Enhanced Markov-type Categorical Prediction with geophysical soft constraints for hydrostratigraphic modeling

Guo, Liming; Hermans, Thomas; Benoit, Nicolas; Dudal, David; Van De Vijver, Ellen; Madsen, Rasmus; Nørgaard, Jesper; Deleersnyder, Wouter

doi:10.5194/hess-30-1421-2026

Articles | Volume 30, issue 5

https://doi.org/10.5194/hess-30-1421-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-30-1421-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 30, issue 5

Research article

|

17 Mar 2026

Research article |

| 17 Mar 2026

Enhanced Markov-type Categorical Prediction with geophysical soft constraints for hydrostratigraphic modeling

Liming Guo, Thomas Hermans, Nicolas Benoit, David Dudal, Ellen Van De Vijver, Rasmus Madsen, Jesper Nørgaard, and Wouter Deleersnyder

Data sets

3D hydrogeological layer model of the Egebjerg area L. T. Andersen https://doi.org/10.22008/FK2/FHP1XK

Short summary

Understanding what lies beneath the ground is often difficult due to limited drilling data. Our research combines geostatistical method with large-scale geophysical surveys to create more realistic underground maps. We developed a method that merges both data sources to better predict underground layers, helping improve decisions in groundwater management and future geological studies.