R/SWIFT.R
In HannesDeDeurwaerder/SWIFT: SWIFT: Tracking stable water isotopic fluctuation along the length of a plant
Defines functions
Bprep
PSI0calc
SoilRootCond
SWIFT_H
SWIFT_SB
Documented in
Bprep
PSI0calc
SoilRootCond
SWIFT_H
SWIFT_SB
#'##############################################################################
#'##############################################################################
#'
#' @title SWIFT model (Stable Water Isotope Fluctuation within Trees)
#'
#'
#' @param ARtot Description: The total fine root area area of the focal plant
#' [in m2];
#' Structure: One value, representative of the studied plant.
#' @param Ax Description: The total lumen area [in m2];
#' Structure: One value, representative of the studied plant.
#' @param B Description: The comunity plant Root length density at every
#' discrete soil layer
#' - Results from the function Bprep - [in m m-3];
#' Structure: A discrete vector of n elements, with n the number
#' of soil layers.
#' @param beta Description: Factor in the root length density distribution
#' function for the focal plant;
#' Structure: One value, derived from Jackson et al. (1996),
#' table 1.
#' @param betaCom Description: Factor in the root length density distribution
#' function of the plant community
#' (required to distribute the root length over all
#' soil layers)
#' Structure: One value, derived from Jackson et al. (1996),
#' table 1.
#' @param D2Hxylem Description: The deuterium signature at stem base - derived
#' from the function SWIFT_SB [in permil, VSMOW];
#' Structure: A discrete vector of n elements, with n the
#' number of timesteps sampled.
#' @param D2Hsoil Description: Vector representing the stable water isotopic
#' siganture profile with depth
#' [in permil, VSMOW];
#' Structure: A discrete vector of n elements, with n the
#' number of soil layers.
#' @param dZ Description: Thickness of the soil layer [in m];
#' Structure: One value, Samples should be taken at discrete
#' depths which have the same thickness.
#' @param hom Description: A vector of studied measurement heights [in m];
#' Structure: The size of the vector is defined by the interest
#' of the user.
#' @param k Description: Plant specific total soil-to-root conductance at
#' each specific specific soil layer [in s-1];
#' Structure: A vector - results from the function SoilRootCond
#' - and has n elements corresponding to the number of
#' soil layers.
#' @param kr Description: The root membrane permeability [s-1];
#' Structure: One value, representative of the studied plant.
#' @param PSIs Description: Soil water potential at the each specific soil
#' layer [in m];
#' Structure: A vector of n element, where n corresponds to the
#' number of soil layers;
#' Note: The water potentials per soil layer is currently
#' considered static in time.
#' @param R0 Description: Factor in the root lenght density distribution per
#' unit of soil, for entire plant community;
#' NOTE: Provide a Positive value!!
#' Structure: One value,representative of the studied plant, here
#' derived from Huang et al, 2017.
#' @param SF Description: Instantaneous sap flow over time [in m^3 s-1];
#' Structure: A vector of n elements, where n corresponds to the
#' number of timesteps.
#' @param Soiltype Description: Type of soil layer (Sand; Loamy Sand;
#' Sandy Loam; Silt Loam; Loam; Sandy Clay Loam;
#' Silty Clay Loam; Clay Loam;Sandy Clay;
#' Silty Clay; Clay);
#' Structure: A Character string.
#' @param t Description: Cumulative time steps [in s];
#' Structure: A vector.
#' @param tstud Description: By the user defined timesteps to which an output
#' is required [in second after initialisation];
#' Structure: A vector with n elements defined by the user;
#' Note: When an output is needed for all values, then
#' tstud = t.
#' @param tF Description: Measurement frequence per hour [in measurement
#' points per hour];
#' Structure: One value, defined by the user;
#' Note: Lower numbers will increase the speed of the
#' model, but for graphical display, higher values
#' are prefered.
#' @param Z Description: A vector of Soil depth [in m];
#' Structure: A discrete vector of n elements, where n
#' corresponds to the number of soil layers.
#'
#'
#'
#' @author Hannes De Deurwaerder, Marco D. Visser, Matteo Detto, Pascal Boeckx,
#' Felicien Meunier and Hans Verbeeck.
#'
#' @examples
#' \dontrun{
#'
#' # Initialisation of parameters
#' n <- 20 # Multiple number of days studied, needed for spin up
#' # of the model.
#' tF <- 60 # Time frequence of measurements per hour
#' # [in measurments per h].
#' t <- seq(0,24*n,length.out = 24*tF*n) # Discrete time vector [in h].
#' dZ <- 0.001 # Thickness of sampled layer [in m].
#' L <- 1 # maximum soil depth [in m].
#' Z <- seq(dZ,L,dZ) # Discrete depth vector centered [in m].
#' kr <- 10*10^(-10) # root membrane permeability [in s^(-1)]
#' # (source: Leuschner et al, 2004).
#' DBH <- 0.213 # Diameter at breast height [in m].
#' LA <- 0.136 # Lumen Fraction, i.e. lumen area/sapwood area [%]
#' # (derived from Zanne et al, 2010) [table 2, F-value].
#' Ax <- LA * ((1.582*((DBH*100)^1.764)) /10^4)
#' # Total lumen area of the studied tree [m^2],i.e. the
#' # lumena area fraction multiplied by sapwood area
#' # estimated from the DBH (Meinzer et al, 2001) .
#' ARtot <- exp(0.88*log(pi*2*(100*DBH/2)^2)-2)
#' # ARtot in [m^2] via DBH[in cm] (Cermak et al, 2006)
#' R0 <- 438688 # Derived from Huang et al, 2017.
#' betaCom <- 0.976 # Derived from Jackson et al., 1996 [table 1,
#' # beta-term].
#' beta <- 0.976 # Derived from Jackson et al., 1996 [table 1,
#' # beta-term].
#' # Source the SWIFT model
#' require("SWIFT")
#'
#'
#' # Prepare additional input data of the model
#' data(SFday)
#' # SF for one day, time frequency: every min, expressed in [kg h-1].
#' # This data is derived from Huang et al, 2017.
#' uch <- (60/tF)*60*1000 # unit conversion: h to sec. and kg to m3
#' SF <- c(rep(SFday,n))/(uch) # repetition of SF day over n prefered days.
#'
#' # Soil water potential curve with depth, from Meissner et al, 2012
#' CTpsi <- 101.97 # Conversion factor between MPa and m H2O.
