Advertisement

Water Resources Management

, Volume 33, Issue 2, pp 539–553 | Cite as

A Regional Scale Hydrostratigraphy Generated from Geophysical Data of Varying Age, Type, and Quality

  • Troels VilhelmsenEmail author
  • Pernille Marker
  • Nikolaj Foged
  • Thomas Wernberg
  • Esben Auken
  • Anders Vest Christiansen
  • Peter Bauer-Gottwein
  • Steen Christensen
  • Anne-Sophie Høyer
Article
  • 72 Downloads

Abstract

In the present study, we show how persistent management and collection of hydrological and geophysical data at a national scale can be combined with innovative analysis methods to generate decision support tools for groundwater and surface water managers. This is exemplified by setting up a regional scale groundwater model in an area with geophysical data of varying age, type, and quality. The structure for the regional model is derived from a newly developed resistivity clay-fraction cluster analysis. This modelling strategy can be used in combination with local detailed geological modelling thus utilizing the detailed expertise locally, while securing a cost-effective (price vs. performance) solution to the numerical simulations of the regional scale water balance. In this way we avoid unwanted boundary effects on the local model simulations due to the presence of artificial numerical boundaries located proximate to the areas of interest. In this application, it is particularly important that boundary conditions are remote, due to the presence of a dense network of buried valley structures. Simulated impacts of groundwater abstraction from two existing well-fields spread through the valley system far beyond the local focus areas of the study.

Keywords

Geophysics Groundwater modelling Groundwater management Data integration MODFLOW-USG Buried valleys 

Notes

Acknowledgements

This study was financed by the HyGEM project, project no. 11-116763. The funding is provided by Innovation Fund Denmark.

