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  2. Please report issues with the manual on the GitHub Issues.

  3. Please cite SUEWS with proper information from our Zenodo page. supy.util.calib_g#

supy.util.calib_g(df_fc_suews, ser_ra, g_max, lai_max, wp_smd, method='cobyla', prms_init=None, debug=False)[source]#

Calibrate parameters for modelling surface conductance over vegetated surfaces using LMFIT. Parameters#


DataFrame in SuPy forcing format

ser_ra: pandas.Series

Series with RA, aerodynamic resistance, [s m-1]


Maximum surface conductance [mm s-1]


Maximum LAI [m2 m-2]


Wilting point indicated as soil moisture deficit [mm]

method: str, optional

Method used in minimisation by lmfit.minimize: details refer to its method.

prms_init: lmfit.Parameters, optional

Initial parameters for calibration

debugbool, optional

Option to output final calibrated ModelResult, by default False Returns#

dict, or ModelResult if debug==True
  1. dict: {parameter_name -> best_fit_value}

  2. ModelResult


Parameters for surface conductance: g_lai (LAI related), g2 (solar radiation related), g_dq_base (humidity related), g_dq_shape (humidity related), g_ta (air temperature related), g_smd (soil moisture related) Note#

For calibration validity, turbulent fluxes, QH and QE, in df_fc_suews should ONLY be observations, i.e., interpolated values should be avoided. To do so, please place np.nan as missing values for QH and QE.