#' Apsi <- 198.4455; Bpsi <- 448.9092; Cpsi <- 255.5937;
#' # Apsi, Bpsi and Cpsi are values derived from Meissner et al 2012 data
#' # from optimizing the function defined in the paper of De Deurwaerder
#' # et al. (In Review).
#' PSIs <- ((Apsi + Bpsi *log(Z) - Cpsi*Z^2) /10000) * CTpsi
#'
#' # isotopic water isotopic signature with depth from Meissner et al, 2012
#' lsoil <- -73.98008; msoil <- 0.148735; soildev <- 0.001
#' # lsoil and msoil are values derived from the Meissner et al 2012 data
#' # from optimizing the function defined in the paper of De Deurwaerder
#' # et al. (In Review).
#' D2Hsoil <- lsoil * (Z+soildev)^msoil
#'
#' # NOTE that the data of Meissner et al 2012 is accessible and can be sourced
#' # as provided below:
#' data(MeissnerData)
#'
#'
#' # Using the SWIFT model functions
#'
#' # A. Root density distribution
#' B <- Bprep(betaCom, R0, Z) # output is in [m m^(-3)].
#'
#' # B. the soil-root conductance
#' k <- SoilRootCond(B, kr, PSIs, Z, 'Silt Loam')
#'
#' # C. the ARi
#' devio=beta^(100*Z)*(1-beta^(100*dZ))
#' ARi=ARtot*devio/sum(devio)
#'
#' # D. Isotopic signature fluctuation at stem base
#' StemBase <- SWIFT_SB(ARi, D2Hsoil, k, PSIs, SF, t, Z)
#'
#' # E. Isotopic signature at specific height and time
#' tstud <- seq(2*(24*tF), 3*(24*tF),1)
#' # Provides the data of day 3 of the modeled tree.
#' # (We selected day 3 to assure proper spin up of the model).
#' hom <- 1.3 # measured at standard coring height, 1.3 m.
#' D2Htree <- SWIFT_H( Ax, StemBase, hom, SF, tstud, tF)
#'
#' # E. The Water potential at stem base
#' PSI0vec <- PSI0calc(ARi, k, PSIs, Sf, t, Z)/CTpsi
#' # CTpsi to convert from m to MPa.
#'
#'
#' # Field data corroborating the hypothesis of strong isotopic fluctuations
#' # along the length of a stem:
#' data(Fielddata)
#'
#'
#' # Making a simple plot of the SWIFT output
#'
#' # MAKING A SIMPLE PLOT OF THE SWIFT OUTPUT
#' ylabel=expression(paste(delta,""^"2","H"," [","\211",", vsmow]"))
#' plot(t,StemBase, xlim= c( min(tstud)/tF, max(tstud)/tF), type='l',
#' lty=2, col='grey', ylab=ylabel, xlab='timesteps', mgp = c(2, 0.8, 0))
#' # Plot the signature fluctuations at the stem base
#' lines( tstud/tF, D2Htree, col='blue')
#' # Plot the signature fluctuations at the height defined by the user
#' legend( 'bottomleft', c('at stembase',paste0('at ',hom,' m')),
#' lty=c(2,1), col=c('grey', 'blue'), bty='n', cex=0.7)
#'
#' load()
#' }
#'
#' @return Provided by function
#' - SWIFT_SB: Vector of isotopic signatures at the stem base for
#' every timestep [in permil, VSMOW].
#' - SWIFT_H: Vector of isotopic signatures at by the user defined
#' height and time [in permil, VSMOW].
#' - SoilRootCond: Vector of soil to root conductivity for every
#' defined soil layer [in s-1].
#' - PSI0calc: Vector of water potential at stem base for every
#' timestep [in m H2O].
#' - Bprep: Vector of root length distribution for every defined
#' soil layer [in m m-3].
#'
#' @export
#'
#'##############################################################################
#'##############################################################################
SWIFT_SB<-function(ARi=NULL, D2Hsoil=NULL, k=NULL, PSIs=NULL, SF=NULL, t=NULL, Z=NULL){
#===============================================================================
# SWIFT MODEL PART A
#===============================================================================
# STABLE WATER ISOTOPES CALUCLATED AT STEM BASE
#-------------------------------------------------------
# Function description: This function calculates the isotopic signature at the
# stem base at every timestep.
# Declare empty vectors
D2Hxylem=rep(NaN,length(t))
D2Hvec <- fi <- RWU <- rep(NaN,length(Z))
for (a in 2:length(t)){
# first value is NaN due to model spin-up.
if((SF[a]==0 & a!=1) | (is.nan(SF[a]))){
D2Hxylem[a]<-ifelse(is.nan(D2Hxylem[a-1]),NaN,D2Hxylem[a-1])
# When SF=0, water is stagnant --> signature at t=0 equals signature
# at t=-1.
}else{
# Water potential at stem base
PSI0 <- (sum(k*ARi*(PSIs-Z)) - SF[a])/ sum(k*ARi)
RWU0 <- k*ARi*(PSIs-Z - PSI0)
# make sure no negative RWU flows occurs
not.use <- which(RWU0<0)
RWU <- RWU0
while (sum(not.use)>0){
not.use <- which(RWU<0)
RWU[not.use] <- 0
use <- which(RWU>0)
ARiuse = ARi[use]
kuse = k[use]
Zuse = Z[use]
PSIsuse = PSIs[use]
PSI0 <- (sum(kuse*ARiuse*(PSIsuse-Zuse)) - SF[a]) / sum(kuse*ARiuse)
RWU[use] <- kuse*ARiuse*(PSIsuse-Zuse - PSI0)
}
fi <- RWU/sum(RWU, na.rm=TRUE)
D2Hxylem[a] <- sum(fi*D2Hsoil, na.rm=TRUE)
}
}
return(D2Hxylem)
}
################################################################################
################################################################################
SWIFT_H<-function(Ax=NULL, D2Hxylem=NULL, hom=NULL, SF=NULL, tstud=NULL,
tF=NULL){
#===============================================================================
# SWIFT MODEL PART B
#===============================================================================
# STABLE WATER ISOTOPES CALUCLATED AT BY THE USER DEFINED HEIGHT AND TIME
#-------------------------------------------------------------------------
# Function description: This function calculates the isotopic signature at
# by the user defined height of measurement and timing of sampling.
hts <- length( as.vector(hom) ) # vector of user defined heights.
tms <- length( as.vector(tstud)) # vector of user defined sample times.
D2Hxylem_hom <- matrix(NA,hts,tms)
uc <-((60/tF)*60) # unit conversion.
