class ETUtil.ETBase(data: DataFrame, units: dict, constants: dict, transform_etp: bool = True, **kwargs)[source]

Bases: Utils

according to Jensen and Haise method

parameters:

data: pd.DataFrame

input data as pd.DataFrame which can have following columns

  • temp: temperature in degree centigrade

  • rh_min: minimum relative humidity in percentage

  • rh_max: maximum relative humidity in percentage

  • sunshine_hrs: sunshine hours

  • wind_speed: wind speed in m/s

  • wind_dir: wind direction in degrees

  • temp_max: maximum temperature in degree centigrade

  • temp_min: minimum temperature in degree centigrade

  • temp_mean: mean temperature in degree centigrade

  • tdew: dew point temperature in degree centigrade

  • rns: net incoming shortwave radiation in MJ m-2 day-1

  • rnl: net outgoing longwave radiation in MJ m-2 day-1

  • sol_rad: solar radiation in MJ m-2 day-1

__init__(data: DataFrame, units: dict, constants: dict, transform_etp: bool = True, **kwargs)[source]
class ETUtil.PenmanMonteith(data: DataFrame, units: dict, constants: dict, transform_etp: bool = True, **kwargs)[source]

Bases: ETBase

calculates reference evapotrnaspiration according to Penman-Monteith (Allen et al 1998) equation which is also recommended by FAO. The etp is calculated at the time step determined by the step size of input data. For hourly or sub-hourly calculation, equation 53 is used while for daily time step equation 6 is used.

# Requirements Following timeseries data is used

relative humidity temperature

Following constants are used

lm=None, a_s=0.25, b_s=0.5, albedo=0.23

http://www.fao.org/3/X0490E/x0490e08.htm#chapter%204%20%20%20determination%20of%20eto

__init__(data: DataFrame, units: dict, constants: dict, transform_etp: bool = True, **kwargs)