Tutorial"

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

1. Install from GitHub

if(!require("remotes")) { install.packages("remotes") }
remotes::install_github(repo = "KWB-R/kwb.hantush", dependencies = TRUE)

2. Using the package

2.1 Loading the package

library(kwb.hantush)

2.2 Model validation

For comparing the implementation of the Hantush equation, 1967 the results are compared to the USGS benchmark example (page 25). The results can be visualized with the following code:

### Comparision of R results to all 
### eight benchmark models in one plot
plotModelComparison()

### Comparision of R results to all 
### eight benchmark models in multiple plots (one plot for each model)
plotModelComparison(layout=c(1,1))

3. How to perform model runs?

3.1 Model parameterisation

baseProps <- baseProperties( time = 2^(0:6), ## day, for 6 different times !
                             infiltrationRate = 1, ## meter / day
                             basinWidth = 10, ## meter
                             basinLength = 50, ## meter
                             horizConductivity = 10, ## meter / day
                             iniHead = 10, ## meter
                             specificYield = 0.2)

3.2 Running the model

res <- hantushDistancesBaseProps(baseProps = baseProps)

3.3 Plotting the results

cols <- length(unique(res$dat[[res$changedBaseProp.Name]]))
mainTxt <- sprintf("Changed baseProperty: %s", res$changedBaseProp.Name)
xyplot(WLincrease ~ x,
       groups=res$dat[[res$changedBaseProp.Name]],
       data=res$dat,
       type="b",
       auto.key=list(columns=cols),
       main=mainTxt)


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kwb.hantush documentation built on Sept. 17, 2019, 5:03 p.m.