# Cumulative SF vector
cumSF=cumsum(SF) # Cumulative sapflow
cumH=uc*cumSF/Ax # Cumulative Height reached by the sapflow
cumH[which(cumSF==0)]<-NaN
# No sapflow yet, this is the spinup, should be set at NA
for (ab in 1:tms){
a=tstud[ab] # By user defined timesteps.
for (w in 1:hts){
# First value will be NA, for spin
if (a==1){
D2Hxylem_hom[w,ab] <- NaN
next
}
# for signatures at stem base, i.e. h=0
if (hom[w]==0 && a!=1){D2Hxylem_hom[w,ab] <- D2Hxylem[a]
next
}
# for all other cases
# for the spinup values
if(is.nan(cumH[a])){D2Hxylem_hom[w,ab] <- D2Hxylem[a-1]
next
}else{
# not spinup values
CumHt <- cumH -(cumH[a])+ hom[w]
Minind <- which(abs(CumHt)==min(abs(CumHt), na.rm=TRUE))
# Total delay for the sapflow to reach hom (time)
# Delay extends the datarange?
if (length(Minind)==0){
D2Hxylem_hom[w,ab] <- NaN # only a problem during model spin up
}else{
delay=a-Minind[1]
D2Hxylem_hom[w,ab] <- D2Hxylem[a-delay]
}
rm(delay); rm(Minind)
}
}
}
return(D2Hxylem_hom)
}
################################################################################
################################################################################
SoilRootCond <- function(B=NULL, kr=NULL, PSIs=NULL, Z=NULL, Soiltype=NULL ){
#===============================================================================
# PLANT SPECIFIC TOTAL SOIL TO ROOT CONDUCTANCE
#===============================================================================
# Function description: This function calculates the soil to root conductance
# while considering the soiltype.
# Soiltype conform the soil texture triangle, with corresponding
# values from clapp and hornberger (1978).
if(Soiltype == 'Sand'){
ksmax=1.056/(100*60); PSIsat=-0.121; b=4.05; sigmasat=0.395}
if(Soiltype == 'Loamy Sand'){
ksmax=0.938/(100*60); PSIsat=-0.090; b=4.38; sigmasat=0.410}
if(Soiltype == 'Sandy Loam'){
ksmax=0.208/(100*60); PSIsat=-0.218; b=4.90; sigmasat=0.435}
if(Soiltype == 'Silt Loam'){
ksmax=0.0432/(100*60); PSIsat=-0.786; b=5.30; sigmasat=0.485}
if(Soiltype == 'Loam'){
ksmax=0.0417/(100*60); PSIsat=-0.478; b=5.39; sigmasat=0.451}
if(Soiltype == 'Sandy Clay Loam'){
ksmax=0.0378/(100*60); PSIsat=-0.299; b=7.12; sigmasat=0.420}
if(Soiltype == 'Silty Clay Loam'){
ksmax=0.0102/(100*60); PSIsat=-0.356; b=7.75; sigmasat=0.477}
if(Soiltype == 'Clay Loam'){
ksmax=0.0147/(100*60); PSIsat=-0.630; b=8.52; sigmasat=0.476}
if(Soiltype == 'Sandy Clay'){
ksmax=0.0130/(100*60); PSIsat=-0.153; b=10.40; sigmasat=0.426}
if(Soiltype == 'Silty Clay'){
ksmax=0.0062/(100*60); PSIsat=-0.490; b=10.40; sigmasat=0.492}
if(Soiltype == 'Clay'){
ksmax=0.0077/(100*60); PSIsat=-0.405; b=11.40; sigmasat=0.482}
# calculate k using the Clapp and Hornberger (1978) equation.
k=ks<-rep(NA,length(Z))
for (h in 1:length(Z)){
ks[h] <- ksmax * (PSIsat/PSIs[h])^(2+3/b)
k[h]<- kr * ks[h]*sqrt(pi*B[h]) / (0.53*kr + ks[h]*sqrt(pi*B[h]) )
}
return(k)
}
################################################################################
################################################################################
PSI0calc <- function(ARi=NULL, k=NULL, PSIs=NULL, SF=NULL, t=NULL, Z=NULL){
#===============================================================================
# WATER POTENTIAL AT STEM BASE
#===============================================================================
# Function description: This function calculates the water potential at stem
# base at every timestep, indirectly derived from the sap flow.
PSI0vec=rep(NA,length(t))
for (a in 1:length(t)){
# Water potential at stem base
PSI0 <- (sum(k*ARi*(PSIs-Z)) - SF[a])/ sum(k*ARi)
RWU0 <- k*ARi*(PSIs-Z - PSI0)
# make sure no negative RWU flows occurs
not.use <- which(RWU0<0)
RWU <- RWU0
while (sum(not.use)>0){
not.use <- which(RWU<0)
RWU[not.use] <- 0
use <- which(RWU>0)
ARiuse = ARi[use]
kuse = k[use]
Zuse = Z[use]
PSIsuse = PSIs[use]
PSI0 <- (sum(kuse*ARiuse*(PSIsuse-Zuse)) - SF[a]) / sum(kuse*ARiuse)
RWU[use] <- kuse*ARiuse*(PSIsuse-Zuse - PSI0)
}
# assign PSI0 of one time point to the vector of PSI at stem base
PSI0vec[a] <- PSI0
}
return(PSI0vec)
}
################################################################################
################################################################################
Bprep<-function( beta=NULL, R0=NULL, Z=NULL){
#===============================================================================
# ROOT LENGTH DISTRIBUTION FUNCTION
#===============================================================================
# Function description: This function calculates root length distribution
# cf. Huang et al, 2016.
B <- rep(NA,length(Z))
UnCo <- 100 # unit conversion from m to cm.
for (h in 1:length(Z)){
B[h]= -R0* beta^(UnCo*Z[h])*log(beta, base=exp(1))
}
return(B)
}
################################################################################
################################################################################
#' The Laussat Trees and Liana isotopic signature along the lenght of
#' the plant dataset.
#'
#'
#' General Description:
#' This dataset contains both sample extraction information, i.e.
#' timing and height of sampling, the diameter, growth form type and species
#' name, as well as the isotopic deuterium and oxygen 18 signature of the
#' sampled plant
#'
#'
#' This dataset may not be
#' used without previous written permission from the
#' owner.
#'
#'
#' Ownership: Hannes De Deurwaerder <Hannes_de_deurwaerder@hotmail.com>
#'
#' Research Location:
#' Within the research forest of LAUSSAT, French Guyana.
