Topp Equation Research Articles

Continuous Automatic Estimation of Volumetric Water Content Profile During Infiltration Using Sparse Multi-Offset GPR Data

Ground-penetrating radar (GPR) is a non-destructive and non-invasive geophysical survey method that has been used to characterize soil volumetric water content (VWC) dynamics. An array antenna GPR system was used to collect nearly seamless, time-lapse multi-offset GPR data during an in-situ infiltration test on sand dunes with limited traces. Because the data volume was significant, an approach was utilized to automatically determine electromagnetic wave velocities from sparse common midpoint (CMP) data using standard velocity analysis, such as semblance analysis. The objective of this study was to develop a methodology that allows one to automatically perform velocity analysis by interpolating sparse CMP data obtained with the array GPR system. The proposed method determined the optimal normal moveout velocity values and the removal range of the F-K zone pass filter that minimized errors between the original and interpolated CMP data using leave-one-out cross-validation (LOOCV). After interpolating the sparse CMP data with the F-K zone pass filter, semblance analysis was used to determine the time-lapse velocity structure of the soil profile during water infiltration. The velocity data were converted to VWC data based on the Topp equation, which relates the soil VWC to the soil dielectric constant. The proposed method was tested using CMP data obtained via numerical simulation and experiments. The VWC profile from the proposed approach matched well with the independently observed VWC profiles obtained from an invasive probe-type soil moisture sensor.

Evaluation of a multi‐sensor for measuring solution electrical conductivity in coir

AbstractThe simultaneous measurements of both volumetric water content (θ) and electrical conductivity of pore solutions (ECw) are essential for nutrient solution management within soilless culture systems. The present study was carried out in order to evaluate a capacitance sensor (METER 5TE) for the measurement θ and ECw within coir. Following the evaluation of the spatial sensitivity of the 5TE sensor, a calibration experiment was executed with six levels of θ (0.30, 0.35, 0.40, 0.45, 0.50, and 0.55 m3 m−3) and four levels of KCl solutions (1.0, 3.0, 5.0, and 7.0 dS m−1). The measured relationship between θ and dielectric permittivity (εa) for coir significantly deviated from Topp's equation for organic soil, but was similar to the calibration equation for growing media from the sensor manufacturer and for peat soils. The Hilhorst (2000) model recommended by the manufacturer overestimated ECw within coir. On the other hand, accounting for EC dependency on the real part of the complex dielectric permittivity of the solution within the Hilhorst model will greatly improve ECw prediction. In contrast, the Rhoades (1976) model was more capable of describing the dependence of the apparent soil electrical conductivity (ECa) on θ and ECw for the coir samples for ECa < 2.9 dS m−1. Hence, when ECw−ECa−θ relations are known, the capacitance sensor is a powerful tool for horticultural practices because a single measurement can yield both θ and ECw.

Estimating water content of unsaturated sandy soils by GPR during a drainage experiment

This study shows how to estimate water content of unsaturated sandy soils from ground-penetrating radar (GPR) data acquired during water drainage experiment. Using the Topp equation, water content can be converted to dielectric permittivity. Afterwards, based on 1D forward modeling method a GPR synthetic trace is generated. Finally, a trial-and-error match of modeled and observed GPR traces was performed to estimate the optimum set of parameters characterizing the materials composing the soil. According to the comparison of the modeling signal and the real signal, we go back to update the water content. Repeating the procedure until the modeling signal fits the real signal very well. We used this procedure to obtain the evolution of water content of unsaturated sandy soils. The method is presented on drainage experiment carried out on unsaturated sandy soil of a large-controlled experimental site. In order to follow the change of the water level, we measured GPR profiles at different times and picked up four GPR profiles, then the same trace (No. 700) were picked up on each GPR profile and estimated the water content from each signal.

Enhanced GPR data interpretation to estimate in situ water saturation in a landfill

Research was completed to show that using the complex refractive index model (CRIM) to interpret GPR data can improve the estimation of in situ water content of the waste in the landfill. Literature shows that the Topp equation is normally used to analyse GPR data, despite the fact it fails to consider porosity and other properties of the landfill material or soil that can affect the electromagnetic properties of the material. The application of (CRIM) overcomes these limitations and more. Previously measured field GPR data were reanalyzed with CRIM and supported by synthetic GPR data to show that CRIM provides a better prediction of the water content of the landfill material.Further enhancement of GPR data interpretation was implemented by optimizing the frequency of the GPR scan and determining the ideal offset separation distance between the transmitter and the receiver using sensitivity tests. The sensitivity tests were based on synthetic 2D surface based-reflection GPR data sets generated by MATLAB®. The sensitivity results showed that the optimum frequency was 1 GHz, with an ideal offset distance of 0.75 m. After using the optimized values, it was possible to obtain a percentage of error of 1% between modelled water saturation and GPR measured water saturation.

