Articles | Volume 22, issue 10
https://doi.org/10.5194/hess-22-5485-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-5485-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Oct 2018
Research article |
| 24 Oct 2018
| 24 Oct 2018
Contributions to uncertainty related to hydrostratigraphic modeling using multiple-point statistics
Adrian A. S. Barfod
CORRESPONDING AUTHOR
Department of Groundwater and Quaternary Geological Mapping,
Geological Survey of Denmark & Greenland (GEUS), C.F. Møllers Allé
8, 8000 Aarhus C, Denmark
Hydrogeophysics Group, Department of
Geoscience, Aarhus University, C.F. Møllers Allé 4, 8000 Aarhus C,
Denmark
Troels N. Vilhelmsen
Hydrogeophysics Group, Department of
Geoscience, Aarhus University, C.F. Møllers Allé 4, 8000 Aarhus C,
Denmark
Flemming Jørgensen
Department of Groundwater and Quaternary Geological Mapping,
Geological Survey of Denmark & Greenland (GEUS), C.F. Møllers Allé
8, 8000 Aarhus C, Denmark
Anders V. Christiansen
Hydrogeophysics Group, Department of
Geoscience, Aarhus University, C.F. Møllers Allé 4, 8000 Aarhus C,
Denmark
Anne-Sophie Høyer
Department of Groundwater and Quaternary Geological Mapping,
Geological Survey of Denmark & Greenland (GEUS), C.F. Møllers Allé
8, 8000 Aarhus C, Denmark
Julien Straubhaar
Centre d'Hydrogéologie et de Géothermie (CHYN), Université
de Neuchâtel, Neuchâtel, Switzerland
Ingelise Møller
Department of Groundwater and Quaternary Geological Mapping,
Geological Survey of Denmark & Greenland (GEUS), C.F. Møllers Allé
8, 8000 Aarhus C, Denmark
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Cited
14 citations as recorded by crossref.
- QuickSampling v1.0: a robust and simplified pixel-based multiple-point simulation approach M. Gravey & G. Mariethoz https://doi.org/10.5194/gmd-13-2611-2020
- 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. https://doi.org/10.5194/hess-25-2759-2021
- Estimation using multiple-point statistics Ó. Jóhannsson & T. Hansen https://doi.org/10.1016/j.cageo.2021.104894
- Assessing the Impact of Fractured Zones Imaged by ERT on Groundwater Model Prediction: A Case Study in a Chalk Aquifer in Voort (Belgium) B. Van Riet et al. https://doi.org/10.3389/frwa.2021.783983
- Development of a high-resolution 3D geological model for landfill leachate risk assessment A. Høyer et al. https://doi.org/10.1016/j.enggeo.2018.12.015
- Multiple-point statistical modeling of three-dimensional glacial aquifer heterogeneity for improved groundwater management N. Kawo et al. https://doi.org/10.1007/s10040-023-02658-x
- 3D hydrostratigraphic architecture of a Late Pleistocene buried valley infill at Kurikka, west-central Finland A. Åberg et al. https://doi.org/10.1016/j.quaint.2025.110080
- 3D hydrostratigraphic and hydraulic conductivity modelling using supervised machine learning T. Tilahun & J. Korus https://doi.org/10.1016/j.acags.2023.100122
- Probabilistic Modeling and Uncertainty Simulations of National-Scale Hydrostratigraphic Models: An Example from Denmark R. Madsen et al. https://doi.org/10.1007/s11004-025-10263-9
- A probabilistic approach to establishing the resistivity-lithology relationship using co-located tTEM data and lithological logs S. Nielsen et al. https://doi.org/10.1016/j.jappgeo.2026.106245
- Combining Clustering Methods With MPS to Estimate Structural Uncertainty for Hydrological Models T. Vilhelmsen et al. https://doi.org/10.3389/feart.2019.00181
- Combining geophysical and geological datasets to improve a conceptual aquifer model of the Oak Openings Region in northwest Ohio, USA A. Ogunkoya et al. https://doi.org/10.1007/s12665-023-11197-3
- Conditioning of multiple-point statistics simulations to indirect geophysical data S. Levy et al. https://doi.org/10.1016/j.cageo.2024.105581
- Incorporating interpretation uncertainties from deterministic 3D hydrostratigraphic models in groundwater models T. Enemark et al. https://doi.org/10.5194/hess-28-505-2024
14 citations as recorded by crossref.
- QuickSampling v1.0: a robust and simplified pixel-based multiple-point simulation approach M. Gravey & G. Mariethoz https://doi.org/10.5194/gmd-13-2611-2020
- 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. https://doi.org/10.5194/hess-25-2759-2021
- Estimation using multiple-point statistics Ó. Jóhannsson & T. Hansen https://doi.org/10.1016/j.cageo.2021.104894
- Assessing the Impact of Fractured Zones Imaged by ERT on Groundwater Model Prediction: A Case Study in a Chalk Aquifer in Voort (Belgium) B. Van Riet et al. https://doi.org/10.3389/frwa.2021.783983
- Development of a high-resolution 3D geological model for landfill leachate risk assessment A. Høyer et al. https://doi.org/10.1016/j.enggeo.2018.12.015
- Multiple-point statistical modeling of three-dimensional glacial aquifer heterogeneity for improved groundwater management N. Kawo et al. https://doi.org/10.1007/s10040-023-02658-x
- 3D hydrostratigraphic architecture of a Late Pleistocene buried valley infill at Kurikka, west-central Finland A. Åberg et al. https://doi.org/10.1016/j.quaint.2025.110080
- 3D hydrostratigraphic and hydraulic conductivity modelling using supervised machine learning T. Tilahun & J. Korus https://doi.org/10.1016/j.acags.2023.100122
- Probabilistic Modeling and Uncertainty Simulations of National-Scale Hydrostratigraphic Models: An Example from Denmark R. Madsen et al. https://doi.org/10.1007/s11004-025-10263-9
- A probabilistic approach to establishing the resistivity-lithology relationship using co-located tTEM data and lithological logs S. Nielsen et al. https://doi.org/10.1016/j.jappgeo.2026.106245
- Combining Clustering Methods With MPS to Estimate Structural Uncertainty for Hydrological Models T. Vilhelmsen et al. https://doi.org/10.3389/feart.2019.00181
- Combining geophysical and geological datasets to improve a conceptual aquifer model of the Oak Openings Region in northwest Ohio, USA A. Ogunkoya et al. https://doi.org/10.1007/s12665-023-11197-3
- Conditioning of multiple-point statistics simulations to indirect geophysical data S. Levy et al. https://doi.org/10.1016/j.cageo.2024.105581
- Incorporating interpretation uncertainties from deterministic 3D hydrostratigraphic models in groundwater models T. Enemark et al. https://doi.org/10.5194/hess-28-505-2024
Saved (final revised paper)
Latest update: 13 Jun 2026
Short summary
The focus of this study is on the uncertainty related to using multiple-point statistics (MPS) for stochastic modeling of the upper 200 m of the subsurface. The main research goal is to showcase how MPS methods can be used on real-world hydrogeophysical data and show how the uncertainty related to changing the underlying MPS setup propagates into the finalized 3-D subsurface models.
The focus of this study is on the uncertainty related to using multiple-point statistics (MPS)...
