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Abstract

The use of geophysics for the characterization of the near surface is requiring more and more frequently that data be analysed quantitatively to offer meaningful information for the specific discipline object of investigation. This is true for all applications, including environmental studies, hydrology, soil science and geotechnics. This tendency leads substantially to overtaking of the classical approach to geophysics as a pure imaging technique, and requires in-depth understanding of the information contained in each specific physical measurement. Irrespective of the specific application, the geophysical response of the near surface is essentially controlled by a combination of geological (“static”) and ambient (“dynamic”) factors. The latter include moisture content and temperature variations. The separation of static and dynamic factors is the key step towards a quantitative use of near surface geophysics, as individual disciplines and applications may be interested selectively in one or more of the static or dynamic aspects, or combinations. Physico-mathematical modelling is often a fundamental tool that helps to discriminate between static and dynamic aspects, extracting the factors of specific interest for the application at hand. A link between measured geophysical quantities and the corresponding quantities of practical interest can only be established in the form of quantitative constitutive relationships. As many applications can benefit from the joint application of multivariate geophysical measurements (e.g. ERT, GPR, SIP etc) it would be highly advantageous to develop constitutive laws that in turn depend on few parameters that can be independently measured and that have a common, albeit different, impact on several geophysical data. In this contribution we illustrate the above general framework with a number of applications including catchment hydrology, digital soil mapping, contaminated site characterization and subsurface hydrology.

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/content/papers/10.3997/2214-4609.20149984
2010-06-13
2024-04-28
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20149984
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