The Effect of Soil Iron on the Estimation of Soil Water Content Using Dielectric Sensors

Nowadays, the estimation of volumetric soil water content (θ) through apparent dielectric permittivity (εa) is the most widely used method. The purpose of this study is to investigate the effect of the high iron content of two sandy loam soils on estimating their water content using two dielectric sensors. These sensors are the WET sensor operating at 20 MHz and the ML2 sensor operating at 100 MHz. Experiments on specific soil columns, in the laboratory, by mixing different amounts of water in the soils to obtain a range of θ values under constant temperature conditions were conducted. Analysis of the results showed that both sensors, based on manufacturer calibration, led to overestimation of θ. This overestimation is due to the high measured values of εa by both sensors used. The WET sensor, operating at a lower frequency and being strongly affected by soil characteristics, showed the greatest overestimation. The difference of εa values between the two sensors ranged from 14 to 19 units at the maximum actual soil water content (θm). Compared to the Topp equation, the WET sensor measures 2.3 to 2.8 fold higher value of εa. From the results, it was shown that the relationship θm-εa0.5 remained linear even in the case of these soils with high iron content and the multi-point calibration (CALALL) is a good option where individual calibration is needed.

Substrate‐sensitive relationships of dielectric permittivity and water content: implications for moisture sounding

ABSTRACTDielectric permittivity is a fundamental parameter for all investigations based on electromagnetic waves, particularly for moisture sounding. However, the physical principles of dielectric permittivity in natural materials and its influence on propagation velocity, the reflection coefficient, and the decay of the electromagnetic waves have been rarely addressed for variable substrate compositions or frequencies. Hence, this paper aims to fill this gap by systematically investigating quantitative relationships between dielectric permittivity and soil water content for a continuum of the three most common soil components in moderately temperate humid latitudes (i.e., illite, carbonate, and quartz‐rich sand). We carried out frequency‐dependent permittivity measurements for a large variety of artificial and natural substrates with an impedance analyser at frequencies ranging from 10 MHz to 1 GHz. Based on these measurements, we selected 200 MHz as the most commonly used frequency value for geological, ground‐penetrating radar applications and developed a set of empirical equations from third‐degree and ternary factorial diagrams to quantify the relationship between dielectric permittivity and volumetric moisture content of pure sand, clay, carbonate, and mixtures. The results show systematic trends, which can be explained by competing electrophysical properties of minerals and their wetting behaviour. This investigation shows that different wetting affinities of 1:1 and 2:1 clay minerals strongly control permittivity. Thresholds and non‐linearity effects were identified, where specific mineral properties and/or wetting processes became dominant in complex mixtures of soil materials. Bulk densities and porosities, respectively, were shown to have only minor influence compared with the impact of water. Consequently, the presented method is applicable to both undisturbed and disordered samples and, hence, to mobile devices or permanent installations in the field after compositional laboratory or onsite analyses. The permittivity of natural soils was measured in two field studies. The results show a good correlation between calculated and measured moisture contents. Our study confirms that the widely used Topp equation is only valid for sandy soil materials, i.e., the soil types it was originally designed for. For soils with a clay content >30% and/or a moisture level >20%, the new equations reduce the error in the level of permittivity measurements from up to 20% (using the Topp equation) to 5%.

A pragmatic, automated approach for retroactive calibration of soil moisture sensors using a two-step, soil-specific correction

