Abstract: Modelling depth of the redox interface in high resolution at national scale using machine learning and geostatistics (AGU Fall Meeting 2018)

Modelling depth of the redox interface in high resolution at national scale using machine learning and geostatistics

Julian Koch¹, Simon Stisen², Jens Christian Refsgaard¹, Ernstsen Vibeke³, Peter Roll Jakobsen³ and Anker L Højberg¹, (1)Geological Survey of Denmark and Greenland, Department of Hydrology, Copenhagen, Denmark, (2)Geological Survey of Denmark and Greenland, Department of Hydrology, København K, Denmark, (3)Geological Survey of Denmark and Greenland, Department of Geochemistry, Copenhagen, Denmark

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