Computed tomography has become a routine method for probing processes in porous media, and the use of neutron imaging is especially suited to the study of the dynamics of hydrogenous fluids, and of fluids in a high-density matrix. In this paper we give an overview of recent developments in both instrumentation and methodology at the neutron imaging facilities NEUTRA and ICON at the Paul Scherrer Institut. Increased acquisition rates coupled to new reconstruction techniques improve the information output for fewer projection data, which leads to higher volume acquisition rates. Together, these developments yield significantly higher spatial and temporal resolutions, making it possible to capture finer details in the spatial distribution of the fluid, and to increase the acquisition rate of 3-D CT volumes. The ability to add a second imaging modality, e.g., X-ray tomography, further enhances the feature and process information that can be collected, and these features are ideal for dynamic experiments of fluid distribution in porous media. We demonstrate the performance for a selection of experiments carried out at our neutron imaging instruments.

Saturated flow in soil with the occurrence of preferential flow often exhibits temporal changes of saturated hydraulic conductivity even during the time scale of a single infiltration event. These effects, observed in a number of experiments done mainly on heterogeneous soils, are often attributed to the changing distribution of water and air in the sample. We have measured the variation of the flow rates during the steady state stage of the constant head ponded infiltration experiment conducted on a packed sample composed of three different grades of sand. The experiment was monitored by quantitative neutron imaging, which provided information about the spatial distribution of water in the sample. Measurements were taken during (i) the initial stages of infiltration by neutron radiography and (ii) during the steady state flow by neutron tomography. A gradual decrease of the hydraulic conductivity has been observed during the first 4 h of the infiltration event. A series of neutron tomography images taken during the quasi‐steady state stage showed the trapping of air bubbles in coarser sand. Furthermore, the water content in the coarse sand decreased even more while the water content in the embedded fine sand blocks gradually increased. The experimental results support the hypothesis that the effect of the gradual hydraulic conductivity decrease is caused by entrapped air redistribution and the build up of bubbles in preferential pathways. The trapped air thus restricts the preferential flow pathways and causes lower hydraulic conductivity.

In arable land, topsoil is exposed to structural changes during each growing season due to agricultural management, climate, the kinetic energy of rainfall, crop and root growth. The shape, size, and spatial distributions of soil aggregates are considerably altered during the season and thus affect water infiltration and the soil moisture regime. Agricultural topsoils are prone to soil compaction and surface sealing which result in soil structure degradation and disconnection of preferential pathways. To study topsoil infiltration properties over time, near-saturated hydraulic conductivity of topsoil was repeatedly assessed in a catchment in central Bohemia (Czech Republic) during three consecutive growing seasons, using a recently developed automated tension minidisk infiltrometer (MultiDisk). Seasonal variability of soil bulk density and saturated water content was observed as topsoil consolidated between seedbed preparations. Topsoil unsaturated hydraulic conductivity was lower in spring and increased in the summer months during two seasons, and the opposite trend was observed during one season. Temporal unsaturated hydraulic conductivity variability was higher than spatial variability. Cumulative kinetic energy of rainfall, causing a seasonal decrease in soil macroporosity and unsaturated hydraulic conductivity, was not a statistically significant predictor.