Influence of pore size and geometry on peat unsaturated hydraulic conductivity computed from 3D computed tomography image analysis

In organic soils, hydraulic conductivity is related to the degree of decomposition and soil compression, which reduce the effective pore diameter and consequently restrict water flow. This study investigates how the size distribution and geometry of air‐filled pores control the unsaturated hydraulic conductivity of peat soils using high‐resolution (45 µm) three‐dimensional (3D) X‐ray computed tomography (CT) and digital image processing of four peat sub‐samples from varying depths under a constant soil water pressure head. Pore structure and configuration in peat were found to be irregular, with volume and cross‐sectional area showing fractal behaviour that suggests pores having smaller values of the fractal dimension in deeper, more decomposed peat, have higher tortuosity and lower connectivity, which influences hydraulic conductivity. The image analysis showed that the large reduction of unsaturated hydraulic conductivity with depth is essentially controlled by air‐filled pore hydraulic radius, tortuosity, air‐filled pore density and the fractal dimension due to degree of decomposition and compression of the organic matter. The comparisons between unsaturated hydraulic conductivity computed from the air‐filled pore size and geometric distribution showed satisfactory agreement with direct measurements using the permeameter method. This understanding is important in characterizing peat properties and its heterogeneity for monitoring the progress of complex flow processes at the field scale in peatlands. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of a probabilistic approach to simulation of alkalinity and electrical conductivity at a river bank filtration site

In river bank filtration, impurities present in the river water travel with the bank filtrate towards the pumping well. During this passage, certain types of impurities, such as turbidity, total coliform, and so forth, may get attenuated; however, it is interesting to note that some of the instant raw river water quality parameters, such as alkalinity and electrical conductivity, increase after the passage of water through the porous medium. This occurs because water, when passing through the soil pores, absorbs many of the solutes that cause an increase in alkalinity and electrical conductivity. Measurements at a river bank filtration site for a year showed that alkalinity of 116–32 mg l^?1 in river water increased to 222.4–159.9 mg l^?1 in the river bank filtered water. Likewise, the electrical conductivity increased from 280–131 μS cm^?1 to 462–409.6 μS cm^?1. This study uses a probabilistic approach for investigating the variation of alkalinity and electrical conductivity of source water that varies with the natural logarithm of the concentration of influent water. The probabilistic approach has the potential of being used in simulating the variation of alkalinity and electrical conductivity in river bank filtrate. Copyright © 2011 John Wiley & Sons, Ltd.     

Transport properties of rocks from statistics and percolation

Two simplified microstructural models that account for permeability and conductivity of low-porosity rocks are compared. Both models result from statistics and percolation theory. The first model assumes that transport results from the connection of 1D objects or pipes; the second model assumes that transport results from the connection of 2D objects or cracks. In both cases, statistical methods permit calculation of permeability k and conductivity , which are dependent on three independent microvariables: average pipe (crack) length, average pipe radius (crack aperture), and average pipe (crack) spacing. The degree of connection is one aspect of percolation theory. Results show that use of the mathematical concept of percolation and use of the rock physics concept of tortuosity are equivalent. Percolation is used to discuss k and near the threshold where these parameters vanish. Relations between bulk parameters (permeability, conductivity, porosity) are calculated and discussed in terms of microvariables.