Package References

Base class

class eto.ETo(df=None, z_msl=500, lat=-43.6, lon=172, TZ_lon=173, z_u=2, time_int='days', K_rs=0.16, a_s=0.25, b_s=0.5, alb=0.23)

Class to handle the parameter estimation of metereological values and the calcuation of reference ET and similar ET methods.

This class can be either initiated with empty parameters or will initialise to the param_est function.

Parameter estimation

ETo.param_est(df, z_msl=500, lat=-43.6, lon=172, TZ_lon=173, z_u=2, time_int='days', K_rs=0.16, a_s=0.25, b_s=0.5, alb=0.23)

Function to estimate the parameters necessary to calculate reference ET (ETo) from the FAO 56 paper [1] using a minimum of T_min and T_max for daily estimates and T_mean and RH_mean for hourly, but optionally utilising the maximum number of available met parameters. The function prioritizes the estimation of specific parameters based on the available input data.

Parameters:
  • df (DataFrame) – Input Metereological data (see Notes section).
  • z_msl (float or int) – Elevation of the met station above mean sea level (m) (only needed if P is not in df).
  • lat (float or int) – The latitude of the met station (dec deg) (only needed if R_s or R_n are not in df).
  • lon (float or int) – The longitude of the met station (dec deg) (only needed if calculating ETo hourly)
  • TZ_lon (float or int) – The longitude of the center of the time zone (dec deg) (only needed if calculating ETo hourly).
  • z_u (float or int) – The height of the wind speed measurement (m).
  • time_int (str) – The time interval of the input and output (either ‘days’ or ‘hours’).
  • K_rs (float) – Rs calc coefficient (0.16 for inland stations, 0.19 for coastal stations)
  • a_s (float) – Rs calc coefficient
  • b_s (float) – Rs calc coefficient
  • alb (float) – Albedo (should be fixed for the reference crop)
Returns:
Return type:

DataFrame

Notes

The input data must be a DataFrame with specific column names according to the met parameter. The column names should be a minimum of T_min and T_max for daily estimates and T_mean and RH_mean for hourly, but can contain any/all of the following:

R_n
Net radiation (MJ/m2)
R_s
Incoming shortwave radiation (MJ/m2)
G
Net soil heat flux (MJ/m2)
T_min
Minimum Temperature (deg C)
T_max
Maximum Temperature (deg C)
T_mean
Mean Temperature (deg C)
T_dew
Dew point temperature (deg C)
RH_min
Minimum relative humidity
RH_max
Maximum relative humidity
RH_mean
Mean relative humidity
n_sun
Number of sunshine hours per day
U_z
Wind speed at height z (m/s)
P
Atmospheric pressure (kPa)
e_a
Actual Vapour pressure derrived from RH

Parameter estimation values refer to the quality level of the input parameters into the ETo equations. Where a 0 (or nothing) refers to no necessary parameter estimation (all measurement data was available), while a 1 refers to parameters that have the best input estimations and up to a value of 3 is the worst. Starting from the right, the first value refers to U_z, the second value refers to G, the third value refers to R_n, the fourth value refers to R_s, the fifth value refers to e_a, the sixth value refers to T_mean, the seventh value refers to P.

References

[1]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.

ETo functions

ETo.eto_fao(max_ETo=15, min_ETo=0, interp=False, maxgap=15, export=None)

Function to estimate reference ET (ETo) from the FAO 56 paper [1] using a minimum of T_min and T_max for daily estimates and T_mean and RH_mean for hourly, but optionally utilising the maximum number of available met parameters. The function prioritizes the estimation of specific parameters based on the available input data.

Parameters:
  • max_ETo (float or int) – The max realistic value of ETo (mm).
  • min_ETo (float or int) – The min realistic value of ETo (mm).
  • interp (False or str) – Should missing values be filled by interpolation? Either False if no interpolation should be performed, or a string of the interpolation method. See Pandas interpolate function for methods. Recommended interpolators are ‘linear’ or ‘pchip’.
  • maxgap (int) – The maximum missing value gap for the interpolation.
  • export (str) – Export path for csv output or None to not export.
Returns:

If fill=False, then the function will return a Series of estimated ETo in mm. If fill is a str, then the function will return a DataFrame with an additional column for the filled ETo value in mm.
Return type:

DataFrame or Series

References

[1]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.
ETo.eto_hargreaves(max_ETo=15, min_ETo=0, interp=False, maxgap=15, export=None)

Function to estimate Hargreaves ETo using a minimum of T_min and T_max, but optionally utilising the maximum number of available met parameters. The function prioritizes the estimation of specific parameters based on the available input data.

Parameters:
  • max_ETo (float or int) – The max realistic value of ETo (mm).
  • min_ETo (float or int) – The min realistic value of ETo (mm).
  • interp (False or str) – Should missing values be filled by interpolation? Either False if no interpolation should be performed, or a string of the interpolation method. See Pandas interpolate function for methods. Recommended interpolators are ‘linear’ or ‘pchip’.
  • maxgap (int) – The maximum missing value gap for the interpolation.
  • export (str) – Export path for csv output or None to not export.
Returns:

If fill=False, then the function will return a Series of estimated ETo in mm. If fill is a str, then the function will return a DataFrame with an additional column for the filled ETo value in mm.
Return type:

DataFrame or Series

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