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  4. Ice volume and basal topography estimation using geostatistical methods and GPR measurements: Application on the Tsanfleuron and Scex Rouge glacier, Swiss Alps
 
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Ice volume and basal topography estimation using geostatistical methods and GPR measurements: Application on the Tsanfleuron and Scex Rouge glacier, Swiss Alps

Auteur(s)
Neven, Alexis
Dall'Alba, Valentin
Juda, Przemyslaw 
Collaborateurs de la Faculté des sciences 
Straubhaar, Julien 
Centre d'hydrogéologie et de géothermie 
Renard, Philippe 
Centre d'hydrogéologie et de géothermie 
Date de parution
2021-7
In
The Cryosphere Discussions
No
2021
De la page
161
A la page
188
Revu par les pairs
1
Résumé
Ground Penetrating Radar (GPR) is nowadays widely used for determining glacier thickness. However, this method provides thickness data only along the acquisition lines and therefore interpolation has to be made between them. Depending on the interpolation strategy, calculated ice volumes can differ and can lack an accurate error estimation. Furthermore, glacial basal topography is often characterized by complex geomorphological features, which can be hard to reproduce using classical 5 interpolation methods, especially when the conditioning data are sparse or when the morphological features are too complex. This study investigates the applicability of multiple-point statistics (MPS) simulations to interpolate glacier bedrock topography using GPR measurements. In 2018, a dense GPR data set was acquired on the Tsanfleuron Glacier (Switzerland). The results obtained with the direct sampling MPS method are compared against those obtained with kriging and sequential Gaussian simulations (SGS) on both a synthetic data set – with known reference volume and bedrock topography – and the real data 10 underlying the Tsanfleuron glacier. Using the MPS modelled bedrock, the ice volume for the Scex Rouge and Tsanfleuron Glacier is estimated to be 113.9 ± 1.6 Miom3 . The direct sampling approach, unlike the SGS and the kriging, allowed not only an accurate volume estimation but also the generation of a set of realistic bedrock simulations. The complex karstic geomorphological features are reproduced, and can be used to significantly improve for example the precision of under-glacial flow estimation.
URI
https://libra.unine.ch/handle/123456789/30421
DOI
10.5194/tc-2021-161
Autre version
https://doi.org/10.5194/tc-2021-161
Type de publication
Resource Types::text::journal::journal article
Dossier(s) à télécharger
 main article: 2023-01-11_110_5530.pdf (25.3 MB)
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