approx_standprop: Create a daily sequence of stand properties from parameters...

In pschmidtwalter/LWFBrook90R: Simulate Evapotranspiration and Soil Moisture with the SVAT Model LWF-Brook90

Create a daily sequence of stand properties from parameters using interpolation

Description

Uses yearly values of inter-annual vegetation development values (e.g. sai, height, densef, age) and interpolates them to a daily sequence.

Usage

approx_standprop(
  x_yrs,
  y,
  y_ini = NULL,
  xout_yrs = x_yrs,
  use_growthperiod = FALSE,
  startdoy = 121,
  enddoy = 279,
  approx.method = "constant",
  return_xout = FALSE
)

Arguments

x_yrs	A sequence of years or a single year.
y	Vector of the same length as x_yrs. If approx.method = 'linear', the values are interpreted to be valid at the end of the respective year in x_yrs
y_ini	Initial value used as a starting point for linear interpolation. Interpreted to be valid at the 1st of January of the first year in x_yrs. Ignored if approx.method = 'constant'.
xout_yrs	Vector of years for which output is generated. May be longer or shorter than x_yrs. For years outside x_yrs, the value of the closest data extrem is returned.
use_growthperiod	Logical: Use startdoy and enddoy for linear interpolation? If TRUE, yearly changes take place between startdoy and enddoy, othe wise from end of year to end of the year after.
startdoy	A single value or vector of the same length as x_yrs, with the day of year when growth begins.
enddoy	A single value or vector of the same length as x_yrs, with the day of year when growth cessates.
approx.method	Name of interpolation method ('constant' or 'linear').
return_xout	Logical: If true, daily values of y and a date vector are returned in a data.frame.

Details

For approx.method = 'constant', the value of y is returned for the whole respective year in x_yrs, which results in a yearly changing step function. If approx.method = 'linear', the values of y are interpolated between the years in x_yrs, and interpreted to be reached at the 31st of December of the respective x_yrs. In this case, y_ini is required as an initial value, from which the sequence is interpolated to the first value of y. The linear changes are either accomplished between 31st to 31st of December of the years in x_yrs, or during the growing season only (use_growingperiod = TRUE).

Value

A vector of interpolated daily values

Examples

years <- 2002:2004
height_yearly <- c(20.2,20.8,21.3)

# constant 'interpolation'
height_c <- approx_standprop(x_yrs = years,
                             y = height_yearly)

# linear interpolation
height_ini <- 19.1
height_l <- approx_standprop(x_yrs=years,
                             y = height_yearly,
                             y_ini = height_ini,
                             approx.method = 'linear')

# use growthperiod
height_l_gp <- approx_standprop(x_yrs = years,
                                y = height_yearly,
                                y_ini = height_ini,
                                use_growthperiod = TRUE,
                                startdoy = 121,
                                enddoy = 279,
                                approx.method = 'linear')

dates <- seq.Date(from = as.Date(paste0(min(years),"-01-01")),
                  to = as.Date(paste0(max(years),"-12-31")),
                  by = "day")
plot(dates, height_c,
     type = "l", lwd = 2, col = "black",
     ylim = c(19,22), ylab = "height [m]", xlab = "", xpd = TRUE)
lines(dates, height_l,
      col = "blue", lwd = 2)
lines(dates, height_l_gp,
      col = "green", lwd = 2)
legend("topleft", legend = c("'constant'", "'linear'",
                             "'linear', 'use_growthperiod'"),
       col  = c("black", "blue", "green"),  lwd = 2, pch = NULL,
       bty = "n")

pschmidtwalter/LWFBrook90R documentation built on Jan. 27, 2024, 1:48 p.m.