Single-day simulation

Function spwb_day performs water balance for a single day and growth_day performs water and carbon balance for a single day.

Usage

growth_day(
  x,
  date,
  meteovec,
  latitude,
  elevation,
  slope = NA_real_,
  aspect = NA_real_,
  runon = 0,
  lateralFlows = NULL,
  waterTableDepth = NA_real_,
  modifyInput = TRUE
)

spwb_day(
  x,
  date,
  meteovec,
  latitude,
  elevation,
  slope = NA_real_,
  aspect = NA_real_,
  runon = 0,
  lateralFlows = NULL,
  waterTableDepth = NA_real_,
  modifyInput = TRUE
)

Arguments

x: An object of class spwbInput or growthInput.
date: Date as string "yyyy-mm-dd".
meteovec: A named numerical vector with weather data. See variable names in parameter meteo of spwb.
latitude: Latitude (in degrees).
elevation, slope, aspect: Elevation above sea level (in m), slope (in degrees) and aspect (in degrees from North).
runon: Surface water amount running on the target area from upslope (in mm).
lateralFlows: Lateral source/sink terms for each soil layer (interflow/to from adjacent locations) as mm/day.
waterTableDepth: Water table depth (in mm). When not missing, capillarity rise will be allowed if lower than total soil depth.
modifyInput: Boolean flag to indicate that the input x object is allowed to be modified during the simulation.

Value

Function spwb_day() returns a list of class spwb_day with the following elements:

"cohorts": A data frame with cohort information, copied from spwbInput.
"topography": Vector with elevation, slope and aspect given as input.
"weather": A vector with the input weather.
"WaterBalance": A vector of water balance components (rain, snow, net rain, infiltration, ...) for the simulated day, equivalent to one row of 'WaterBalance' object given in spwb.
"Soil": A data frame with results for each soil layer:
- "Psi": Soil water potential (in MPa) at the end of the day.
- "HerbTranspiration": Water extracted by herbaceous plants from each soil layer (in mm).
- "HydraulicInput": Water entering each soil layer from other layers, transported via plant roots (in mm).
- "HydraulicOutput": Water leaving each soil layer (going to other layers or the transpiration stream) (in mm).
- "PlantExtraction": Water extracted by woody plants from each soil layer (in mm).
"Stand": A named vector with with stand values for the simulated day, equivalent to one row of 'Stand' object returned by spwb.
"Plants": A data frame of results for each plant cohort (see transp_transpirationGranier or transp_transpirationSperry).

The following items are only returned when transpirationMode = "Sperry" or transpirationMode = "Sureau":

"EnergyBalance": Energy balance of the stand (see transp_transpirationSperry).
"RhizoPsi": Minimum water potential (in MPa) inside roots, after crossing rhizosphere, per cohort and soil layer.
"SunlitLeaves" and "ShadeLeaves": For each leaf type, a data frame with values of LAI, Vmax298 and Jmax298 for leaves of this type in each plant cohort.
"ExtractionInst": Water extracted by each plant cohort during each time step.
"PlantsInst": A list with instantaneous (per time step) results for each plant cohort (see transp_transpirationSperry).
"LightExtinction": A list of information regarding radiation balance through the canopy, as returned by function light_instantaneousLightExtinctionAbsortion.
"CanopyTurbulence": Canopy turbulence (see wind_canopyTurbulence).

Details

The simulation functions allow using three different sub-models of transpiration and photosynthesis:

The sub-model corresponding to 'Granier' transpiration mode is illustrated by function transp_transpirationGranier and was described in De Caceres et al. (2015), and implements an approach originally described in Granier et al. (1999).
The sub-model corresponding to 'Sperry' transpiration mode is illustrated by function transp_transpirationSperry and was described in De Caceres et al. (2021), and implements a modelling approach originally described in Sperry et al. (2017).
The sub-model corresponding to 'Sureau' transpiration mode is illustrated by function transp_transpirationSureau and was described for model SurEau-Ecos v2.0 in Ruffault et al. (2022).

