sw: Swartzendruber infiltration parameter optimisation in R

In gowusu/vadose: The estimation of saturated hydraulic conductivity and soil water retention Curves in the vadose zone

Description

This function optimises Swartzendruber (1987) cumulative infiltration (I) or infiltration rate (i) parameters: As, Ks and S.

Usage

sw(data, time, I, As = 0.1, S = 0.1, Ks = 0.1, group = NULL)

## Default S3 method:
sw(data, time, I, As = 0.1, S = 0.1, Ks = 0.1,
  group = NULL)

## S3 method for class 'sw'
predict(object, time = NULL, ...)

## S3 method for class 'sw'
plot(x, xlab = "Time(Minutes)", ylab = "Cumulative (mm)",
  main = NULL, layout = NULL, ...)

## S3 method for class 'sw'
print(x, ...)

## S3 method for class 'sw'
coef(object, ...)

Arguments

data	dataframe. It can contain data with column names of "time" and "I"
time	character or numeric. The name of time variable in the dataframe. If the "data" parameter contains "time", this will be ignored. The unit must be in seconds.
I	cumulative infiltration (I) or infiltration rate (i) [mm]
As	an optimised parameter
S	numeric. sorptivity parameter
Ks	saturated hydraulic conductivity
group	character. The name of the group variables if the data is from different areas.
object	Model output object
...	Any other graphical parameter
x	a return object of the function.
xlab	x label of the plot
ylab	y label of the plot
main	Title of the plot
layout	plot layout

Value

• As: optimised As parameter

• Ks: optimised saturated hydraulic conductivity[L/T]

• S: optimised sorptivity [LT^-0.5]

• output: output of the group simulation

Author(s)

George Owusu

References

Swartzendruber, D. (1987). A quasi-solution of Richards equation for the downward infiltration of water into soil. Water Resour Res, 23, 809-817.

Examples

data=read.csv(system.file("ext","sys","exampleBEST.csv",package="vadose"))
sw1<-sw(data=data,time="time",I="I")
print(gof(sw1))
plot(sw1)
predict(sw1)
coef(sw1)
gof(sw1)

#infiltration rate
data=read.csv(system.file("ext","sys","infiltration2.csv",package="vadose"))
assin_breko<- subset(data, ID=="41A20_1")
swr<-sw(data=assin_breko,time="minutes",I="cm.hr")

#group simulation
swg<-sw(data=data,time="minutes",I="cm.hr",group="ID")
coef(swg)

gowusu/vadose documentation built on May 17, 2019, 7:59 a.m.