Hydrogeological data constitute an enormous and largely unexploited potential source of information. Tapping this potential requires proper data management, analysis and modelling tools. Groundwater Monitor will allow hydrogeologists to get the most out of their groundwater data, while minimizing the effort and costs of the process.

Groundwater Monitor benefits:

Efficient data processing and reliable, validated data. Data form the basis of every analysis, model or research, and, as such, their proper management is crucial. Flexible and clear analyses and visualizations. These are not only useful to assess the quality of the data themselves, but also to gain understanding of the structure and functioning of the system from which they originate. Evidence-based, parsimonious results and conclusions. As the time series model structure is transparent and contains a minimum of assumptions, the results and conclusions are generally accurate and clear.

Manual

The Groundwater Monitor tool comes with a comprehensive manual on the user-friendly Menyanthes program, covering  the installation procedure, the functions and graphic functionalities. Step by step, it leads you through the program, and also describes how to interpret and validate data.

Together with the Menyanthes software program, scientific background material and an introductory course for first-time users of the software, the manual helps you to optimise your use of groundwater data. It also helps in explaining and eliminating differences in interpretation of the data.
Download the Menyanthes manual.

Software & downloads

Groundwater Monitor can be applied for monitoring network design, data management, data analysis and visualization, and time series modelling. It offers a solution for groundwater monitoring, from initial design, via crude data, down to the final conclusions and results, which are the objectives of the monitoring. By combining these functions in an all-in-one software solution, synergy between the different functions is guaranteed.

Groundwater Monitor implementation steps:

  1. Information collection:
    importing groundwater level data into Menyanthes. Various data formats can be imported.
  2. Information processing:
    Menyanthes stores all data on groundwater levels, explanatory series and time series models in a single database file. You can choose the type of information you want to extract, e.g., explanations, time series, location maps.
  3. Results presentation:
    the tool can present data, statistics, results and various graphs.
  4. Context. 

Training

There are several forms of support available to ensure that you optimise your use of the Groundwater Monitor tool, and that you are updated on all the latest developments. Specifically, you can make use of the following options to suit your particular situation:

  • An introductory course (in company) for first-time users, with computer exercises and application examples.
  • A helpdesk (by e-mail and telephone) for software support.
  • Expanded or modified Groundwater Monitor functionalities to create tailored solutions.
  • Consultancy services, research and support on groundwater monitoring issues in general.
  • Access to background material, including scientific publications and an introduction to the methods and theory.

Publications

Mentioned in: 5 publications
Enrolled in: 78 Cases in 25 Countries

  • Von Asmuth, J. R., Grootjans, A. P., and Van der Schaaf, S.
    “Over de dynamiek van peilen en fluxen in vennen en veentjes”
    Eindrapport deel 2, OBN-onderzoek
  • Von Asmuth, J. R., Grootjans, A. P., and Van der Schaaf, S.
    “Herstel van biodiversiteit en landschapsecologische relaties in het natte zandlandschap”
    Rapport nr. 2011/OBN147-2-NZ, Bosschap, bedrijfschap voor bos en natuur, (Driebergen, 2011).
  • Von Asmuth , J. R., Van der Schaaf , S., Grootjans, A. P., and Maas, C.,
    Vennen en veentjes: (niet-)ideale systemen voor niet-lineaire tijdreeksmodellen
    Stromingen, 18(2) (2012), 97-112.
  • Von Asmuth, J.R.,
    “Groundwater System Identification through Time Series Analysis”.
    PhD thesis, 2012 (ISBN 9789051550795).
  • Maas, C.,
    Valkuilen in de tijdreeksanalyse: Het geval Terwisscha
    Stromingen, 18(2) (2012),43-76.

Tool Expert(s)

Jos von Asmuth

Jos von Asmuth

Scientific researcher and content manager Menyanthes, KWR

+31 (0) 30 60 69 512
jos.von.asmuth@kwrwater.nl