#' Sampled species all are located on a white sandy subsoil.
#'
#' Dataset abstract:
#' These data are being used to evaluate hypothesized mechanisms of
#' xylem water isotopic variation along the length of a plant
#'
#'
#' Methods:
#' The methods of sampling are in much detail described in
#' De Deurwaerder et al. (2018) Tree Physiology. 38(7). p.1071-1083
#'
#'
#' The dataset contains the following labels (columns):
#' \itemize{
#' \item Number (Integer) Unique identifier per growth form.
#' \item Type (Character) Indication of the growth form, i.e. liana or tree.
#' \item Family (Character) Identification of the scientific plant family.
#' \item Family (Character) Species (Character) identification of the scientific
#' species name.
#' \item Date (Character) Date of sampling in the year 2017.
#' \item Time (Character) Time of sampling.
#' \item Hour (Integer) Hour of measurement.
#' \item Minute (Integer) Minute of measurement.
#' \item Height (Numeric) Height of measurement [in m].
#' \item H2 (Numeric) Xylem deuterium isotopic signature [in permil, VSMOW].
#' \item stdev_H2 (Numeric) Standard deviation on the xylem deuterium isotopic
#' signature [in permil, VSMOW], resulting from the Picarro measurement.
#' \item O18 (Numeric) Xylem O18 isotopic signature [in permil, VSMOW].
#' \item stdev_O18 (Numeric)Standard deviation on the xylem O18 isotopic
#' signature [in permil, VSMOW], resulting from the Picarro measurement.
#' \item Diam (Numeric) Diameter of the growth form [in cm].
#' \D1O
#' }
#'
#'
#' @docType data
#' @keywords datasets
#' @name Fielddata
#' @usage data(Fielddata)
#' @format
#'
NULL
################################################################################
################################################################################
#' The Meissner et al 2012 of water isotopic signatures
#' and the water potential in the soil.
#'
#' General Description:
#' This data, providing an overview of both deuterium and oxygen 18
#' signatures as well as the water potential gradient discussed in the paper
#' of meissner et al, 2012 papers entitled: (i)Partitioning of soil water among
#' canopy trees during a soil desiccation period in a temperate mixed forest'
#' and (ii) Soil water uptake by trees using water stable isotopes
#' (d2H and d18O)- a method testregarding soil moisture, texture and carbonate
#'
#'
#' This dataset is freely accessible from the papers of Meissner et al 2012.
#' However, users should feel enclined to cite Meissner et al 2012 when using
#' the data
#'
#'
#' Ownership: M. Meissner <mmeissn3@gwdg.de>
#'
#'
#' Research Location:
#' Soil samples were collected at the Hainich National Park close to the vilage
#' of Weberstedt in Central Germany. Height of sampling was approx. 350 m a.s.l.
#' and the region experiences a subatlatic climate with a mean anual
#' precipitation around 600 mm and st.dev. around 50mm.
#' More details are provided in both articles of Meissner et al, 2012.
#'
#'
#' Dataset abstract:
#' These data is being used to test the hypothesized mechanisms of xylem water
#' isotopic variation along the length of a plant.
#'
#' Methods:
#' The methods of sampling are in much detail described in both papers of
#' Meissner et al, 2012. More specifically, this data forms the driver data of
#' the SWIFT model (1) "Soil water uptake by trees using water stable isotopes
#' (d2H and d18O) - a method testregarding soil moisture, texture and carbonate
#' (2) Partitioning of soil water among canopy trees during a soil
#' desiccation period in a temperate mixed forest"
#'
#'
#' The dataset contains the following labels (columns):
#' \itemize{
#' \item Meissner_depth (Numeric) The average depth of the samples soil layer
#' [in m].
#' \item Meissner_d2h (Numeric) The deuterium isotopic siganture of the bulk
#' soil water at the sampled depths [in permil, VMSOW].
#' \item Meissner_sdd2h (Numeric) The standard deviations on the deuterium
#' isotopic siganture of the bulk soil
#' water at the sampled depths [in permil, VMSOW].
#' \item Meissner_d18o(Numeric) The oxygen 18 isotopic siganture of the bulk
#' soil water at the sampled depths [in permil, VMSOW].
#' \item Meissner_sdd18o (Numeric) The standard deviations on the oxygen 18
#' isotopic siganture of the bulk soil
#' water at the sampled depths [in permil, VMSOW].
#' \item Meissner_psi (Numeric) The water potential at the sampled soil depths
#' [in hPa].
#' \item Meissner_sdpsi (Numeric) The standard deviations on the water potential
#' at the sampled soil depths [in hPa].
#' \D1O
#' }
#'
#'
#' @docType data
#' @keywords datasets
#' @name MeissnerData
#' @usage data(MeissnerData)
#' @format
#'
NULL
################################################################################
################################################################################
#' The daily sap flow derived from Huang et al 2017.
#'
#'
#' General Description:
#' The daily sap flow flux [in kg h-1] derived from the Huang et al 2017 paper,
#' day 11 of scenario 6. Data is interpollated to derive a timefrequency per
#' minute.
#'
#'
#' This dataset is freely accessible from the paper of Huang et al. 2017
#' However, Users should feel enclined to cite Huang et al. 2017 when using the
#' data. paper title: The effect of plant water storage on water fluxes within
#' the coupled soil-plant system.
#'
#'
#' Ownership: Cheng-Wei Huang <chengweihuang1206@gmail.com>
#'
#'
#' Research Location:
#' Details on the research location and scenario description
#' is in detail described in Huang et al, 2017, New Phytologist paper
#' entitled: The effect of plant water storage on water fluxes within
#' the coupled soil-plant system
#'
#'
#' Dataset abstract:
#' These data are being used to evaluate hypothesized mechanisms of
#' xylem water isotopic variation along the length of a plant.
#' This data is used to drive the SWIFT model, as presented by De Deurwaerder
#' et al. (IN REVIEW)
#'
#'
#' Methods:
#' Details on the sap flow data and scenario description
#' is in detail described in Huang et al, 2017, New Phytologist paper
#' entitled: The effect of plant water storage on water fluxes within
#' the coupled soil-plant system
#'
#'
#' The dataset contains the following labels (columns):
#' \itemize{
#'
#' \item SFday (Numeric) sap flow [kg h-1] per time step frequency of 1 minute.