Soil moisture sensors are increasingly deployed in sensor networks for both agronomic research and precision agriculture. Soil-specific calibration improves the accuracy of soil water content sensors, but laboratory calibration of individual sensors is not practical for networks installed across heterogeneous settings. Using daily water content readings collected from a sensor network (42 locations×5 depths=210 sensors) installed at the Cook Agronomy Farm (CAF) near Pullman, Washington, we developed an automated calibration approach that can be applied to individual sensors after installation. As a first step, we converted sensor-based estimates of apparent dielectric permittivity to volumetric water content using three different calibration equations (Topp equation, CAF laboratory calibration, and the complex refractive index model, or CRIM). In a second, “re-calibration” step, we used two pedotransfer functions based upon particle size fractions and/or bulk density to estimate water content at wilting point, field capacity, and saturation at each sensor insertion point. Using an automated routine, we extracted the same three reference points, when present, from each sensor’s record, and then bias-corrected and re-scaled the sensor data to match the estimated reference points. Based on validation with field-collected cores, the Topp equation provided the most accurate calibration with an RMSE of 0.074m3m−3, but automated re-calibration with a local pedotransfer function outperformed any of the calibrations alone, yielding a network-wide RMSE of 0.055m3m−3. The initial calibration equation used in the first step was irrelevant when the re-calibration was applied. After correcting for the reference core measurement error of 0.026m3m−3 used for calibration and validation, the error of the sensors alone (RMSEadj) was computed as 0.049m3m−3. Sixty-five percent of individual sensors exhibited re-calibration errors less than or equal to the network RMSEadj. The incorporation of soil physical information at sensor installation sites, applied retroactively via an automated routine to in situ soil water content sensors, substantially improved network sensor accuracy.

Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA.

The quantity of liquid water in the snowpack defines its wetness. The temporal evolution of snow wetness’s plays a significant role in wet-snow avalanche prediction, meltwater release, and water availability estimations and assessments within a river basin. However, it remains a difficult task and a demanding issue to measure the snowpack’s liquid water content (LWC) and its temporal evolution with conventional in situ techniques. We propose an approach based on the use of time-domain reflectometry (TDR) and CS650 soil water content reflectometers to measure the snowpack’s LWC and temperature profiles. For this purpose, we created an easily-applicable, low-cost, automated, and continuous LWC profiling instrument using reflectometers at the Cooperative Remote Sensing Science and Technology Center-Snow Analysis and Field Experiment (CREST-SAFE) in Caribou, ME, USA, and tested it during the snow melt period (February–April) immediately after installation in 2014. Snow Thermal Model (SNTHERM) LWC simulations forced with CREST-SAFE meteorological data were used to evaluate the accuracy of the instrument. Results showed overall good agreement, but clearly indicated inaccuracy under wet snow conditions. For this reason, we present two (for dry and wet snow) statistical relationships between snow LWC and dielectric permittivity similar to Topp’s equation for the LWC of mineral soils. These equations were validated using CREST-SAFE in situ data from winter 2015. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Additionally, the equations seemed to be able to capture the snowpack state (i.e., onset of melt, medium, and maximum saturation). Lastly, field test results show advantages, such as: automated, continuous measurements, the temperature profiling of the snowpack, and the possible categorization of its state. However, future work should focus on improving the instrument’s capability to measure the snowpack’s LWC profile by properly calibrating it with in situ LWC measurements. Acceptable validation agreement indicates that the developed snow LWC, temperature, and wetness profiler offers a promising new tool for snow hydrology research.

Application of a thermo-time domain reflectometry probe in sand-kaolin clay mixtures

Simultaneous measurements of soil thermal properties, moisture content and dry density are quite challenging, but very significant to geothermal related engineering applications. Thermo-time domain reflectometry (TDR) probe is able to measure soil thermal properties by the thermos probe, and predict soil moisture content and dry density by the TDR technique. This research studies the application of a new thermo-TDR probe in measuring thermal property, moisture content and dry density of sand-kaolin clay mixtures. Laboratory experiments were performed on five sand-kaolin clay mixtures with clay content ranging from 0% to 30% by dry weight. Measured thermal properties by the thermo-TDR probe were compared with a KD2 Pro. The moisture content and dry density were predicted by four alternative methods: Topp's equation, heat capacity method, one-step TDR method and Jung's method. The results revealed that Jung's method exhibited the highest prediction accuracy among the four methods, being the relative deviations between the predicted and measured values within 1% and 5% for gravimetric moisture content and dry density, respectively. It is concluded that the thermo-TDR probe can be applied in sand-kaolin clay mixtures successfully to accurately measure their thermal and geotechnical properties.

Error Analysis of Clay-Rock Water Content Estimation with Broadband High-Frequency Electromagnetic Sensors--Air Gap Effect.

