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Automating the Raw Data to Model Input Process Using Flexible Open Source Tools

  • C. De Mulder
  • T. Flameling
  • J. Langeveld
  • Y. Amerlinck
  • S. Weijers
  • I. Nopens
Conference paper
Part of the Lecture Notes in Civil Engineering book series (LNCE, volume 4)

Abstract

The availability of dynamic influent data is of crucial importance for model development, as it provides the model input needed realistic dynamic simulations. Data analysis and reconciliation of such data are however often very time-consuming tasks, making that, even when some online influent data is indeed available, the option is often chosen to generate influent data in one way or the other. A lot of information contained in the available data is lost in that way. This contribution showcases a python package that allows for a streamlined data analysis workflow and provides possibilities for data analysis, validation and gap filling, with as main goal to recover and use as much (influent) data as possible. In the end, this provides a means towards more scientifically sound dynamic simulations and model calibration and validation, while limiting the time spent on data reconciliation.

Keywords

Data analysis Modelling Python package 

Notes

Acknowledgements

The authors would like to express their gratitude towards Waterboard De Dommel for both the funding of this research and the smooth cooperation.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • C. De Mulder
    • 1
  • T. Flameling
    • 2
  • J. Langeveld
    • 3
  • Y. Amerlinck
    • 1
  • S. Weijers
    • 2
  • I. Nopens
    • 1
  1. 1.BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Faculty of Bioscience EngineeringGhent UniversityGhentBelgium
  2. 2.Waterschap De DommelBoxtelThe Netherlands
  3. 3.Delft University of TechnologyDelftThe Netherlands

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