potential_ET(::PriestleyTaylor, Tair, pressure, Rn; G=0.0, S=0.0, ...)
potential_ET(::PriestleyTaylor, Tair, pressure, Rn, G, S; ...)

potential_ET(::PenmanMonteith, Tair, pressure, Rn, VPD, Ga_h;
  G=zero(Tair),S=zero(Tair), ...)
fpotential_ET(::PenmanMonteith, Tair, pressure, Rn, VPD, Ga_h, G, S; ...)

potential_ET!(df, approach; ...)

Potential evapotranspiration according to Priestley & Taylor 1972 or the Penman-Monteith equation with a prescribed surface conductance.

Arguments

• Tair: Air temperature (degC)
• pressure: Atmospheric pressure (kPa)
• Rn: Net radiation (W m-2)
• VPD: Vapor pressure deficit (kPa)
• Ga: Aerodynamic conductance to heat/water vapor (m s-1)
• df: DataFrame with the above variables
• approach: Approach used: Either PriestleyTaylor() or PenmanMonteith().

optional:

• G=0.0: Ground heat flux (W m-2). Defaults to zero.
• S=0.0: Sum of all storage fluxes (W m-2) . Defaults to zero.
• constants=BigleafConstants(): physical constants (cp, eps, Rd, Rgas)

for PriestleyTaylor:

• alpha = 1.26: Priestley-Taylor coefficient

for PenmanMonteith:

• Gs_pot = 0.6: Potential/maximum surface conductance (mol m-2 s-1);
• Esat_formula: formula used in Esat_from_Tair

Details

Potential evapotranspiration is calculated according to Priestley & Taylor, 1972 (approach = PriestleyTaylor():

$\mathit{LE}_{pot} = (\alpha \, \Delta \, (Rn - G - S)) / (\Delta + \gamma)$

$\alpha$ is the Priestley-Taylor coefficient, $\Delta$ is the slope of the saturation vapor pressure curve (kPa K-1), and $\gamma$ is the psychrometric constant (kPa K-1).

If approach = PenmanMonteith(), potential evapotranspiration is calculated according to the Penman-Monteith equation:

$\mathit{LE}_{pot} = (\Delta \, (R_n - G - S) + \rho \, c_p \, \mathit{VPD} \; G_a) / (\Delta + \gamma \, (1 + G_a/G_{s pot})$

where $\Delta$ is the slope of the saturation vapor pressure curve (kPa K-1), $\rho$ is the air density (kg m-3), and $\gamma$ is the psychrometric constant (kPa K-1). The value of $G_{s pot}$ is typically a maximum value of $G_s$ observed at the site, e.g. the $90^{th}$ percentile of $G_s$ within the growing season.

Ground heat flux and storage heat flux G or S are provided as optional arguments. In the input-explicit variants, they default to zero. In the data-frame arguments, they default to missing, which results in assuming them to be zero which is displayed in a log-message. Note that in difference to the bigleaf R package, you explicitly need to care for missing values (see examples).

Value

NamedTuple with the following entries:

• ET_pot: Potential evapotranspiration (kg m-2 s-1)
• LE_pot: Potential latent heat flux (W m-2)

References

• Priestley, CHB., Taylor, R_J., 1972: On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Review 100, 81-92.
• Allen, RG., Pereira LS., Raes D., Smith M., 1998: Crop evapotranspiration - Guidelines for computing crop water requirements - FAO Irrigation and drainage paper 56.
• Novick, K_A., et al. 2016: The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nature Climate Change 6, 1023 - 1027.

