pyet is an open source python package for calculating reference and potential Evapotranspiration (PET) for 1D (pandas.Series) and 3D (xarray.DataArrray) data. Currently, eighteen methods for calculating daily PET are implemented:

$^a$ $T_{max}$ and $T_{min}$ can also be provided. $^b$ $RH_{max}$ and $RH_{min}$ can also be provided. $^c$ If actual vapor pressure is provided, RH is not needed. $^d$ Input for radiation can be (1) Net radiation, (2) solar radiation or (3) sunshine hours. If (1), then latitude is not needed. If (1, 3) latitude and elevation is needed. $^e$ One must provide either the atmospheric pressure or elevation. $^f$ The PM method can be used to estimate potential crop evapotranspiration, if leaf area index or crop height data is available. $^g$ The effect of $CO_2$ on stomatal resistance can be included using the formulation of Yang et al. 2019. $^h$ If net radiation is provided, RH and Lat are not needed. $^i$ If method==2, $u_2$, $RH_{min}$ and sunshine hours are required. $^j$ Additional input of $T_{max}$ and $T_{min}$, or $T_{dew}$. $^k$ Input can be $RH$ or actual vapor pressure. $^l$ If method==1, latitude is needed instead of $R_s$. $^m$ $T_{max}$ and $T_{min}$ also needed.

Examples of using pyet can be found in the example folder:

• Example 1: Estimating PET using pandas.Series

• Example 2: Estimating PET using xarray.DataArray

• Example 3: Benchmarking Makkink against KNMI data

• Example 4: Benchmarking FAO56 against CoAgMET data

• Example 5: Calibrating the Romanenko and Abtew method against the PM-FAO56

• Example 6: Worked examples for estimating meteorological variables and potential evapotranspiration after McMahon et al., 2013

• Example 7: Example for estimating potential evapotranspiration under warming and elevated $CO_2$ concentrations following Yang et al., (2019)

• Example 8: Determining the crop coefficient function with Python

• Example 9: Estimating PET using CMIP data

• Example 10: Notebook supporting PyEt manuscript

Documentation is hosted on ReadTheDocs.

After defining the input data, evapotranspiration is estimated using only one line of python code:

>>> pyet.pm_fao56(tmean, wind, rn=rn, tmax=tmax, tmin=tmin, rh=rh, elevation=elevation)

Most of the methods implemented in pyet are benchmarked against literature values from the FAO Irrigation and drainage paper 56, McMahon et al., 2013 (supplementary) and Schrödter, 1985. In addition, two comparative analysis between daily PE estimated with pyet and other organizations is made:

• pyet.pm_fao56 against daily PET estimated with ASCE Penman-Monteith from CoAgMET ( Colorado State University),

• pyet.makkink against daily PET estimated with Makkink from The Royal Netherlands Meteorological Institute (KNMI).

As of version v1.2., pyet is compatible with both Pandas.Series and xarray.DataArray, which means you can now estimate potential evapotranspiration for both point and gridded data.

pyet is in active development, and bug reports are welcome as GitHub Issues. General questions or discussions are possible through GitHub Discussions.

The pyet package is available from the Pypi package index and can be installed as follows::

>>> pip install pyet

To install in developer mode, use the following syntax:

>>> pip install -e .

If you use pyet in one of your studies, please cite the pyet EGU abstract:

• Vremec, M., Collenteur, R. A., and Birk, S.: PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration, Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024, 2024.

@Article{gmd-17-7083-2024,
AUTHOR = {Vremec, M. and Collenteur, R. A. and Birk, S.},
TITLE = {\textit{PyEt} v1.3.1: a Python package for the estimation of potential evapotranspiration},
JOURNAL = {Geoscientific Model Development},
VOLUME = {17},
YEAR = {2024},
NUMBER = {18},
PAGES = {7083--7103},
URL = {https://gmd.copernicus.org/articles/17/7083/2024/},
DOI = {10.5194/gmd-17-7083-2024}
}