Welcome to evapotranspiration!

evapotranspiration calculate reference evapotranspiration.

License: MIT

Documentation

http://warsa.de/evapotranspiration/

Installation

pip install evapotranspiration

Quickstart

For given elevation and latitude, different values of ETo can be calculated individually. One possible set of parameters is day of the year (doy) [-], temperature (t) [°C], relative humidity (rh) [%] and number of cloudless hours (n) [-].

>>> pm = PenmanMonteithDaily(elevation=100, latitude=50.80)
>>> et0_187 = pm.et0(doy=187, u2=2.078, t_min=12.3, t_max=21.5, rh_min=63, rh_max=84, n=9.25)
>>> et0_188 = pm.et0(doy=188, u2=1.553, t_min=14.2, t_max=23.9, rh_min=68, rh_max=78, n=7.3)
>>> print(et0_187)
3.872968723753793
>>> print(et0_188)
3.7135214054227945

The day of the year can be replaced by the date ("YYYY-MM-DD") and the number of cloudless hours can be replaced by the shortwave radiation (rs) [MJ/m²day].

>>> pm = PenmanMonteithDaily(elevation=100, latitude=50.80)
>>> et0_187 = pm.et0(date='2019-07-06', u2=2.078, t_min=12.3, t_max=21.5, rh_min=63, rh_max=84, rs=22)
>>> print(et0_187)
3.8652694092853253

The following parameters are available after each calculation:

>>> print(pm.doy)
187
>>> print(pm.u2)
2.078
>>> print(pm.lamda)
2.4610990999999998
>>> print(pm.delta)
0.12211265844598747
>>> print(pm.psych)
0.06658213300847304
>>> print(pm.daylight_hours)
16.104611680362108
>>> print(pm.es)
1.9974855625338357
>>> print(pm.ea)
1.4086238018595982
>>> print(pm.ra)
41.08837556354228
>>> print(pm.rs)
22.072051614368547
>>> print(pm.rs0)
30.898458423783794
>>> print(pm.rns)
16.995479743063783
>>> print(pm.rnl)
3.7117830478654503
>>> print(pm.rn)
13.283696695198332
>>> print(pm.etr)
2.8051216802858416
>>> print(pm.etw)
1.0678470434679512
>>> print(pm.et)
3.872968723753793

Using pandas DataFrame:

>>> df = pd.DataFrame({'date': ['2001-07-06', '2001-07-06'], 'u2': [2.078, 2.078],
                      't_min': [12.3, 12.3], 't_max': [21.5, 21.5],
                      'rh_min': [63, 63], 'rh_max': [84, 84], 'n': [9.25, 9.25]})
>>> pm = PenmanMonteithDaily(elevation=100, latitude=50.80)
>>> df = pm.et0_frame(df)
>>> print(df)
         date     u2  t_min  t_max  ...       Rnl      ET0r      ET0w       ET0
0  2001-07-06  2.078   12.3   21.5  ...  3.711783  2.805122  1.067847  3.872969
1  2001-07-06  2.078   12.3   21.5  ...  3.711783  2.805122  1.067847  3.872969

[2 rows x 19 columns]

There are also other possible input parameters, like mean temperature and mean relative humidity. Also parameters for other crops than reference grass can be defined. See the documentation for further details: http://warsa.de/evapotranspiration/