Broadband electromagnetic frequency or time domain sensor techniques present high potential for quantitative water content monitoring in porous media. Prior to in situ application, the impact of the relationship between the broadband electromagnetic properties of the porous material (clay-rock) and the water content on the frequency or time domain sensor response is required. For this purpose, dielectric properties of intact clay rock samples experimental determined in the frequency range from 1 MHz to 10 GHz were used as input data in 3-D numerical frequency domain finite element field calculations to model the one port broadband frequency or time domain transfer function for a three rods based sensor embedded in the clay-rock. The sensor response in terms of the reflection factor was analyzed in time domain with classical travel time analysis in combination with an empirical model according to Topp equation, as well as the theoretical Lichtenecker and Rother model (LRM) to estimate the volumetric water content. The mixture equation considering the appropriate porosity of the investigated material provide a practical and efficient approach for water content estimation based on classical travel time analysis with the onset-method. The inflection method is not recommended for water content estimation in electrical dispersive and absorptive material. Moreover, the results clearly indicate that effects due to coupling of the sensor to the material cannot be neglected. Coupling problems caused by an air gap lead to dramatic effects on water content estimation, even for submillimeter gaps. Thus, the quantitative determination of the in situ water content requires careful sensor installation in order to reach a perfect probe clay rock coupling.

Enhancing modelled water content by dielectric permittivity in stony soils

Applicability of time domain reflectometry (TDR) under naturally distributed stone fragments in soils has seldom been investigated. A multilayer profile of a 30-m-deep well was sampled and the natural distribution of stone fragments in the soils was replicated in the laboratory. Gravimetric soil water content (SWC) was measured simultaneously with TDR dielectric permittivity (Ka) readings and bulk densities in three subsamples as replications. Two connector and buriable probes and three reflection-time capture windows (10, 20 and 40 ns) were used for the measurements. These were repeated for sieved soil samples <2 mm with fixed, pre-measured bulk densities. Measurements of Ka and observed SWC were repeated for extension-cable lengths of 3–30 m. All measurements were taken in samples saturated from the bottom. A semi-empirical mixture model was applied for different fractions of stony samples in order to convert bulk Ka to bulk volumetric SWC (θv) by the mixture model (θvmx), to be compared with θv by the conventional Topp equation (θvTp). An improvement in model performance was observed with lower root-mean-square error (RMSE, 0.02–0.04 v. 0.07–0.1) and ratio of RMSE to observation standard deviation (0.32–0.87 v. 1.07–3.05) for θvmx compared with θvTp. This approach for converting the in-situ measured dielectric permittivity to the θv of the bulk soil can be applied based on the determined stoniness. The 15-cm, 2-rod (connector) probe type with capture windows 20 ns resulted in a better performance than the 20-cm, 3-rod (buriable) probe type with capture windows 10 and 40 ns. Development of regression equations for the stone-free samples resulted in calibrated equations for converting the measured Ka to θv with better results (RMSE ~0.002 m3 m–3) than those obtained using the Topp equation. In contrast to the traditional equation, new sets of coefficients for the Topp equation were also capable of estimating extremely low θv values of ≤0.02 m3 m–3 where the minimum calculated θv values were adequately similar to the observed ones. Noticeable effects of cable length on measured Ka were found for lengths exceeding 10 m. Accurate Ka values might be obtained in similar soil conditions if the suggested regression equations are employed, provided a correction is made for the extension cables.

Wide-band composite electromagnetic scattering from the earth soil surface and multiple targets shallowly buried

Wide-band electromagnetic scattering from multiple objects shallowly buried beneath rough earth soil surfaces has been an important research topic in recent years because of its extensive applications in detecting the buried objects such as mines, pipes, and tunnels. Due to the advantages of finite-difference time-domain (FDTD) method in simulating wide-band electromagnetic scattering from rough surface in the presence of multiple objects, the FDTD method under Gaussian differential pulse wave incidence is utilized in the present study to analyze the frequency response of rough soil surfaces with shallowly buried objects, which serves as a basis for the detection and discrimination of objects buried below rough soil surfaces. The Topp equation model that can predict the dielectric constant of soil-water mixture is adopted in the present study to properly describe the dielectric property of earth soil with water. The actual rough land surface is modeled as the realization of a Gaussian random process with exponential spectrum by using Monte Carlo method. Simulation results show that the variation of composite scattering coefficient with frequency is oscillatory. It is also shown that the composite scattering coefficient versus frequency increases with the increase of root-mean-square of soil surface, water ratio of soil, the target section height, and the separation distance of target. However, simulation results indicate that the composite scattering coefficient versus frequency decreases with the increase of target section width. In summary, the variation of wide-band scattering coefficient is very complicated and is very sensitive to the incidence angle of electromagnetic wave. However, the wide-band scattering coefficient under Gaussian differential pulse wave incidence is less sensitive to the correlation length of rough soil surface, the depth of buried objects, and the dielectric constant of target. These qualitative results relating to the frequency response of rough soil surfaces in the presence of multiple objects are potentially valuable for detecting and discriminating the objects buried below rough soil surfaces by utilizing a wide-band ground penetrating radar system, although the present study is limited to one-dimensional rough soil surface due to the severe computational burden encountered in the large-scale Monte Carlo simulations. In addition, compared with frequency-domain numerical methods, the FDTD method has significant advantages in calculating wide-band composite scattering from rough surfaces in the presence of multiple objects, and thus has extensive applications in radar imaging simulation of multiple objects below or above rough surfaces, which goes beyond the scope of this paper.