See also

surface_conductance

Examples

Calculate potential ET of a surface that receives a net radiation of 500 Wm-2 using Priestley-Taylor:

Tair, pressure, Rn = 30.0,100.0,500.0
ET_pot, LE_pot = potential_ET(PriestleyTaylor(), Tair, pressure, Rn)    
≈(ET_pot, 0.000204; rtol = 1e-2)

Calculate potential ET for a surface with known Gs (0.5 mol m-2 s-1) and Ga (0.1 m s-1) using Penman-Monteith:

Tair, pressure, Rn = 30.0,100.0,500.0
VPD, Ga_h, Gs_pot = 2.0, 0.1, 0.5
ET_pot, LE_pot = potential_ET(
  PenmanMonteith(), Tair,pressure,Rn,VPD, Ga_h; Gs_pot)    
# now cross-check with the inverted equation
Gs_ms, Gs_mol = surface_conductance(
  InversePenmanMonteith(), Tair,pressure,VPD,LE_pot,Rn,Ga_h)
Gs_mol ≈ Gs_pot

DataFrame variant with explicitly replacing missings using coalesce.:

using DataFrames
df = DataFrame(
  Tair = 20.0:1.0:30.0,pressure = 100.0, Rn = 500.0, G = 105.0, VPD = 2.0, 
  Ga_h = 0.1) 
allowmissing!(df, Cols(:G)); df.G[1] = missing
#
# need to provide G explicitly
df_ET = potential_ET!(copy(df), PriestleyTaylor(); G = df.G)    
ismissing(df_ET.ET_pot[1])
#
# use coalesce to replace missing values by zero
df_ET = potential_ET!(
  copy(df), PriestleyTaylor(); G = coalesce.(df.G, zero(df.G)))    
!ismissing(df_ET.ET_pot[1])

equilibrium_imposed_ET(Tair,pressure,VPD,Gs, Rn; ...)
equilibrium_imposed_ET!(df; ...)

Evapotranspiration (ET) split up into imposed ET and equilibrium ET.

Arguments

• Tair : Air temperature (deg C)
• pressure : Atmospheric pressure (kPa)
• VPD : Air vapor pressure deficit (kPa)
• Gs : surface conductance to water vapor (m s-1)
• Rn : Net radiation (W m-2)

optional :

• G=0 : Ground heat flux (W m-2)
• S=0 : Sum of all storage fluxes (W m-2)
• Esat_formula=Sonntag1990(): formula used in Esat_from_Tair
• constants=BigleafConstants(): physical constants (cp, eps)

Details

Total evapotranspiration can be written in the form (Jarvis & McNaughton 6):

$ET = \Omega \mathit{ET}_{eq} + (1 - \Omega) \mathit{ET}_{imp}$

where $\Omega$ is the decoupling coefficient as calculated from decoupling. ET_eq is the equilibrium evapotranspiration i.e., the ET rate that would occur under uncoupled conditions, where the budget is dominated by radiation (when Ga -> 0):

$ET_{eq} = (\Delta \, (R_n - G - S) \, \lambda) / ( \Delta \gamma)$

where $\Delta$ is the slope of the saturation vapor pressur(kPa K-1), $\lambda$ is the latent heat of vaporization (J kg-1), and $\gamma$ is the psychrometric constant (kPa K-1). ET_imp is the imposed evapotranspiration rate, the ET rate that would occur under fully coupled conditions (when Ga -> inf):

$ET_{imp} = (\rho \, c_p \, \mathit{VPD} ~ G_s \, \lambda) / \gamma$

where $\rho$ is the air density (kg m-3).

Value

A NamedTuple or DataFrame with the following columns:

• ET_eq: Equilibrium ET (kg m-2 s-1)
• ET_imp: Imposed ET (kg m-2 s-1)
• LE_eq: Equilibrium LE (W m-2)
• LE_imp: Imposed LE (W m-2)

References

• Jarvis, PG., McNaughton, KG., 1986: Stomatal control of transpiration: scaling up from leaf to region. Advances in Ecological Rese1-49.
• Monteith, JL., Unsworth, MH., 2008: Principles of ironmPhysics. 3rd edition. Academic Press, London.

Examples

Tair,pressure,Rn, VPD, Gs = 20.0,100.0,50.0, 0.5, 0.01
ET_eq, ET_imp, LE_eq, LE_imp = equilibrium_imposed_ET(Tair,pressure,VPD,Gs, Rn)    
≈(ET_eq, 1.399424e-05; rtol = 1e-5)