Wrap your model in an R package!

The groundwater drawdown model WTAQ-2, provided by the United States Geological Survey for free, has been "wrapped" into an R package, which contains functions for writing input files, executing the model engine and reading output files. By calling the functions from the R package a sensitivity analysis, calibration or validation requiring multiple model runs can be performed in an automated way. Automation by means of programming improves and simplifies the modelling process by ensuring that the WTAQ-2 wrapper generates consistent model input files, runs the model engine and reads the output files without requiring the user to cope with the technical details of the communication with the model engine. In addition the WTAQ-2 wrapper automatically adapts cross-dependent input parameters correctly in case one is changed by the user. This assures the formal correctness of the input file and minimises the effort for the user, who normally has to consider all cross-dependencies for each input file modification manually by consulting the model documentation. Consequently the focus can be shifted on retrieving and preparing the data needed by the model. Modelling is described in the form of version controlled R scripts so that its methodology becomes transparent and modifications (e.g. error fixing) trackable. The code can be run repeatedly and will always produce the same results given the same inputs. The implementation in the form of program code further yields the advantage of inherently documenting the methodology. This leads to reproducible results which should be the basis for smart decision making.

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1. 1
   www.kompetenz-wasser.de
   kwb-r.github.io
   your in an
   Michael Rustler &
   Hauke Sonnenberg
   Kompetenzzentrum Wasser Berlin
   @MichaelRustler
   mrustl
   !
   

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2. 2
   www.kompetenz-wasser.de
   kwb-r.github.io
   Introduction
   Environmental
   models
   your in an
   !
   

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3. 3
   www.kompetenz-wasser.de
   kwb-r.github.io
   Generic
   Case-specific
   Sensitivity analysis
   Calibration
   Challenges
   (Usually) not implemented in
   Generic
   

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4. 4
   www.kompetenz-wasser.de
   kwb-r.github.io
   Generic
   Case-specific
   Sensitivity analysis
   Calibration
   Challenges
   (Usually) not implemented in
   Generic
   “If you’re going to do something
   three times or more, you should think
   about writing a small package”(Peng,2016)
   

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5. 5
   www.kompetenz-wasser.de
   kwb-r.github.io
   Well drawdown model
   Freely available at:
   http://water.usgs.gov/ogw/wtaq
   

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6. 6
   www.kompetenz-wasser.de
   kwb-r.github.io
   Usual workflow
   Input
   

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7. 7
   www.kompetenz-wasser.de
   kwb-r.github.io
   Our approach
   Input
   createConfiguration()
   writeInputFile() runModelEngine() readOutputFile()
   

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8. 8
   www.kompetenz-wasser.de
   kwb-r.github.io
   functions:
   1. Create model configuration (R list)
   2. Write input file (text file)
   3. Run model engine (text file)
   4. Read output file (R data.frame)
   Model engine (source / binary)
   +
   

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9. 9
   www.kompetenz-wasser.de
   kwb-r.github.io
   Automated workflow
   

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10. 10
    www.kompetenz-wasser.de
    kwb-r.github.io
    https://github.com/KWB-R/kwb.wtaq
    Thanks to for sponsoring this work within the project
    Tutorial: https://kwb-r.github.io/kwb.wtaq
    EPANET (USEPA)
    VS2DI (USGS)
    Summary
    “Wrapped“ models:
    Method: Wrap your model! (Sonnenberg et al. 2014)
    http://doi.org/10.13140/RG.2.1.2140.3683
    WTAQ-2 (USGS)
    

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11. 11
    www.kompetenz-wasser.de
    kwb-r.github.io
    @MichaelRustler
    mrustl
    slides at https://github.com/mrustl/useR-2016
    Michael Rustler &
    Hauke Sonnenberg
    Kompetenzzentrum Wasser Berlin
    

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