Measurement of Soil Moisture Content at Microwave Frequencies

This paper discusses the measurement of moisture content present in soil by computing the dielectric constant of soil samples at three frequencies, using microwave free-space transmission technique. This leads to the determination of inherent moisture content in the samples by applying Topp's Equation. The change in the value of dielectric constant and the subsequent increase in the moisture content for each of the soil samples with added moisture levels at 20%, 23.1% and 28.6% are noted. Dielectric constant of some common materials such as free-space, FR4, acrylic and water are measured to check the efficacy of the proposed method.

Identifying dispersive GPR signals and inverting for surface wave-guide properties

The vadose zone is a dynamic environment in which water is retained or transferred into the saturated zone or atmosphere. Knowledge of water content in the near-surface soil layers is important for improving our understanding of groundwater recharge, evaporation, and uptake by crops or natural vegetation (Vereecken et al., 2008). Ground-penetrating radar (GPR) measurements are capable of estimating the subsurface radar velocity, which can be converted to water content using Topp's equation. The direct ground wave is often used to provide radar velocities for the very shallow part of the vadose zone (Huisman 2003). However, this method can only be applied when the subsurface can be approximated by a homogeneous half-space (e.g., a subsurface with a uniform water content profile). Due to the large permittivity of water (∊r = 80), the permittivity of soils can change dramatically when precipitation or irrigation is occurring at a site.

Effective medium theories for modelling the relationships between electromagnetic properties and hydrological variables in geomaterials: a review

ABSTRACTThe paper reviews the effective medium theories used for modelling the relationships between electromagnetic properties (low‐frequency conductivity and high‐frequency permittivity) and hydrological variables (water content, salinity, suction, permeability) in soils and rocks. It aims a) to provide a simple presentation of these theoretical approaches, b) to present their theoretical and practical limitations and c) to establish some connections with empirical equations usually used in hydrogeophysics (i.e., Archie relationships, Topp equation and complex refractive index model). This review demonstrates that two groups of effective medium theories can be clearly identified. The first group constituted by the Maxwell‐Wagner and Symmetric‐Bruggeman rules is characterized by easy‐to‐use models. When the volumetric water content and the texture are known, they allow to obtain fast estimates of effective electromagnetic properties. In the second group, the differential effective medium schemes that are more complex from a mathematical point of view are preferred when frequency‐dependent properties are studied. In particular, differential effective medium schemes are used for providing some insights into the physical basis of spectral induced polarization measurements in hydrogeophysical applications.

Multi‐offset GPR methods for hyporheic zone investigations

ABSTRACTPorosity of stream sediments has a direct effect on hyporheic exchange patterns and rates. Improved estimates of porosity heterogeneity will yield enhanced simulation of hyporheic exchange processes. Ground‐penetrating radar (GPR) velocity measurements are strongly controlled by water content thus accurate measures of GPR velocity in saturated sediments provides estimates of porosity beneath stream channels using petrophysical relationships. Imaging the substream system using surface based reflection measurements is particularly challenging due to large velocity gradients that occur at the transition from open water to saturated sediments. The continuous multi‐offset method improves the quality of subsurface images through stacking and provides measurements of vertical and lateral velocity distributions. We applied the continuous multi‐offset method to stream sites on the North Slope, Alaska and the Sawtooth Mountains near Boise, Idaho, USA. From the continuous multi‐offset data, we measure velocity using reflection tomography then estimate water content and porosity using the Topp equation. These values provide detailed measurements for improved stream channel hydraulic and thermal modelling.

