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  4. Integrated methods for stochastic ensemble aquifer modelling (ENSEMBLE)
Project Title
Integrated methods for stochastic ensemble aquifer modelling (ENSEMBLE)
Internal ID
14692
Principal Investigator
Renard, Philippe  
Status
Completed
Start Date
March 1, 2011
End Date
February 28, 2014
Investigators
Huggenberger, Peter
Linde, Niklas
Bayer, Peter
Caers, Jef
Ginsbourger, David
Lunati, Ivan
Organisations
Centre d'hydrogéologie et de géothermie  
Identifiants
https://libra.unine.ch/handle/20.500.14713/2602
-
https://libra.unine.ch/handle/123456789/1404
Keywords
Hydrogeology Numerical modeling Alluvial system Geology Geophysics Uncertainty Multiple-point statistics numerical modelling hydrogeophysics ensemble modelling geostatistics alluvial deposits inverse methods error analysis model simplification kriging optimization
Description
The state of the art in modeling groundwater systems is related to developments in geology, physics, geophysics, hydrogeology, and mathematics. Too often, the research in these areas is pursued independently by different teams and is therefore not integrated around a unique vision. The aim of the ENSEMBLE project is therefore to integrate the recent developments in quantitative geology, hydrology, numerical, and stochastic modeling to increase our ability to understand and predict complex hydrological systems. The teams involved in the ENSEMBLE project (ETH Zürich, Stanford University, Universities of Basel, Bern, Neuchâtel and Lausanne) will focus their research on developing new integrated methods (multiple point statistics, joint hydrogeological and geophysical inversion, fast methods for uncertainty analysis, etc.) for the characterization of the heterogeneity of alluvial systems and for the efficient stochastic ensemble simulation of groundwater flow and solute transport in those systems. Four common field sites corresponding to different alluvial systems (Tagliamento, Thur, Birs, Herten) will be used to illustrate and test the concepts and methods developed in the project.
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