherlands
KNMI	Meteorological		Netherlands
Lizard	Groundwater		Netherlands (Vitens)
Waterconnect	Groundwater		South Australia
Waterinfo	Surface water quantity and quality		Netherlands

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Some sources also provide files readable by HydroPandas.

source	observations	file format	location
BRO	Groundwater	xml	Netherlands
DINO	Groundwater / surface water	csv	Netherlands
FEWS	Groundwater / surface water	xml	Netherlands
KNMI	Meteorological	txt	Netherlands
Pastastore	Time series models	NA	NA
Waterinfo	Surface water quantity and quality	csv / zip	Netherlands
Wiski (no docs available)	Groundwater	csv	Netherlands

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Install

Install the module with pip:

pip install hydropandas

For some functionality additional packages are required. Install all optional packages:

pip install hydropandas[full]

For installing in development mode, clone the repository and install by typing pip install -e .[full] from the module root directory.

Documentation

• Documentation is provided on the dedicated website hydropandas.readthedocs.io
• Examples are available in the examples directory on the documentation website
• View and edit the example notebooks of hydropandas in GitHub Codespaces

Get in touch

• Questions on HydroPandas ("How can I?") can be asked and answered on Github Discussions.
• Bugs, feature requests and other improvements can be posted as Github Issues.
• Find out how to contribute to HydroPandas at our Contribution page.

Structure

The HydroPandas package allows users to store a timeseries and metadata in a single object (Obs class). Or store a collection of timeseries with metadata in a single object (ObsCollection class). Both inheret from a pandas DataFrame and are extended with custom methods and attributes related to hydrological timeseries.

The Obs class

The Obs class holds the measurements and metadata for one timeseries. There are currently 7 specific Obs classes for different types of measurements:

• GroundwaterObs: for groundwater measurements
• WaterQualityObs: for groundwater quality measurements
• WaterlvlObs: for surface water level measurements
• ModelObs: for "observations" from a MODFLOW model
• MeteoObs: for meteorological observations
• PrecipitationObs: for precipitation observations, subclass of MeteoObs
• EvaporationObs: for evaporation observations, subclass of MeteoObs

Each of these Obs classes is essentially a pandas DataFrame with additional methods and attributes related to the type of measurement that it holds. Each Obs object also contains specific methods to read data from specific sources.

The ObsCollection class

The ObsCollection class hold the data for a collection of Obs classes, e.g. 10 timeseries of the groundwater level in a certain area. The ObsCollection is essentialy a pandas DataFrame in which each timeseries is stored in a different row. Each row contains metadata (e.g. latitude and longitude of the observation point) and the Obs object that holds the measurements. It's recommended to use one ObsCollection per observation type — for example, group 10 GroundwaterObs in one collection and 5 PrecipitationObs in another.

More information on dealing with Obs and ObsCollection objects in the documentation

Authors

• Onno Ebbens, Artesia
• Ruben Caljé, Artesia
• Davíd Brakenhoff, Artesia
• Martin Vonk, Artesia