Time‐Lapse GPR Tomography of Unsaturated Water Flow in an Ice‐Contact Delta

Cross‐well ground penetrating radar (GPR) data sets were collected in the vadose zone of an ice‐contact delta near Oslo's Gardermoen Airport (Norway) before, during, and after snowmelt in 2005. The observed travel times were inverted using curved‐ray travel time tomography. The tomograms are in good agreement with the local geologic structure of the delta. The tomographic results were confirmed independently by surface GPR reflection data and x‐ray images of core samples. In addition to structure, the GPR tomograms also show a strong time dependency due to the snowmelt. The time‐lapse tomograms were used to estimate volumetric soil water content using Topp's equation. The volumetric soil water content was also observed independently by using a neutron meter. Comparison of these two methods revealed a strong irregular wetting process during the snowmelt. This was interpreted to be due to soil heterogeneity as well as a heterogeneous infiltration rate. The geologic structure and water content estimates obtained from the GPR tomography can be used in forward and inverse flow modeling. Finally, the water balance in the vadose zone was calculated using snow accumulation data, precipitation data, porosity estimates, and observed changes in the groundwater table. The amount of water stored in the vadose zone obtained from the water balance is consistent with the amount estimated using GPR tomography. Alternatively, the change in water storage in the vadose zone can be estimated using GPR tomography. This may then permit estimates of evapotranspiration to be made, provided other components of the water balance are known.

Measuring Water Content Heterogeneity Using Multifold GPR with Reflection Tomography

Continuous multioffset acquisition of ground penetrating radar (GPR) data provides the capability to measure the lateral and vertical distribution of soil moisture. Multioffset data enable measurement of radar velocity, which in turn allows the estimation of soil moisture through an appropriate petrophysical relationship. Although rarely used in GPR investigations, reflection tomography coupled with prestack depth migration has the ability to measure lateral velocity variations with much greater resolution and accuracy than conventional methods of velocity analysis. I used reflection tomography in the post‐migration domain to estimate radar velocity and the Topp equation to estimate subsurface moisture distribution in two and three dimensions. At a contaminated site near a former refinery I identified a near‐vertical boundary separating coarse‐grained sands and gravels from a unit containing a high fraction of silts and clays. At a chlorinated solvent waste site, I found significant heterogeneity in the moisture content distribution despite apparent homogeneity indicated by direct push methods.

Simplified Permittivity Calibration of Custom-Designed TDR Probes for Measuring Soil Water Content

Time domain reflectometry (TDR), measuring the travel time of a microwave signal, has been recognized as a superior method of monitoring volumetric water content (θ) in soil. Although various custom-designed TDR probes having different advantages have been designed, the calibration requirement for any specific probe has been a major problem for their users. To propose a simpler calibration approach for custom-designed probes, we first examined their sensitivity to the change in permittivity for several fluid media (air, water, and ethanol-water mixtures), and then calibrated them for sand with a different θ. The custom-designed probes were less sensitive to the change in permittivity than a conventional probe because the detection part is surrounded by low-permittivity materials, and thus we could not adequately determine θ of sand from measured permittivity by applying widely used Topp equation. However, we confirmed that the equation is valid for estimating θ if the effect of the surrounding materials on the measured permittivity was excluded, which effect can be evaluated based on the data sets of permittivity measured for the fluid media. From this result, we concluded that the calibration of the custom-designed probes can be easily conducted by the testing for the fluid media.

Relationship between dielectric permittivity and water content for vadose zone materials of volcanic origin

Seven materials, encompassing a young volcanic soil, its parent material, two older buried soils (Palaeosols), and an underlying older volcanic deposit were investigated in a laboratory study to determine the relationship between dielectric permittivity (ϵc) and water content (θ). Empirical 3rd-order polynomial models generally fitted the data better than semi-physical 3-phase mixing models and normalised conversion functions. Based on their different dielectric response, which presumably is mainly due to their different bulk density (and thus porosity), the materials could be grouped into Ignimbrite materials and Palaeosol materials. Relative to the Ignimbrites, Palaeosols showed a particularly muted response at the low end of dielectric permittivity measurements, which could be due to a particularly high amount of bound water in these allophane-rich materials and/or to greater microstructural and phase configuration effects. Applying the Topp equation resulted in substantial underestimations of the water contents of both groups. A relationship previously developed on New Zealand sandy volcanic soils fitted our Ignimbrite materials well, but still underestimated the water contents of the Palaeosols substantially. Normalised conversion functions described both material groupings reasonably well, demonstrating that bulk density differences can explain a substantial part of the variation of ϵc–θ relationships between different materials.