Articles | Volume 30, issue 5
https://doi.org/10.5194/hess-30-1421-2026
https://doi.org/10.5194/hess-30-1421-2026
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

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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.
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