Ruggeri, Paolo; Irving, James; Gloaguen, Erwan et Holliger, Klaus (2013). Regional-scale integration of multiresolution hydrological and geophysical data using a two-step Bayesian sequential simulation approach. Geophysical Journal International , vol. 194 , nº 1. pp. 289-303. DOI: 10.1093/gji/ggt067.
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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.
| Type de document: | Article |
|---|---|
| Mots-clés libres: | probabilistic forecasting; downhole methods; tomography; hydrogeophysics; permeability and porosity |
| Centre: | Centre Eau Terre Environnement |
| Date de dépôt: | 06 déc. 2016 21:44 |
| Dernière modification: | 06 déc. 2016 21:44 |
| URI: | https://espace.inrs.ca/id/eprint/3502 |
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