#' \item timestep (Numeric) Timesteps throughout the duration of an entire day,
#' i.e. 24h
#' \D1O
#' }
#'
#'
#' @docType data
#' @keywords datasets
#' @name SFday
#' @usage data(SFday)
#' @format
#'
NULL
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Defines functions Bprep PSI0calc SoilRootCond SWIFT_H SWIFT_SB
Documented in Bprep PSI0calc SoilRootCond SWIFT_H SWIFT_SB
#'##############################################################################
#'##############################################################################
#'
#' @title SWIFT model (Stable Water Isotope Fluctuation within Trees)
#'
#'
#' @param ARtot Description: The total fine root area area of the focal plant
#' [in m2];
#' Structure: One value, representative of the studied plant.
#' @param Ax Description: The total lumen area [in m2];
#' Structure: One value, representative of the studied plant.
#' @param B Description: The comunity plant Root length density at every
#' discrete soil layer
#' - Results from the function Bprep - [in m m-3];
#' Structure: A discrete vector of n elements, with n the number
#' of soil layers.
#' @param beta Description: Factor in the root length density distribution
#' function for the focal plant;
#' Structure: One value, derived from Jackson et al. (1996),
#' table 1.
#' @param betaCom Description: Factor in the root length density distribution
#' function of the plant community
#' (required to distribute the root length over all
#' soil layers)
#' Structure: One value, derived from Jackson et al. (1996),
#' table 1.
#' @param D2Hxylem Description: The deuterium signature at stem base - derived
#' from the function SWIFT_SB [in permil, VSMOW];
#' Structure: A discrete vector of n elements, with n the
#' number of timesteps sampled.
#' @param D2Hsoil Description: Vector representing the stable water isotopic
#' siganture profile with depth
#' [in permil, VSMOW];
#' Structure: A discrete vector of n elements, with n the
#' number of soil layers.
#' @param dZ Description: Thickness of the soil layer [in m];
#' Structure: One value, Samples should be taken at discrete
#' depths which have the same thickness.
#' @param hom Description: A vector of studied measurement heights [in m];
#' Structure: The size of the vector is defined by the interest
#' of the user.
#' @param k Description: Plant specific total soil-to-root conductance at
#' each specific specific soil layer [in s-1];
#' Structure: A vector - results from the function SoilRootCond
#' - and has n elements corresponding to the number of
#' soil layers.
#' @param kr Description: The root membrane permeability [s-1];
#' Structure: One value, representative of the studied plant.
#' @param PSIs Description: Soil water potential at the each specific soil
#' layer [in m];
#' Structure: A vector of n element, where n corresponds to the
#' number of soil layers;
#' Note: The water potentials per soil layer is currently
#' considered static in time.
#' @param R0 Description: Factor in the root lenght density distribution per
#' unit of soil, for entire plant community;
#' NOTE: Provide a Positive value!!
#' Structure: One value,representative of the studied plant, here
#' derived from Huang et al, 2017.
#' @param SF Description: Instantaneous sap flow over time [in m^3 s-1];
#' Structure: A vector of n elements, where n corresponds to the
#' number of timesteps.
#' @param Soiltype Description: Type of soil layer (Sand; Loamy Sand;
#' Sandy Loam; Silt Loam; Loam; Sandy Clay Loam;
#' Silty Clay Loam; Clay Loam;Sandy Clay;
#' Silty Clay; Clay);
#' Structure: A Character string.
#' @param t Description: Cumulative time steps [in s];
#' Structure: A vector.
#' @param tstud Description: By the user defined timesteps to which an output
#' is required [in second after initialisation];
#' Structure: A vector with n elements defined by the user;
#' Note: When an output is needed for all values, then
#' tstud = t.
#' @param tF Description: Measurement frequence per hour [in measurement
#' points per hour];
#' Structure: One value, defined by the user;
#' Note: Lower numbers will increase the speed of the
#' model, but for graphical display, higher values
#' are prefered.
#' @param Z Description: A vector of Soil depth [in m];
#' Structure: A discrete vector of n elements, where n
#' corresponds to the number of soil layers.
#'
#'
#'
#' @author Hannes De Deurwaerder, Marco D. Visser, Matteo Detto, Pascal Boeckx,
#' Felicien Meunier and Hans Verbeeck.
#'
#' @examples
#' \dontrun{
#'
#' # Initialisation of parameters
#' n <- 20 # Multiple number of days studied, needed for spin up
#' # of the model.
#' tF <- 60 # Time frequence of measurements per hour
#' # [in measurments per h].
#' t <- seq(0,24*n,length.out = 24*tF*n) # Discrete time vector [in h].
#' dZ <- 0.001 # Thickness of sampled layer [in m].
#' L <- 1 # maximum soil depth [in m].
#' Z <- seq(dZ,L,dZ) # Discrete depth vector centered [in m].
#' kr <- 10*10^(-10) # root membrane permeability [in s^(-1)]
#' # (source: Leuschner et al, 2004).
#' DBH <- 0.213 # Diameter at breast height [in m].
#' LA <- 0.136 # Lumen Fraction, i.e. lumen area/sapwood area [%]
#' # (derived from Zanne et al, 2010) [table 2, F-value].
#' Ax <- LA * ((1.582*((DBH*100)^1.764)) /10^4)
#' # Total lumen area of the studied tree [m^2],i.e. the
#' # lumena area fraction multiplied by sapwood area
#' # estimated from the DBH (Meinzer et al, 2001) .
#' ARtot <- exp(0.88*log(pi*2*(100*DBH/2)^2)-2)
#' # ARtot in [m^2] via DBH[in cm] (Cermak et al, 2006)
#' R0 <- 438688 # Derived from Huang et al, 2017.
#' betaCom <- 0.976 # Derived from Jackson et al., 1996 [table 1,
#' # beta-term].
#' beta <- 0.976 # Derived from Jackson et al., 1996 [table 1,
#' # beta-term].
#' # Source the SWIFT model
#' require("SWIFT")
#'
#'
#' # Prepare additional input data of the model
#' data(SFday)
#' # SF for one day, time frequency: every min, expressed in [kg h-1].
#' # This data is derived from Huang et al, 2017.
#' uch <- (60/tF)*60*1000 # unit conversion: h to sec. and kg to m3
#' SF <- c(rep(SFday,n))/(uch) # repetition of SF day over n prefered days.
#'
#' # Soil water potential curve with depth, from Meissner et al, 2012
#' CTpsi <- 101.97 # Conversion factor between MPa and m H2O.
#' Apsi <- 198.4455; Bpsi <- 448.9092; Cpsi <- 255.5937;
#' # Apsi, Bpsi and Cpsi are values derived from Meissner et al 2012 data
#' # from optimizing the function defined in the paper of De Deurwaerder
#' # et al. (In Review).