Simulations using the 'Sperry' or 'Sureau' transpiration mode are computationally much more expensive than 'Granier'.

References

De Cáceres M, Martínez-Vilalta J, Coll L, Llorens P, Casals P, Poyatos R, Pausas JG, Brotons L. (2015) Coupling a water balance model with forest inventory data to predict drought stress: the role of forest structural changes vs. climate changes. Agricultural and Forest Meteorology 213: 77-90 (doi:10.1016/j.agrformet.2015.06.012).

De Cáceres M, Mencuccini M, Martin-StPaul N, Limousin JM, Coll L, Poyatos R, Cabon A, Granda V, Forner A, Valladares F, Martínez-Vilalta J (2021) Unravelling the effect of species mixing on water use and drought stress in holm oak forests: a modelling approach. Agricultural and Forest Meteorology 296 (doi:10.1016/j.agrformet.2020.108233).

Granier A, Bréda N, Biron P, Villette S (1999) A lumped water balance model to evaluate duration and intensity of drought constraints in forest stands. Ecol Modell 116:269–283. https://doi.org/10.1016/S0304-3800(98)00205-1.

Ruffault J, Pimont F, Cochard H, Dupuy JL, Martin-StPaul N (2022) SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level. Geoscientific Model Development 15, 5593-5626 (doi:10.5194/gmd-15-5593-2022).

Sperry, J. S., M. D. Venturas, W. R. L. Anderegg, M. Mencuccini, D. S. Mackay, Y. Wang, and D. M. Love. 2017. Predicting stomatal responses to the environment from the optimization of photosynthetic gain and hydraulic cost. Plant Cell and Environment 40, 816-830 (doi: 10.1111/pce.12852).

Author

Miquel De Cáceres Ainsa, CREAF
Nicolas Martin-StPaul, URFM-INRAE

Examples

#Load example daily meteorological data
data(examplemeteo)

#Load example plot plant data
data(exampleforest)

#Default species parameterization
data(SpParamsMED)

#Define soil parameters
examplesoil <- defaultSoilParams(4)

# Day to be simulated
d <- 100
meteovec <- unlist(examplemeteo[d,-1])
date <- as.character(examplemeteo$dates[d])

#Simulate water balance one day only (Granier mode)
control <- defaultControl("Granier")
x1 <- spwbInput(exampleforest,examplesoil, SpParamsMED, control)
sd1 <- spwb_day(x1, date, meteovec,  
                latitude = 41.82592, elevation = 100, slope=0, aspect=0) 

#Simulate water balance for one day only (Sperry mode)
control <- defaultControl("Sperry")
x2 <- spwbInput(exampleforest, examplesoil, SpParamsMED, control)
sd2 <-spwb_day(x2, date, meteovec,
              latitude = 41.82592, elevation = 100, slope=0, aspect=0)

#Simulate water balance for one day only (Sureau mode)
control <- defaultControl("Sureau")
x3 <- spwbInput(exampleforest, examplesoil, SpParamsMED, control)
sd3 <-spwb_day(x3, date, meteovec,
              latitude = 41.82592, elevation = 100, slope=0, aspect=0)


#Simulate water and carbon balance for one day only (Granier mode)
control <- defaultControl("Granier")
x4  <- growthInput(exampleforest,examplesoil, SpParamsMED, control)
sd4 <- growth_day(x4, date, meteovec,
                latitude = 41.82592, elevation = 100, slope=0, aspect=0)

#Simulate water and carbon balance for one day only (Sperry mode)
control <- defaultControl("Sperry")
x5  <- growthInput(exampleforest,examplesoil, SpParamsMED, control)
sd5 <- growth_day(x5, date, meteovec,
                latitude = 41.82592, elevation = 100, slope=0, aspect=0)

#Simulate water and carbon balance for one day only (Sureau mode)
control <- defaultControl("Sureau")
x6  <- growthInput(exampleforest,examplesoil, SpParamsMED, control)
sd6 <- growth_day(x6, date, meteovec,
                latitude = 41.82592, elevation = 100, slope=0, aspect=0)