Article (Scientific journals)
Bayesian Evidential Learning: a field validation using push-pull tests
Hermans, Thomas; Lesparre, Nolwenn; De Schepper, Guillaume et al.
2019In Hydrogeology Journal, 27 (5), p. 1661-1672
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Keywords :
Bayesian Evidential Learning; BEL; shallow alluvial aquifers; Experimental design; Heat tracer; ATES; Modelling; Push pull tests
Abstract :
[en] Recent developments in uncertainty quantification show that a full inversion of model parameters is not always necessary to forecast the range of uncertainty of a specific prediction in Earth sciences. Instead, Bayesian evidential learning (BEL) uses a set of prior models to derive a direct relationship between data and prediction. This recent technique has been mostly demonstrated for synthetic cases. This paper demonstrates the ability of BEL to predict the posterior distribution of temperature in an alluvial aquifer during a cyclic heat tracer push-pull test. The data set corresponds to another push-pull experiment with different characteristics (amplitude, duration, number of cycles). This experiment constitutes the first demonstration of BEL on real data in a hydrogeological context. It should open the range of future applications of the framework for both scientists and practitioners.
Disciplines :
Geological, petroleum & mining engineering
Author, co-author :
Hermans, Thomas ;  Universiteit Gent - UGent > Géologie
Lesparre, Nolwenn;  Université de Strasbourg > École et observatoire des sciences de la Terre
De Schepper, Guillaume;  Aquale SPRL > R&D
Robert, Tanguy ;  Université de Liège - ULiège > Département ArGEnCo > Hydrogéologie & Géologie de l'environnement
Language :
English
Title :
Bayesian Evidential Learning: a field validation using push-pull tests
Publication date :
August 2019
Journal title :
Hydrogeology Journal
ISSN :
1431-2174
eISSN :
1435-0157
Publisher :
Springer, Germany
Volume :
27
Issue :
5
Pages :
1661-1672
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
ATHENA
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique
Available on ORBi :
since 12 November 2019

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