Electrical resistivity of the soil can be considered as a proxy for the spatial and temporal variability of many other soil physical properties (i.e. structure, water content, or fluid composition). Because the method is non-destructive and very sensitive, it offers a very attractive tool for describing the subsurface properties without digging. It has been already applied in various contexts like : groundwater exploration, landfill and solute transfer delineation, agronomical management by identifying areas of excessive compaction or soil horizon thickness and bedrock depth, and at least assessing the soil hydrological properties. The surveys, depending on the areas heterogeneities can be performed in one-, two-or three-dimensions and also at different scales resolution from the centimetric scale to the regional scale. In this review, based on many electrical resistivity surveys, we expose the theory and the basic principles of the method, we overview the variation of electrical resistivity as a function of soil properties, we listed the main electrical device to performed one-, two-or three-dimensional surveys, and explain the basic principles of the data interpretation. At least, we discuss the main advantages and limits of the method.

Summary Tillage and traffic modify soil porosity and pore size distribution, leading to changes in the unsaturated hydraulic properties of the tilled layer. These changes are still difficult to characterize. We have investigated the effect of compaction on the change in the soil porosity and its consequences for water retention and hydraulic conductivity. A freshly tilled layer and a soil layer compacted by wheel tracks were created in a silty soil to obtain contrasting bulk densities (1.17 and 1.63 g cm−3, respectively). Soil porosity was analysed by mercury porosimetry, and scanning electron microscopy was used to distinguish between the textural pore space and the structural pore space. The laboratory method of Wind (direct evaporation) was used to measure the hydraulic properties in the tensiometric range. For water potentials < −20 kPa, the compacted layer retained more water than did the uncompacted layer, but the relation between the hydraulic conductivity and the water ratio (the volume of water per unit volume of solid phase) was not affected by the change in bulk density. Compaction did not affect the textural porosity (i.e. matrix porosity), but it created relict structural pores accessible only through the micropores of the matrix. These relict structural pores could be the reason for the change in the hydraulic properties due to compaction. They can be used as an indicator of the consequences of compaction on unsaturated hydraulic properties. The modification of the pore geometry during compaction results not only from a decrease in the volume of structural pores but also from a change in the relation between the textural pores and the remaining structural pores.

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Ary Bruand : Present Address : Institut des Sciences de la Terre d'OrléansInternational audienceThin sections of soil surrounding maize roots were studied in scanning electron microscopy using the backscattered electron mode. The soil is a fine-loamy, mixed, mesic, Typic Eutrochrept. Backscattered electron scanning images (BESI) of the porosity surrounding a selected maize (Zea mays L.) root were studied by image analysis at the scale of micro- and mesopores. Image analysis of BESI revealed that the porosity was 22 to 24% less within the soil surrounding the root than in the bulk soil. The bulk density increased up to 1.80 Mg m−3 close by the root-soil interface, although it was 1.54 Mg m−3 in the bulk soil. The porosity reduction consisted of a removal of the mesopores and a decrease in micropores, which resulted from the packing of skeleton grains with the porous clayey phase. The micropores were affected, although they are usually thought to be altered only with difficulty under natural conditions. A model which was developed earlier for soil compression around roots of plants growing on remolded soils was fitted to the experimental data by nonlinear regression analysis