Characterization of European Medieval Silver Bars Using Micro X-ray Fluorescence, Conductivity Meter and Scanning Electron Microscopy

The objective of this paper is to use μ-X-ray fluorescence (XRF) analysis to evaluate the fineness and components of European Medieval Silver Bars samples. Conductivity measurements were used to assess the fineness and localization of the faults found in the samples. Because unevenness causes a change in conductivity, the tests were performed on the flattest areas of the Bars. Some rods, such as B3 and B9, have greater conductivity than others. All bars were subjected to the segregation test. In the instance of certain bars, it was not always practicable to categorically state that segregation had happened. There is no diminishing conductivity curve as one moves away from the zero height, as there is for bars B1, B8, and B9. As a result, there may be no solidification on these bars from Obverse to Reverse. A scanning electron microscope was used to record the following bars at various positions on the bars, and quantitative determinations were achieved using energy-dispersed XRF analysis through intensity measurements of the element-specific wavelength.

A simple model to predict hydraulic conductivity in medium to dry soil from the water retention curve

<p>The mathematical representation of the soil hydraulic properties is of central importance for modeling water, solute and energy transport in the vadose zone. The established models of the soil water retention and hydraulic conductivity curves account for capillary water retention and capillary conductivity, but neglect water adsorption and water flow in films and in pore corners. They are therefore suited for modeling flow and transport processes in the medium to wet moisture range, but are susceptible to failure in dry soil. The model system developed by Peters (2013, 2014) and Iden and Durner (2014) (PDI in the following) is a simple parametric framework that overcomes these structural shortcomings. However, it requires an additional parameter to scale the hydraulic conductivity curve in the medium to dry moisture range where non-capillary flow is dominant. Measured conductivity data are required to estimate this scaling parameter and to compute the hydraulic conductivity over the complete moisture range. In this contribution, we first analyze the original model formulation and show that it is in close agreement with a comprehensive physically-based model for film conductivity in porous media. We then suggest a physically based method to predict the film conductivity from the water retention curve. This reduces the number of free parameters by one and gives a complete prediction of the hydraulic conductivity curve if only water retention data and the saturated conductivity are known. Application to literature data covering a broad range of textures shows a very good agreement between measured data and predictions.</p>

An implicit model for soil thermal conductivity and matric potential

<p>Soil thermal conductivity (λ) is affected by the energy status of water and is closely related to soil matric potential (h). In this study, a soil water retention curve and a soil thermal conductivity curve were linked via the critical point that separated the adsorption water and capillary water regimes. Based on existing water retention curve and a thermal conductivity curve models, we derived a new implicit mathematical formulation of the λ-h relationship. The λ-h relationship was valid for the entire water content range at room temperature. The new model parameter values for adsorption, capillarity and soil thermal conduction were optimized, and a linear relationship between critical water content and maximum adsorption capacity was established by fitting the SWRC and STCC models to measurements from eight soils. Laboratory evaluations using λ and h measurements on a loam soil and a clay loam soil showed that the new model well described observed values with coefficients of determination greater than 0.97. The implicit model can quantify λ-h behaviors for various soil textures over the entire water content range.</p>

Sigmoidal water retention function with improved behaviour in dry and wet soils

A popular parameterized soil water retention curve (SWRC) has a hydraulic conductivity curve associated with it that can have a physically unacceptable infinite slope at saturation. The problem was eliminated before by giving the SWRC a non-zero air entry value. This improved version still has an asymptote at the dry end, which limits its usefulness for dry conditions and causes its integral to diverge for commonly occurring parameter values. We therefore joined the parameterizations' sigmoid midsection to a logarithmic dry section ending at zero water content for a finite matric potential, as was done previously for a power-law-type SWRC. We selected five SWRC parameterizations that had been proven to produce unproblematic near-saturation conductivities and fitted these and our new curve to data from 21 soils. The logarithmic dry branch gave more realistic extrapolations into the dry end of both the retention and the conductivity curves than an asymptotic dry branch. We tested the original curve, its first improvement, and our second improvement by feeding them into a numerical model that calculated evapotranspiration and deep drainage for nine combinations of soils and climates. The new curve was more robust than the other two. The new curve was better able to produce a conductivity curve with a substantial drop during the early stages of drying than the earlier improvement. It therefore generated smaller amounts of more evenly distributed deep drainage compared to the spiked response to rainfall produced by the earlier improvement.