#' PSIs <- ((Apsi + Bpsi *log(Z) - Cpsi*Z^2) /10000) * CTpsi
#'
#' # isotopic water isotopic signature with depth from Meissner et al, 2012
#' lsoil <- -73.98008; msoil <- 0.148735; soildev <- 0.001
#' # lsoil and msoil are values derived from the Meissner et al 2012 data
#' # from optimizing the function defined in the paper of De Deurwaerder
#' # et al. (In Review).
#' D2Hsoil <- lsoil * (Z+soildev)^msoil
#'
#' # NOTE that the data of Meissner et al 2012 is accessible and can be sourced
#' # as provided below:
#' data(MeissnerData)
#'
#'
#' # Using the SWIFT model functions
#'
#' # A. Root density distribution
#' B <- Bprep(betaCom, R0, Z) # output is in [m m^(-3)].
#'
#' # B. the soil-root conductance
#' k <- SoilRootCond(B, kr, PSIs, Z, 'Silt Loam')
#'
#' # C. the ARi
#' devio=beta^(100*Z)*(1-beta^(100*dZ))
#' ARi=ARtot*devio/sum(devio)
#'
#' # D. Isotopic signature fluctuation at stem base
#' StemBase <- SWIFT_SB(ARi, D2Hsoil, k, PSIs, SF, t, Z)
#'
#' # E. Isotopic signature at specific height and time
#' tstud <- seq(2*(24*tF), 3*(24*tF),1)
#' # Provides the data of day 3 of the modeled tree.
#' # (We selected day 3 to assure proper spin up of the model).
#' hom <- 1.3 # measured at standard coring height, 1.3 m.
#' D2Htree <- SWIFT_H( Ax, StemBase, hom, SF, tstud, tF)
#'
#' # E. The Water potential at stem base
#' PSI0vec <- PSI0calc(ARi, k, PSIs, Sf, t, Z)/CTpsi
#' # CTpsi to convert from m to MPa.
#'
#'
#' # Field data corroborating the hypothesis of strong isotopic fluctuations
#' # along the length of a stem:
#' data(Fielddata)
#'
#'
#' # Making a simple plot of the SWIFT output
#'
#' # MAKING A SIMPLE PLOT OF THE SWIFT OUTPUT
#' ylabel=expression(paste(delta,""^"2","H"," [","\211",", vsmow]"))
#' plot(t,StemBase, xlim= c( min(tstud)/tF, max(tstud)/tF), type='l',
#' lty=2, col='grey', ylab=ylabel, xlab='timesteps', mgp = c(2, 0.8, 0))
#' # Plot the signature fluctuations at the stem base
#' lines( tstud/tF, D2Htree, col='blue')
#' # Plot the signature fluctuations at the height defined by the user
#' legend( 'bottomleft', c('at stembase',paste0('at ',hom,' m')),
#' lty=c(2,1), col=c('grey', 'blue'), bty='n', cex=0.7)
#'
#' load()
#' }
#'
#' @return Provided by function
#' - SWIFT_SB: Vector of isotopic signatures at the stem base for
#' every timestep [in permil, VSMOW].
#' - SWIFT_H: Vector of isotopic signatures at by the user defined
#' height and time [in permil, VSMOW].
#' - SoilRootCond: Vector of soil to root conductivity for every
#' defined soil layer [in s-1].
#' - PSI0calc: Vector of water potential at stem base for every
#' timestep [in m H2O].
#' - Bprep: Vector of root length distribution for every defined
#' soil layer [in m m-3].
#'
#' @export
#'
#'##############################################################################
#'##############################################################################
SWIFT_SB<-function(ARi=NULL, D2Hsoil=NULL, k=NULL, PSIs=NULL, SF=NULL, t=NULL, Z=NULL){
#===============================================================================
# SWIFT MODEL PART A
#===============================================================================
# STABLE WATER ISOTOPES CALUCLATED AT STEM BASE
#-------------------------------------------------------
# Function description: This function calculates the isotopic signature at the
# stem base at every timestep.
# Declare empty vectors
D2Hxylem=rep(NaN,length(t))
D2Hvec <- fi <- RWU <- rep(NaN,length(Z))
for (a in 2:length(t)){
# first value is NaN due to model spin-up.
if((SF[a]==0 & a!=1) | (is.nan(SF[a]))){
D2Hxylem[a]<-ifelse(is.nan(D2Hxylem[a-1]),NaN,D2Hxylem[a-1])
# When SF=0, water is stagnant --> signature at t=0 equals signature
# at t=-1.
}else{
# Water potential at stem base
PSI0 <- (sum(k*ARi*(PSIs-Z)) - SF[a])/ sum(k*ARi)
RWU0 <- k*ARi*(PSIs-Z - PSI0)
# make sure no negative RWU flows occurs
not.use <- which(RWU0<0)
RWU <- RWU0
while (sum(not.use)>0){
not.use <- which(RWU<0)
RWU[not.use] <- 0
use <- which(RWU>0)
ARiuse = ARi[use]
kuse = k[use]
Zuse = Z[use]
PSIsuse = PSIs[use]
PSI0 <- (sum(kuse*ARiuse*(PSIsuse-Zuse)) - SF[a]) / sum(kuse*ARiuse)
RWU[use] <- kuse*ARiuse*(PSIsuse-Zuse - PSI0)
}
fi <- RWU/sum(RWU, na.rm=TRUE)
D2Hxylem[a] <- sum(fi*D2Hsoil, na.rm=TRUE)
}
}
return(D2Hxylem)
}
################################################################################
################################################################################
SWIFT_H<-function(Ax=NULL, D2Hxylem=NULL, hom=NULL, SF=NULL, tstud=NULL,
tF=NULL){
#===============================================================================
# SWIFT MODEL PART B
#===============================================================================
# STABLE WATER ISOTOPES CALUCLATED AT BY THE USER DEFINED HEIGHT AND TIME
#-------------------------------------------------------------------------
# Function description: This function calculates the isotopic signature at
# by the user defined height of measurement and timing of sampling.
hts <- length( as.vector(hom) ) # vector of user defined heights.
tms <- length( as.vector(tstud)) # vector of user defined sample times.
D2Hxylem_hom <- matrix(NA,hts,tms)
uc <-((60/tF)*60) # unit conversion.
