Run P-model (R wrapper)

Run P-model Fortran model on single site.

run_pmodel_f_bysite(
  sitename,
  params_siml,
  site_info,
  forcing,
  params_modl,
  makecheck = TRUE,
  verbose = TRUE
)

Arguments

sitename

Site name.

params_siml

Simulation parameters.

site_info

Site meta info in a data.frame.

forcing

A data frame of forcing climate data, used as input.

params_modl

A named list of free (calibratable) model parameters. See runread_pmodel_f

makecheck

A logical specifying whether checks are performed to verify forcings and model parameters. TRUE by default.

verbose

A logical specifying whether to print warnings. Defaults to TRUE.

For further specifications of above inputs and examples see p_model_drivers or p_model_drivers_vcmax25

Value

Model output is provided as a tidy dataframe, with columns:

date

Date of the observation in YYYY-MM-DD format.

year_dec

Decimal representation of year and day of the year (for example, 2007.000 corresponds to 2007-01-01 and 2007.003 to 2007-01-02.

fapar

Fraction of photosynthetic active radiation (fAPAR), taking values between 0 and 1.

gpp

Gross Primary Productivity (GPP) for each time stamp (in gC m\(^{-2}\) d\(^{-1}\)).

aet

Actual evapotranspiration (AET), calculated by SPLASH following Priestly-Taylor (in mm d\(^{-1}\)).

le

Latent heat flux (in J m\(^{-2}\) d\(^{-1}\)).

pet

Potential evapotranspiration (PET), calculated by SPLASH following Priestly-Taylor (in mm d\(^{-1}\)).

vcmax

Maximum rate of RuBisCO carboxylation (Vcmax) (in mol C m\(^{-2}\) d\(^{-1}\)).

jmax

Maximum rate of electron transport for RuBP regeneration (in mol CO\(_2\) m\(^{-2}\) s\(^{-1}\)).

vcmax25

Maximum rate of carboxylation (Vcmax), normalised to 25\(^o\)C (in mol C m\(^{-2}\) d\(^{-1}\)).

jmax25

Maximum rate of electron transport, normalised to 25\(^o\)C (in mol C m\(^{-2}\) s\(^{-1}\)).

gs_accl

Acclimated stomatal conductance (in mol C m\(^{-2}\) d\(^{-1}\) Pa\(^{-1}\)).

wscal

Relative soil water content, between 0 (permanent wilting point, PWP) and 1 (field capacity, FC).

chi

Ratio of leaf-internal to ambient CO\(_{2}\), ci:ca (unitless).

iwue

Intrinsic water use efficiency (iWUE) (in Pa).

rd

Dark respiration (Rd) in gC m\(^{-2}\) d\(^{-1}\).

tsoil

Soil temperature, in \(^{o}\)C.

netrad

Net radiation, in W m\(^{-2}\). WARNING: this is currently ignored as a model forcing. Instead, net radiation is internally calculated by SPLASH.

wcont

Soil water content, in mm.

snow

Snow water equivalents, in mm.

cond

Water input by condensation, in mm d\(^{-1}\)

Details

Depending on the input model parameters, it's possible to run the different P-model setups presented in Stocker et al. 2020 GMD. The P-model version implemented in this package allows more flexibility than the one presented in the paper, with the following functions:

The temperature dependence of the quantum yield efficiency is given by:
\(\varphi_0 (T) = c (1 + a (T - b)^2 ) \) if \(0 < c (1 + a (T - b)^2 ) < 1\),
\(\varphi_0 (T) = 0 \) if \( c (1 + a (T - b)^2 ) \leq 0\), and
\(\varphi_0 (T) = 1 \) if \( c (1 + a (T - b)^2 ) \geq 1\).
The ORG setup can be reproduced by setting kphio_par_a = 0 and calibrating the kphio parameter only. The BRC setup (which calibrates \(c_L = \frac{a_L b_L}{4}\) in Eq. 18) is more difficult to reproduce, since the temperature-dependency has been reformulated and a custom cost function would be necessary for calibration. The new parameters are related to \(c_L\) as follows:
\(a = -0.0004919819\)
\(b = 32.35294\)
\(c = 0.6910823 c_L\)

The soil moisture stress is implemented as
\(\beta(\theta) = \frac{\beta_0 - 1}{{\theta^{*}}^2} (\theta - \theta^{*})^2 + 1 \) if \( 0 \leq \theta \leq \theta^{*}\) and
\(\beta(\theta) = 1\) if \( \theta > \theta^{*}\).
In Stocker et al. 2020 GMD, the threshold plant-available soil water is set as \(\theta^{*}\) = 0.6 * whc where whc is the site's water holding capacity. Also, the \(\beta\) reduction at low soil moisture (\(\beta_0 = \beta(0)\)) was parameterized as a linear function of mean aridity (Eq. 20 in Stocker et al. 2020 GMD) but is considered a constant model parameter in this package. Hence, the FULL calibration setup cannot be exactly replicated.

Examples

# Define model parameter values from previous work
params_modl <- list(
  kphio              = 0.04998,    # setup ORG in Stocker et al. 2020 GMD
  kphio_par_a        = 0.0,        # disable temperature-dependence of kphio
  kphio_par_b        = 1.0,
  soilm_thetastar    = 0.6 * 240,  # old setup with soil moisture stress
  soilm_betao        = 0.0,
  beta_unitcostratio = 146.0,
  rd_to_vcmax        = 0.014,      # from Atkin et al. 2015 for C3 herbaceous
  tau_acclim         = 30.0,
  kc_jmax            = 0.41
)

# Run the Fortran P-model 
mod_output <- run_pmodel_f_bysite(
  # unnest drivers example data
  sitename = p_model_drivers$sitename[1],
  params_siml = p_model_drivers$params_siml[[1]],
  site_info = p_model_drivers$site_info[[1]],
  forcing = p_model_drivers$forcing[[1]],
  params_modl = params_modl
 )