Relating Hydraulic Conductivity Curve to Soil-Water Retention Curve Using a Fractal Model

In the study of water transference in soil according to Darcy law, the knowledge of hydrodynamic characteristics, formed by the water retention curve θ(ψ), and the hydraulic conductivity curve K(ψ) are of great importance. The first one relates the water volumetric content (θ) with the water-soil pressure (ψ); the second one, the hydraulic conductivity (K) with the water-soil pressure. The objective of this work is to establish relationships between both curves using concepts of probability theory and fractal geometry in order to reduce the number of unknown functions. The introduction of four definitions used at the literature of the pore effective radius that is involve in the general model has permitted to establish four new specials models to predict the relative hydraulic conductivity. Some additional considerations related to the definitions of flow effective area and the tortuosity factor have allow us to deduce four classical models that are extensively used in different studies. In particular, we have given some interpretations of its empirical parameters in the fractal geometry context. The resulting functions for hydrodynamic characteristics can be utilized in many studies of water movement in the soil.

Sigmoidal Water Retention Function with Improved Behavior in Dry and Wet Soils

A popular parameterized soil water retention curve (SWRC) has a hydraulic conductivity curve associated with it that can have an infinite slope at saturation. The problem was eliminated before by giving the SWRC a non–zero air–entry value. This improved version still has an asymptote at the dry end, which limits its usefulness for dry conditions and causes its integral to diverge for commonly occurring parameter values. We therefore joined the parameterizations' sigmoid mid–section to a logarithmic dry section ending at zero water content for a finite matric potential, as was done previously for a power–law type SWRC. We selected five SWRC parameterizations that had been proven to produce unproblematic near–saturation conductivities and fitted these and our new curve to data from 21 soils. The logarithmic dry branch gave more realistic extrapolations into the dry end of both the retention and the conductivity curves than an asymptotic dry branch. We tested the original curve, its first improvement, and our second improvement by feeding them into a numerical model that calculated evapotranspiration and deep drainage for nine combinations of soils and climates. The new curve was more robust than the other two. The new curve was better able to produce a conductivity curve with a substantial drop during the early stages of drying than the earlier improvement. It therefore generated smaller amounts of more evenly distributed deep drainage compared to the spiked response to rainfall produced by the earlier improvement.

Estimation of tropical soils’ hydraulic properties with inverse method and tension infiltrometer field data

In the last few years, many studies have been published by authors from several countries offering approximations and use of the inverse method. However, the unique environmental conditions and distinct properties of the tropical soils in Brazil require extra considerations and the need to adjust these methods to tropical soil conditions. Considering the above, this determined the parameters of the van Genuchten (1980) model (θs, θr, α, n) of the water retention curve in the soils. It also determined the parameter (Ks) of the soil’s hydraulic conductivity curve by solving an inverse problem using the HYDRUS-2D model, considering cumulative infiltration data collected in the field by means of an infiltration test using the tension infiltrometer. It then compared the hydraulic properties determined by these methods in relation to the standard laboratory method. The inverse method was able to efficiently determine the water retention curves in the soils here studied; however, it was not possible to reliably determine the unsaturated hydraulic conductivity curve.

Uncertainty of discharge measurement using salt dilution

<p>Discharge measurement using salt dilution is an old method, but it has been recently more and more used thanks to the development of new sensors making it possible to measure conductivity and compute discharge in real-time. Salt dilution is very well suited for turbulent rivers, such as mountain streams. The ISO standard ISO 9555 propose a normative framework to estimate uncertainty, but it was published in 1994 and is now obsolete for new sensors and computational capabilities. In this article, we propose a complete framework to compute the uncertainty of a salt dilution gauging following the GUM (Guide to the expression of uncertainty in measurement) method that take into account the following error sources:  (i) the uncertainty in the mass of salt injected, (ii)  the uncertainty in the measurement of time, (iii) the uncertainty in the Conductivity to Concentration law, (iv) the uncertainty if a measurement conductivity is out of the range of the Conductivity to Concentration law, (v) the uncertainty in the computation of the area under the conductivity curve, (vi) the uncertainty due to a not perfect mixing of the tracer if the mixing length between injection and the probes is not reached (vii) the uncertainty due to a loss or a gain of tracer between the injection and the probes if tracer can be adsorbed for example and (viii) the uncertainty due to unsteadiness of the flow  i.e. variation of discharge during the measurement. The method for computing each uncertainty source is presented and the new framework is applied to a set of real measurements and compared to the expertise of field hydrologists.</p>