# Cumulative SF vector
cumSF=cumsum(SF) # Cumulative sapflow
cumH=uc*cumSF/Ax # Cumulative Height reached by the sapflow
cumH[which(cumSF==0)]<-NaN
# No sapflow yet, this is the spinup, should be set at NA
for (ab in 1:tms){
a=tstud[ab] # By user defined timesteps.
for (w in 1:hts){
# First value will be NA, for spin
if (a==1){
D2Hxylem_hom[w,ab] <- NaN
next
}
# for signatures at stem base, i.e. h=0
if (hom[w]==0 && a!=1){D2Hxylem_hom[w,ab] <- D2Hxylem[a]
next
}
# for all other cases
# for the spinup values
if(is.nan(cumH[a])){D2Hxylem_hom[w,ab] <- D2Hxylem[a-1]
next
}else{
# not spinup values
CumHt <- cumH -(cumH[a])+ hom[w]
Minind <- which(abs(CumHt)==min(abs(CumHt), na.rm=TRUE))
# Total delay for the sapflow to reach hom (time)
# Delay extends the datarange?
if (length(Minind)==0){
D2Hxylem_hom[w,ab] <- NaN # only a problem during model spin up
}else{
delay=a-Minind[1]
D2Hxylem_hom[w,ab] <- D2Hxylem[a-delay]
}
rm(delay); rm(Minind)
}
}
}
return(D2Hxylem_hom)
}
################################################################################
################################################################################
SoilRootCond <- function(B=NULL, kr=NULL, PSIs=NULL, Z=NULL, Soiltype=NULL ){
#===============================================================================
# PLANT SPECIFIC TOTAL SOIL TO ROOT CONDUCTANCE
#===============================================================================
# Function description: This function calculates the soil to root conductance
# while considering the soiltype.
# Soiltype conform the soil texture triangle, with corresponding
# values from clapp and hornberger (1978).
if(Soiltype == 'Sand'){
ksmax=1.056/(100*60); PSIsat=-0.121; b=4.05; sigmasat=0.395}
if(Soiltype == 'Loamy Sand'){
ksmax=0.938/(100*60); PSIsat=-0.090; b=4.38; sigmasat=0.410}
if(Soiltype == 'Sandy Loam'){
ksmax=0.208/(100*60); PSIsat=-0.218; b=4.90; sigmasat=0.435}
if(Soiltype == 'Silt Loam'){
ksmax=0.0432/(100*60); PSIsat=-0.786; b=5.30; sigmasat=0.485}
if(Soiltype == 'Loam'){
ksmax=0.0417/(100*60); PSIsat=-0.478; b=5.39; sigmasat=0.451}
if(Soiltype == 'Sandy Clay Loam'){
ksmax=0.0378/(100*60); PSIsat=-0.299; b=7.12; sigmasat=0.420}
if(Soiltype == 'Silty Clay Loam'){
ksmax=0.0102/(100*60); PSIsat=-0.356; b=7.75; sigmasat=0.477}
if(Soiltype == 'Clay Loam'){
ksmax=0.0147/(100*60); PSIsat=-0.630; b=8.52; sigmasat=0.476}
if(Soiltype == 'Sandy Clay'){
ksmax=0.0130/(100*60); PSIsat=-0.153; b=10.40; sigmasat=0.426}
if(Soiltype == 'Silty Clay'){
ksmax=0.0062/(100*60); PSIsat=-0.490; b=10.40; sigmasat=0.492}
if(Soiltype == 'Clay'){
ksmax=0.0077/(100*60); PSIsat=-0.405; b=11.40; sigmasat=0.482}
# calculate k using the Clapp and Hornberger (1978) equation.
k=ks<-rep(NA,length(Z))
for (h in 1:length(Z)){
ks[h] <- ksmax * (PSIsat/PSIs[h])^(2+3/b)
k[h]<- kr * ks[h]*sqrt(pi*B[h]) / (0.53*kr + ks[h]*sqrt(pi*B[h]) )
}
return(k)
}
################################################################################
################################################################################
PSI0calc <- function(ARi=NULL, k=NULL, PSIs=NULL, SF=NULL, t=NULL, Z=NULL){
#===============================================================================
# WATER POTENTIAL AT STEM BASE
#===============================================================================
# Function description: This function calculates the water potential at stem
# base at every timestep, indirectly derived from the sap flow.
PSI0vec=rep(NA,length(t))
for (a in 1:length(t)){
# Water potential at stem base
PSI0 <- (sum(k*ARi*(PSIs-Z)) - SF[a])/ sum(k*ARi)
RWU0 <- k*ARi*(PSIs-Z - PSI0)
# make sure no negative RWU flows occurs
not.use <- which(RWU0<0)
RWU <- RWU0
while (sum(not.use)>0){
not.use <- which(RWU<0)
RWU[not.use] <- 0
use <- which(RWU>0)
ARiuse = ARi[use]
kuse = k[use]
Zuse = Z[use]
PSIsuse = PSIs[use]
PSI0 <- (sum(kuse*ARiuse*(PSIsuse-Zuse)) - SF[a]) / sum(kuse*ARiuse)
RWU[use] <- kuse*ARiuse*(PSIsuse-Zuse - PSI0)
}
# assign PSI0 of one time point to the vector of PSI at stem base
PSI0vec[a] <- PSI0
}
return(PSI0vec)
}
################################################################################
################################################################################
Bprep<-function( beta=NULL, R0=NULL, Z=NULL){
#===============================================================================
# ROOT LENGTH DISTRIBUTION FUNCTION
#===============================================================================
# Function description: This function calculates root length distribution
# cf. Huang et al, 2016.
B <- rep(NA,length(Z))
UnCo <- 100 # unit conversion from m to cm.
for (h in 1:length(Z)){
B[h]= -R0* beta^(UnCo*Z[h])*log(beta, base=exp(1))
}
return(B)
}
################################################################################
################################################################################
#' The Laussat Trees and Liana isotopic signature along the lenght of
#' the plant dataset.
#'
#'
#' General Description:
#' This dataset contains both sample extraction information, i.e.
#' timing and height of sampling, the diameter, growth form type and species
#' name, as well as the isotopic deuterium and oxygen 18 signature of the
#' sampled plant
#'
#'
#' This dataset may not be
#' used without previous written permission from the
#' owner.
#'
#'
#' Ownership: Hannes De Deurwaerder <Hannes_de_deurwaerder@hotmail.com>
#'
#' Research Location:
#' Within the research forest of LAUSSAT, French Guyana.
#' Sampled species all are located on a white sandy subsoil.
