Description Usage Arguments Details Value Examples
Determine zero flow conditions (Δ Tmax; or Δ Vmax)
according to four methods; namely,
1) predawn (pd
),
2) moving-window (mw
),
3) double regression (dr
),
and 4) environmental-dependent (ed
) as applied in Peters et al. 2018.
The function can provide (Δ Tmax values and subsequent K values for all methods.
All outputs are provided in a list
including the input data and calculated outputs.
1 2 3 4 5 6 7 8 9 10 11 |
input |
An |
methods |
Character vector of the requested Δ Tmax methods.
Options include |
zero.end |
Numeric, optionally defines the end of the predawn period. Values should be in minutes (e.g. predawn conditions until 08:00 = 8 * 60). When not provided, the algorithm will automatically analyse the cyclic behaviour of the data and define the day length. |
zero.start |
Numeric, optionally defines the beginning of the predawn period. Values should be in minutes (e.g., 01:00 = 1*60). |
interpolate |
Logical: if |
det.pd |
Logical; if |
max.days |
Numeric, defines the number of days which the |
ed.window |
Numeric, defines the length of the period considered for assessing the environmental conditions and stable Δ Tmax values. |
vpd.input |
An |
sr.input |
An |
sel.max |
Optional |
criteria |
Numeric vector, thresholds for the |
df |
Logical; if |
There are a variety of methods which can be applied to determine zero-flow conditions.
Zero-flow conditions are required to calculate K = (Δ Tmax - Δ T) / Δ T.
A detailed description on the methods is provided by Peters et al. (2018).
In short, the pd
method entails the selection of daily maxima occurring prior to sunrise.
This method assumes that during each night zero-flow conditions are obtained.
The algorithm either requires specific times within which it searches for a maximum,
or it analyses the cyclic pattern within the data and defines this time window.
The mw
method uses these predawn Δ Tmax values
and calculates the maximum over a multi-day moving time-window (e.g., 7 days).
The dr
methods is applied by calculating the mean over predawn Δ Tmax
with a specified multi-day window, removing all values below the mean,
and calculating a second mean over the same multi-day window and uses these values as Δ Tmax.
The ed
method selects predawn Δ Tmax values based upon 2-hour averaged environmental
conditions prior to the detected time for the predawn Δ Tmax.
These environmental conditions include low vapour pressure deficit (in kPa) and low solar irradiance
(e.g., in W m-2). In addition, the coefficient of variation (cv) of predawn Δ Tmax are scanned for low values to
ensure the selection of stable zero-flow conditions.
A named list
of zoo
time series or data.frame
objects in the appropriate format for further processing.
List items include:
Δ Tmax time series as determined by the pd
method.
Δ Tmax time series as determined by the mw
method.
Δ Tmax time series as determined by the dr
method.
Δ Tmax time series as determined by the ed
method.
daily predawn Δ Tmax as determined by pd
.
daily predawn Δ Tmax as determined by mw
.
daily predawn Δ Tmax as determined by dr
.
daily predawn Δ Tmax as determined by ed
.
exact predawn Δ Tmax values detected with pd
.
exact predawn Δ Tmax values detected with ed
.
Δ T input data.
data.frame
of the applied environmental and variability criteria used within ed
.
data.frame
of applied methods to detect Δ Tmax.
K values calculated by using the pd
method.
K values calculated by using the mw
method.
K values calculated by using the dr
method.
K values calculated by using the ed
method.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | #perform Delta Tmax calculations
raw <- is.trex(example.data(type = "doy"),
tz = "GMT", time.format = "%H:%M", solar.time = TRUE,
long.deg = 7.7459, ref.add = FALSE)
input <- dt.steps(input = raw, start = "2014-05-08 00:00",
end = "2014-07-25 00:50", time.int = 15, max.gap = 60,
decimals = 6, df = FALSE)
input[which(input<0.2)]<- NA
output.max <- tdm_dt.max(input, methods = c("pd", "mw", "dr"),
det.pd = TRUE, interpolate = FALSE,
max.days = 10, df = FALSE)
str(output.max)
plot(output.max$input, ylab = expression(Delta*italic("V")))
lines(output.max$max.pd, col = "green")
lines(output.max$max.mw, col = "blue")
lines(output.max$max.dr, col = "orange")
points(output.max$all.pd, col = "green", pch = 16)
legend("bottomright", c("raw", "max.pd", "max.mw", "max.dr"),
lty = 1, col = c("black", "green", "blue", "orange") )
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.