Combining ground-based and airborne em through Artificial Neural Networks for modelling glacial till under saline groundwater conditions

Hydrology and Earth System Sciences

Volumn 16, Issue 8, 2012, Pages 3061-3074

  Gunnink, J L ^a   Bosch, J H A ^a   Siemon, B ^b   Roth, B ^c,d   Auken, E ^c  

^a TNO   (Netherlands)

^b FEDERAL INSTITUTE FOR GEOSCIENCES AND NATURAL RESOURCES BGR   (Germany)

^c AARHUS UNIVERSITY   (Denmark)

^d Aarhus Geophysics Aps ^*  (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

AIRBORNE ELECTROMAGNETIC; CONE PENETRATION TESTS; DRILLING DATA; ELECTRICAL CONDUCTIVITY; GEOLOGICAL PARAMETERS; GEOPHYSICAL DATA; GLACIAL TILL; GROUND BASED; HYDROGEOLOGICAL; LEARNING RULES; SALINE GROUNDWATER;

CLIMATE CHANGE; ELECTRIC CONDUCTIVITY; GLACIAL GEOLOGY; GROUNDWATER FLOW; NEURAL NETWORKS;

GROUNDWATER;

ARTIFICIAL NEURAL NETWORK; ELECTRICAL CONDUCTIVITY; ELECTROMAGNETIC METHOD; GROUND-BASED MEASUREMENT; GROUNDWATER FLOW; HYDROGEOLOGY; SALINITY; TILL;

EID: 84869400102     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-16-3061-2012     Document Type: Article

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