#'
#' Dataset abstract:
#' These data are being used to evaluate hypothesized mechanisms of
#' xylem water isotopic variation along the length of a plant
#'
#'
#' Methods:
#' The methods of sampling are in much detail described in
#' De Deurwaerder et al. (2018) Tree Physiology. 38(7). p.1071-1083
#'
#'
#' The dataset contains the following labels (columns):
#' \itemize{
#' \item Number (Integer) Unique identifier per growth form.
#' \item Type (Character) Indication of the growth form, i.e. liana or tree.
#' \item Family (Character) Identification of the scientific plant family.
#' \item Family (Character) Species (Character) identification of the scientific
#' species name.
#' \item Date (Character) Date of sampling in the year 2017.
#' \item Time (Character) Time of sampling.
#' \item Hour (Integer) Hour of measurement.
#' \item Minute (Integer) Minute of measurement.
#' \item Height (Numeric) Height of measurement [in m].
#' \item H2 (Numeric) Xylem deuterium isotopic signature [in permil, VSMOW].
#' \item stdev_H2 (Numeric) Standard deviation on the xylem deuterium isotopic
#' signature [in permil, VSMOW], resulting from the Picarro measurement.
#' \item O18 (Numeric) Xylem O18 isotopic signature [in permil, VSMOW].
#' \item stdev_O18 (Numeric)Standard deviation on the xylem O18 isotopic
#' signature [in permil, VSMOW], resulting from the Picarro measurement.
#' \item Diam (Numeric) Diameter of the growth form [in cm].
#' \D1O
#' }
#'
#'
#' @docType data
#' @keywords datasets
#' @name Fielddata
#' @usage data(Fielddata)
#' @format
#'
NULL
################################################################################
################################################################################
#' The Meissner et al 2012 of water isotopic signatures
#' and the water potential in the soil.
#'
#' General Description:
#' This data, providing an overview of both deuterium and oxygen 18
#' signatures as well as the water potential gradient discussed in the paper
#' of meissner et al, 2012 papers entitled: (i)Partitioning of soil water among
#' canopy trees during a soil desiccation period in a temperate mixed forest'
#' and (ii) Soil water uptake by trees using water stable isotopes
#' (d2H and d18O)- a method testregarding soil moisture, texture and carbonate
#'
#'
#' This dataset is freely accessible from the papers of Meissner et al 2012.
#' However, users should feel enclined to cite Meissner et al 2012 when using
#' the data
#'
#'
#' Ownership: M. Meissner <mmeissn3@gwdg.de>
#'
#'
#' Research Location:
#' Soil samples were collected at the Hainich National Park close to the vilage
#' of Weberstedt in Central Germany. Height of sampling was approx. 350 m a.s.l.
#' and the region experiences a subatlatic climate with a mean anual
#' precipitation around 600 mm and st.dev. around 50mm.
#' More details are provided in both articles of Meissner et al, 2012.
#'
#'
#' Dataset abstract:
#' These data is being used to test the hypothesized mechanisms of xylem water
#' isotopic variation along the length of a plant.
#'
#' Methods:
#' The methods of sampling are in much detail described in both papers of
#' Meissner et al, 2012. More specifically, this data forms the driver data of
#' the SWIFT model (1) "Soil water uptake by trees using water stable isotopes
#' (d2H and d18O) - a method testregarding soil moisture, texture and carbonate
#' (2) Partitioning of soil water among canopy trees during a soil
#' desiccation period in a temperate mixed forest"
#'
#'
#' The dataset contains the following labels (columns):
#' \itemize{
#' \item Meissner_depth (Numeric) The average depth of the samples soil layer
#' [in m].
#' \item Meissner_d2h (Numeric) The deuterium isotopic siganture of the bulk
#' soil water at the sampled depths [in permil, VMSOW].
#' \item Meissner_sdd2h (Numeric) The standard deviations on the deuterium
#' isotopic siganture of the bulk soil
#' water at the sampled depths [in permil, VMSOW].
#' \item Meissner_d18o(Numeric) The oxygen 18 isotopic siganture of the bulk
#' soil water at the sampled depths [in permil, VMSOW].
#' \item Meissner_sdd18o (Numeric) The standard deviations on the oxygen 18
#' isotopic siganture of the bulk soil
#' water at the sampled depths [in permil, VMSOW].
#' \item Meissner_psi (Numeric) The water potential at the sampled soil depths
#' [in hPa].
#' \item Meissner_sdpsi (Numeric) The standard deviations on the water potential
#' at the sampled soil depths [in hPa].
#' \D1O
#' }
#'
#'
#' @docType data
#' @keywords datasets
#' @name MeissnerData
#' @usage data(MeissnerData)
#' @format
#'
NULL
################################################################################
################################################################################
#' The daily sap flow derived from Huang et al 2017.
#'
#'
#' General Description:
#' The daily sap flow flux [in kg h-1] derived from the Huang et al 2017 paper,
#' day 11 of scenario 6. Data is interpollated to derive a timefrequency per
#' minute.
#'
#'
#' This dataset is freely accessible from the paper of Huang et al. 2017
#' However, Users should feel enclined to cite Huang et al. 2017 when using the
#' data. paper title: The effect of plant water storage on water fluxes within
#' the coupled soil-plant system.
#'
#'
#' Ownership: Cheng-Wei Huang <chengweihuang1206@gmail.com>
#'
#'
#' Research Location:
#' Details on the research location and scenario description
#' is in detail described in Huang et al, 2017, New Phytologist paper
#' entitled: The effect of plant water storage on water fluxes within
#' the coupled soil-plant system
#'
#'
#' Dataset abstract:
#' These data are being used to evaluate hypothesized mechanisms of
#' xylem water isotopic variation along the length of a plant.
#' This data is used to drive the SWIFT model, as presented by De Deurwaerder
#' et al. (IN REVIEW)
#'
#'
#' Methods:
#' Details on the sap flow data and scenario description
#' is in detail described in Huang et al, 2017, New Phytologist paper
#' entitled: The effect of plant water storage on water fluxes within
#' the coupled soil-plant system
#'
#'
#' The dataset contains the following labels (columns):
#' \itemize{
#'
#' \item SFday (Numeric) sap flow [kg h-1] per time step frequency of 1 minute.
#' \item timestep (Numeric) Timesteps throughout the duration of an entire day,
#' i.e. 24h
#' \D1O
#' }
#'
#'
#' @docType data
#' @keywords datasets
#' @name SFday
#' @usage data(SFday)
#' @format
#'
NULL
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