Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

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Serval ID
serval:BIB_2F3E9F64683E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach
Journal
Geophysical Journal International
Author(s)
Ruggeri P., Irving J., Gloaguen E., Holliger K.
ISSN-L
0956-540X
Publication state
Published
Issued date
2013
Peer-reviewed
Oui
Volume
194
Pages
289-303
Language
english
Notes
Ruggeri2013
Abstract
Significant progress has been made with regard to the quantitative
integration of geophysical and hydrological data at the local scale
for the purpose of improving predictions of groundwater flow and
solute transport. However, extending corresponding approaches to
the regional scale still represents one of the major challenges in
the domain of hydrogeophysics. To address this problem, we have developed
a regional-scale data integration methodology based on a two-step
Bayesian sequential simulation approach. Our objective is to generate
high-resolution stochastic realizations of the regional-scale hydraulic
conductivity field in the common case where there exist spatially
exhaustive but poorly resolved measurements of a related geophysical
parameter, as well as highly resolved but spatially sparse collocated
measurements of this geophysical parameter and the hydraulic conductivity.
To integrate this multi-scale, multi-parameter database, we first
link the low- and high-resolution geophysical data via a stochastic
downscaling procedure. This is followed by relating the downscaled
geophysical data to the high-resolution hydraulic conductivity distribution.
After outlining the general methodology of the approach, we demonstrate
its application to a realistic synthetic example where we consider
as data high-resolution measurements of the hydraulic and electrical
conductivities at a small number of borehole locations, as well as
spatially exhaustive, low-resolution estimates of the electrical
conductivity obtained from surface-based electrical resistivity tomography.
The different stochastic realizations of the hydraulic conductivity
field obtained using our procedure are validated by comparing their
solute transport behaviour with that of the underlying ?true? hydraulic
conductivity field. We find that, even in the presence of strong
subsurface heterogeneity, our proposed procedure allows for the generation
of faithful representations of the regional-scale hydraulic conductivity
structure and reliable predictions of solute transport over long,
regional-scale distances.
Open Access
Yes
Create date
25/11/2013 18:41
Last modification date
25/09/2019 6:08
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