Compliance with Ethical Standards

Conflict of Interest

None

References

  1. Arnold J, Allen P (1999) Automated methods for estimating baseflow and ground water recharge from streamflow records. J Am Water Resour Assoc 35(2):411–424CrossRefGoogle Scholar
  2. Artimo A, Sarapera S, Ylander I (2008) Methods for integrating an extensive geodatabase with 3D modeling and data management tools for the Virttaankangas artificial recharge project, southwestern Finland. Water Resour Manag 22(12):1723–1739CrossRefGoogle Scholar
  3. Aster RC, Borchers B, Thurber CH (2005) Parameter estimation and inverse problems. Elsevier Academic Press, AmsterdamGoogle Scholar
  4. Atkinson L, Ross M, Stumpf A (2014) Three-dimensional hydrofacies assemblages in ice-contact/proximal sediments forming a heterogeneous 'hybrid' hydrostratigraphic unit in Central Illinois, USA. Hydrogeol J 22(7):1605–1624CrossRefGoogle Scholar
  5. Auken E, Christiansen AV, Jacobsen BH, Foged N, Sørensen KI (2005) Piecewise 1D laterally constrained inversion of resistivity data. Geophys Prospect 53:497–506CrossRefGoogle Scholar
  6. Christiansen AV, Auken E, Sørensen KI (2006) The transient electromagnetic method. In: Kirsch R (ed) Groundwater geophysics. A tool for hydrogeology. Springer, New York, pp 179–224CrossRefGoogle Scholar
  7. Danielsen JE, Auken E, Jørgensen F, Søndergaard VH, Sørensen KI (2003) The application of the transient electromagnetic method in hydrogeophysical surveys. J Appl Geophys 53(4):181–198CrossRefGoogle Scholar
  8. DHI (2009) MIKE SHE user manual, volume 1: user guide. DHI, HørsholmGoogle Scholar
  9. Doherty J (2015) Calibration and uncertainty analysis for complex environmental models. Watermark Numerical Computing, BrisbaneGoogle Scholar
  10. Doherty J (2016) PEST, Model-Independent Parameter Estimation. User Manual Part I: PEST, SENSAN and Global Optimisers, BrisbaneGoogle Scholar
  11. Foged N, Auken E, Christiansen AV, Sørensen KI (2013) Test site calibration and validation of airborne and ground based TEM systems. Geophysics 78(2):E95–E106CrossRefGoogle Scholar
  12. Foged N, Marker PA, Christiansen AV, Bauer-Gottwein P, Jørgensen F, Høyer A-S, Auken E (2014) Large scale 3D-modeling by integration of resistivity models and borehole data through inversion. Hydrol Earth Syst Sci 18:4349–4362CrossRefGoogle Scholar
  13. Harbaugh AW, Banta ER, Hill MC, McDonald MG (2000) MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model - User Guide to Modularization Concepts and the Ground-Water Flow Process, Reston, VirginiaGoogle Scholar
  14. He X, Koch J, Sonnenborg T, Jorgensen F, Schamper C, Refsgaard J (2014) Transition probabilitybased stochastic geological modeling using airborne geophysical data and borehole data. Water Resour Res 50:3147–3169Google Scholar
  15. Henriksen H, Troldborg L, Nyegaard P, Sonnenborg T, Refsgaard J, Madsen B (2003) Methodology for construction, calibration and validation of a national hydrological model for Denmark. J Hydrol 280(1–4):52–71CrossRefGoogle Scholar
  16. Herzog B, Larson D, Abert C, Wilson S, Roadcap G (2003) Hydrostratigraphic modeling of a complex, glacial-drift aquifer system for importation into MODFLOW. Ground Water 41(1):57–65CrossRefGoogle Scholar
  17. Høyer A-S, Jørgensen F, Sandersen PBE, Viezzoli A, Møller I (2015) 3D geological modelling of a complex Buried-Valley network delineated from borehole and AEM data. J Appl Geophys 2015(122):94–102CrossRefGoogle Scholar
  18. Jain A (2010) Data clustering: 50 years beyond K-means. Pattern Recogn Lett 31(8):651–666CrossRefGoogle Scholar
  19. Jørgensen F, Sandersen PBE, Auken E (2003) Imaging buried quaternary valleys using the transient electromagnetic method. J Appl Geophys 53:199–213CrossRefGoogle Scholar
  20. Jørgensen F, Møller RR, Nebel L, Jensen N, Christiansen AV, Sandersen P (2013) A method for cognitive 3D geological voxel modelling of AEM data. Bull Eng Geol Environ 72(3–4):421–432CrossRefGoogle Scholar
  21. Kessler H, Mathers S, Sobisch H (2009) The capture and dissemination of integrated 3D geospatial knowledge at the British Geological Survey using GSI3D software and methodology. Comput Geosci 35(6):1311–1321CrossRefGoogle Scholar
  22. Kronborg C, Bender H, Bjerre R, Friborg R, Jacobsen HO, Kristiansen L, Rasmussen P, Sørensen PR, Larsen G (1990) Glacial stratigraphy of east and Central Jutland. Boreas 19:273–287CrossRefGoogle Scholar
  23. Marker PA, Foged N, He X, Christiansen AV, Refsgaard A, Auken E, Bauer-Gottwein P (2015) Performance evaluation of groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs. HESS 19:3875–3890Google Scholar
  24. Mazac O, Kelly WE, Landa I (1985) A hydrogeophysical model for relations between electrical and hydraulic-properties of aquifers. J Hydrol 79(1–2):1–19CrossRefGoogle Scholar
  25. Møller I, Verner H, Søndergaard VH, Flemming J, Auken E, Christiansen AV (2009) Integrated management and utilization of hydrogeophysical data on a national scale. Near Surf Geophys 7(5–6):647–659CrossRefGoogle Scholar
  26. Panday S, Langevine CD, Niswonger RG, Ibaraki M, Hughes JD (2015) MODFLOW-USG version 1.3.00: An unstructured grid version of MODFLOW for simulating groundwater flow and tightly coupled processes using a control volume finite-difference formulation: U.S. Geological Survey Software Release, 01 December 2015Google Scholar
  27. Ross M, Parent M, Lefebvre R (2005) 3D geologic framework models for regional hydrogeology and land-use management: a case study from a quaternary basin of southwestern Quebec, Canada. Hydrogeol J 13(5–6):690–707CrossRefGoogle Scholar
  28. Sandersen PBE, Jørgensen F (2003) Buried quaternary valleys in western Denmark—occurrence and inferred implications for groundwater resources and vulnerability. J Appl Geophys 53(4):229–248CrossRefGoogle Scholar
  29. Søndergaard V, Thomsen R, Dyrsø O, Nyholm T, Fuglsang E, Thorling L, Misser PV, Hansen B (2004) Redegørelse for grundvandsressourcerne i Århus-Nord området. Vandforsyning - Delrepport 1 (In danish), Aarhus AmtGoogle Scholar
  30. Sonnenborg T, Christensen B, Nyegaard P, Henriksen H, Refsgaard J (2003) Transient modeling of regional groundwater flow using parameter estimates from steady-state automatic calibration. J Hydrol 273(1–4):188–204CrossRefGoogle Scholar
  31. Sørensen KI (1996) Pulled Array Continuous Electrical Profiling. First Break, 14:85–90Google Scholar
  32. Sørensen K, Auken E (2004) SkyTEM – a new high-resolution helicopter transient electromagnetic system. Explor Geophys 35:191–199CrossRefGoogle Scholar
  33. Sørensen K, Auken E, Thomsen P (2000) TDEM in groundwater mapping - a continuous approach. In: Proceedings of the symposium on the application of geophysics to engineering and environmental problems, 2000, pp 485–491Google Scholar
  34. van der Kamp G, Maathuis H (2012) The unusual and large drawdown response of Buried-Valley aquifers to pumping. Ground Water 50(2):207–215CrossRefGoogle Scholar
  35. Viezzoli A, Auken E, Munday T (2009) Spatially constrained inversion for quasi 3D modelling of airborne electromagnetic data - an application for environmental assessment in the lower Murray region of South Australia. Explor Geophys 40:173–183CrossRefGoogle Scholar
  36. Vignoli G, Fiandaca G, Christiansen AV, Kirkegaard C, Auken E (2015) Sharp spatially constrained inversion with applications to transient electromagnetic data. Geophys Prospect 63(1):243–255CrossRefGoogle Scholar
  37. Wu J (2012) Advances in K-means clustering: a data mining thinking. Springer, New YorkCrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Troels Vilhelmsen
    • 1
    Email author
  • Pernille Marker
    • 2
  • Nikolaj Foged
    • 1
  • Thomas Wernberg
    • 3
  • Esben Auken
    • 1
  • Anders Vest Christiansen
    • 1
  • Peter Bauer-Gottwein
    • 2
  • Steen Christensen
    • 1
  • Anne-Sophie Høyer
    • 4
  1. 1.Department of GeoscienceAarhus UniversityAarhus CDenmark
  2. 2.DTU Department of Environmental EngineeringKgs. LyngbyDenmark
  3. 3.NIRASAarhus CDenmark
  4. 4.GEUSAarhus CDenmark

Personalised recommendations