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Estimating flow parameter distributions using ground-penetrating radar and hydrological measurements during transient flow in the vadose zone
Institution:1. Sorbonne Université, CNRS, EPHE, UMR 7619 METIS, Paris, France;2. Department Water Resources and Drinking Water, Swiss Federal Institute of Aquatic Science and Technology, EAWAG, Dubendorf, Switzerland;3. Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland;4. Univ. Rennes, CNRS, Géosciences Rennes - UMR 6118, Rennes, France;5. Applied and Environmental Geophysics Group, Institute of Earth Sciences, University of Lausanne, Switzerland;1. Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Milan 20133, Italy;2. Tethys srl, Viale Lombardia 11, Milan 20131, Italy
Abstract:Methods for estimating the parameter distributions necessary for modeling fluid flow and contaminant transport in the shallow subsurface are in great demand. Soil properties such as permeability, porosity, and water retention are typically estimated through the inversion of hydrological data (e.g., measurements of capillary pressure and water saturation). However, ill-posedness and non-uniqueness commonly arise in such non-linear inverse problems making their solutions elusive. Incorporating additional types of data, such as from geophysical methods, may greatly improve the success of inverse modeling. In particular, ground-penetrating radar (GPR) methods have proven sensitive to subsurface fluid flow processes and appear promising for such applications. In the present work, an inverse technique is presented which allows for the estimation of flow parameter distributions and the prediction of flow phenomena using GPR and hydrological measurements collected during a transient flow experiment. Specifically, concepts from the pilot point method were implemented in a maximum a posteriori (MAP) framework to allow for the generation of permeability distributions that are conditional to permeability point measurements, that maintain specified patterns of spatial correlation, and that are consistent with geophysical and hydrological data. The current implementation of the approach allows for additional flow parameters to be estimated concurrently if they are assumed uniform and uncorrelated with the permeability distribution. (The method itself allows for heterogeneity in these parameters to be considered, and it allows for parameters of the petrophysical and semivariogram models to be estimated as well.) Through a synthetic example, performance of the method is evaluated under various conditions, and some conclusions are made regarding the joint use of transient GPR and hydrological measurements in estimating fluid flow parameters in the vadose zone.
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