pydaymet.pet#

Core class for the Daymet functions.

Module Contents#

pydaymet.pet.potential_et(clm, coords=None, crs=4326, method='hargreaves_samani', params=None)#

Compute Potential EvapoTranspiration for both gridded and a single location.

Parameters

  • clm (pandas.DataFrame or xarray.Dataset) – The dataset must include at least the following variables:

    • Minimum temperature in degree celsius

    • Maximum temperature in degree celsius

    • Solar radiation in in W/m2

    • Daylight duration in seconds

    Optionally, relative humidity and wind speed at 2-m level will be used if available.

    Table below shows the variable names that the function looks for in the input data.

    DataFrame

    Dataset

    tmin (degrees C)

    tmin

    tmax (degrees C)

    tmax

    srad (W/m2)

    srad

    dayl (s)

    dayl

    rh (-)

    rh

    u2m (m/s)

    u2

    If relative humidity and wind speed at 2-m level are not available, actual vapour pressure is assumed to be saturation vapour pressure at daily minimum temperature and 2-m wind speed is considered to be 2 m/s.

  • coords (tuple of floats, optional) – Coordinates of the daymet data location as a tuple, (x, y). This is required when clm is a DataFrame.

  • crs (str, int, or pyproj.CRS, optional) – The spatial reference of the input coordinate, defaults to epsg:4326. This is only used when clm is a DataFrame.

  • method (str, optional) – Method for computing PET. Supported methods are penman_monteith, priestley_taylor, hargreaves_samani, and None (don’t compute PET). The penman_monteith method is based on Allen et al.1 assuming that soil heat flux density is zero. The priestley_taylor method is based on Priestley and TAYLOR2 assuming that soil heat flux density is zero. The hargreaves_samani method is based on Hargreaves and Samani3. Defaults to hargreaves_samani.

  • params (dict, optional) – Model-specific parameters as a dictionary, defaults to None.

Returns

pandas.DataFrame or xarray.Dataset – The input DataFrame/Dataset with an additional variable named pet (mm/day) for DataFrame and pet for Dataset.

References

1

Richard G Allen, Luis S Pereira, Dirk Raes, Martin Smith, and others. Crop evapotranspiration-guidelines for computing crop water requirements-fao irrigation and drainage paper 56. Fao, Rome, 300(9):D05109, 1998.

2

Charles Henry Brian Priestley and Robert Joseph TAYLOR. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly weather review, 100(2):81–92, 1972.

3

George H. Hargreaves and Zohrab A. Samani. Estimating potential evapotranspiration. Journal of the Irrigation and Drainage Division, 108(3):225–230, sep 1982. URL: https://doi.org/10.1061%2Fjrcea4.0001390, doi:10.1061/jrcea4.0001390.