pet

neuralhydrology.datautils.pet.get_jensen_haise_pet(t_avg: ndarray, s_rad: ndarray, daily: bool = True) → ndarray

Calculate potential evapotranspiration (PET) using the Jensen-Haise Method from Jensen et al. (2016) [1].

This method estimates PET from shortwave radiation and mean temperature. Modified from jensen_haise method from PyEt python package [2].

Parameters:

• t_avg (np.ndarray) – Average temperature (degree C)

• s_rad (np.ndarray) – Shortwave radiation (W/m²)

• daily (bool, optional) – If True (default), inputs are assumed to be daily values and PET is computed on a daily timescale. If False, inputs are assumed to be sub-daily (e.g., hourly), and PET is computed accordingly.

Returns:

Estimated potential evapotranspiration (PET) in mm per day or hour.

Return type:

np.ndarray

References

[1]

M. E. Jensen and R. G. Allen, Evaporation, evapotranspiration, and irrigation water requirements. American Society of Civil Engineers (ASCE), Jan. 2016, pp. 632–633,isbn: 9780784479209. doi: 10.1061/9780784414057.

[2]

M. Vremec, M. Collenteur, and S. Birk, Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt. (2023). Python. doi: https://doi.org/10.5194/hess-2022-417.

neuralhydrology.datautils.pet.get_priestley_taylor_pet(t_min: ndarray, t_max: ndarray, s_rad: ndarray, lat: float, elev: float, doy: ndarray) → ndarray

Calculate potential evapotranspiration (PET) as an approximation following the Priestley-Taylor equation.

The ground heat flux G is assumed to be 0 at daily time steps (see Newman et al., 2015 [3]). The equations follow FAO-56 (Allen et al., 1998 [4]).

Parameters:

• t_min (np.ndarray) – Daily min temperature (degree C)

• t_max (np.ndarray) – Daily max temperature (degree C)

• s_rad (np.ndarray) – Solar radiation (Wm-2)

• lat (float) – Latitude in degree

• elev (float) – Elevation in m

• doy (np.ndarray) – Day of the year

Returns:

Array containing PET estimates in mm/day

Return type:

np.ndarray

References

[3]

A. J. Newman, M. P. Clark, K. Sampson, A. Wood, L. E. Hay, A. Bock, R. J. Viger, D. Blodgett, L. Brekke, J. R. Arnold, T. Hopson, and Q. Duan: Development of a large-sample watershed-scale hydrometeorological dataset for the contiguous USA: dataset characteristics and assessment of regional variability in hydrologic model performance. Hydrol. Earth Syst. Sci., 19, 209-223, doi:10.5194/hess-19-209-2015, 2015

[4]

Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome, 300(9), D05109.