Search

Solute diffusion controls important processes in soils: plant uptake of nutrients, sorption-desorption processes, degradation of organic matter, and leaching of radionuclides through clay barriers. We developed a new method for measuring the solute diffusivity (solute diffusion coefficient in the soil relative to water) in intact soil samples (the Multiple Tracer, Filter Separated half-cell method using a Dynamic Model for parameter estimation [MT-FS- DM1). The MT-FS-DM method consists of half-cell diffusion of two pairs of counterdiffusing anionic tracers and a parameter estimation scheme that allows diffusion coefficients for tracers in the two half-cells to be estimated on the basis of two concentration profiles in each sample. The parameter estimation scheme uses a fully dynamic (time-resolved) simulation model. From sensitivity and uncertainty analyses of the dynamic model, we found that the MT-FS-DM method provided reliable results. We compared diffusivities measured on a sandy loam soil using the MT-FS-DM method with diffusivities from six sandy loam test soils from the literature. The new method can be used to estimate solute diffusivity in intact structured soil and provides a more confident estimate for solute diffusion due to the use of two tracer profiles in the same soil sample. Especially when we are interested in determining the diffusivity of a single intact soil sample, such as when relating solute diffusivity to other properties of the soil (e.g., microbial activity), this method will be an improvement over existing methods. [ABSTRACT FROM AUTHOR]

The time required at a field site to obtain a few measurements of saturated hydraulic conductivity (Ks) will allow for many measurements of soil air permeability (ka). This study investigates if ka measured in situ (ka, in situ) can be a substitute for measurement of Ks in relation to infiltration and surface runoff modelling. Measurements of ka, in situ were carried out in two small agricultural catchments. A spatial correlation of the log-transformed values existed having a range of approximately 100 m. A predictive relationship between Ks and ka measured on 100-cm3 soil samples in the laboratory was derived for one of the field slopes and showed good agreement with an earlier suggested predictive Ks–ka relationship. In situ measurements of Ks and ka suggested that the predictive relationships also could be used at larger scale. The Ks–ka relationships together with the ka, in situ data were applied in a distributed surface runoff (DSR) model, simulating a high-intensity rainfall event. The DSR simulation results were highly dependent on whether the geometric average of ka, in situ or kriged values of ka, in situ was used as model input. When increasing the resolution of Ks in the DSR model, a limit of 30–40 m was found for both field slopes. Below this limit, the simulated runoff and hydrograph peaks were independent of resolution scale. If only a few randomly chosen values of Ks were used to represent the spatial variation within the field slope, very large deviations in repeated DSR simulation results were obtained, both with respect to peak height and hydrograph shape. In contrast, when using many predicted Ks values based on a Ks–ka relationship and measured ka, in situ data, the DSR model generally captured the correct hydrograph shape although simulations were sensitive to the chosen Ks–ka relationship. As massive measurement efforts normally will be required to obtain a satisfactory representation of the spatial variability in Ks, the use of ka, in situ to assess spatial variability in Ks appears a promising alternative. Copyright © 2004 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Soil thermal conductivity (λ) and heat capacity (C) control heat transport and the thermal environment for biogeophysical processes in the vadose zone. Accurate λ and C predictions for peaty soils with high organic contents are particularly important for assessing emissions of greenhouse gases formed during microbial activity in wetlands. In this study, we measured the λ and C at different soil-water matric potentials on undisturbed samples for three peaty soil profiles at the Hokkaido Bibai marsh in Japan, representing a total of 10 different soil horizons. The thermal properties under air-dried conditions, λdry and Cdry, were measured separately at changing volumetric solids contents (σ). For each sample, volume shrinkage was observed to varying degrees during the drying process. Measured λ and C increased linearly with increasing volumetric water content (ϑ). Applying the concept of a three-phase mixing model and incorporating the λ-ϑ or C-ϑ and the λdry-σ or Cdry-σ relations, predictive λ and C models were developed as functions of σ and ϑ . The new mixing model is represented by λ = λdry + fλϑλw and C = Cdry + fCϑCw, where λw and Cw are the thermal conductivity and heat capacity of water, respectively, and f is an impedance factor that takes into account the liquid-phase tortuosity. The new mixing model predicted literature λ-ϑ data on peaty and highly organic soils under variable saturation well. The probable ranges of λ and C under variable saturation were proposed based on the sensitivity analysis. [ABSTRACT FROM AUTHOR]