Soil Electrical Conductivity Measurements Research Articles

A Combined Sensor for Simultaneous Measurements of Soil Moisture and Electrical Conductivity

A Combined Sensor for Simultaneous Measurements of Soil Moisture and Electrical Conductivity

Spatial Prediction of Soil Salinity Using Kriging with Measurement Errors and Probabilistic Soft Data

In this study it is shown how kriging with measurement errors (KME) is useful as opposed to more conventional kriging methods. The goal of the study was to properly account for field measured soil electrical conductivity (EC) as soft data for the spatial prediction of soil salinity. Samplings were done in autumn 2009 (first dataset), spring and autumn 2010 (second and third datasets) around Uromieh Lake, northwest of Iran. The salinity was measured both in the field and laboratory for the first and second datasets. The first dataset was used for error measurements from which an error variance can be estimated. The measured errors were then used for characterizing probabilistic type soft data using the second dataset. The KME with only soft data (SKME), KME with both soft and hard data (HSKME) and ordinary kriging methods were compared. Validation criteria, mean error (ME) and mean squared error (MSE) were used for comparing the methods. Finally, the SKME method was applied as a way of improving the salinity prediction for the third dataset where only field measured soil salinity data were available. Comparing different kriging methods, Ordinary Kriging (OK) showed the best results among the comparing methods with ME and MSE equal to −0.12 and 0.55 respectively. SKME with ME equal to −0.13 was slightly different from OK and SKME with ME equal to −0.24 resulted in more bias predictions among others. KME method has shown to be useful for soil salinity monitoring and can effectively reduce sampling time.

Embedded Based Soil Electrical Conductivity Measurement System

Electrical Conductivity measurements are often used to measure the amount of soluble salts in the soil. It is most common measure of soil salinity and is indicative of the ability of an aqueous solution to carry an electrical current. By Agricultural standards, soils with an Electrical Conductivity greater than 4 ds/m are considered for saline. In actually salt-sensitive plants may be affected by conductivities less than 4 ds/m and salt tolerant species may be impacted by concentrations of up to twice this maximum agricultural tolerant limit. Hence in the present an attempt is made to implement and embedded based soil conductivity meter.

Spatio-Temporal Changes of Soil Salinity in Arid Areas of South Xinjiang Using Electromagnetic Induction

The aim of this paper was to research the spatio-temporal changes in total soluble salt content (TS) in a typical arid region of South Xinjiang, China, where the climate is arid and soil salinization happens easily. The total soluble salt content was interpreted by measurements made in the horizontal mode with EM38 and EM31. The electromagnetic induction (EM) surveys were made three times with the apparent soil electrical conductivity (ECa) measurements taken at 3 873 locations in Nov. 2008, 4 807 locations in Apr. 2009 and 6 324 locations in Nov. 2009, respectively. For interpreting the ECa measurements into total soluble salt content, calibtion sites were needed for EM survey of each time, e.g., 66 sites were selected in Nov. 2008 to measure ECa, and soils-core samples were taken by different depth layers of 0-10, 10-20 and 20-40 cm at the same time. On every time duplicate samples were taken at five sites to allevaite the local-scale variability, and soil temperatures in different layers through the profiles were also measured. Factors including TS, pH, water content, bulk density were analyzed by lab experiments. ECa calibration equations were obtained by linear regression analysis, which indicated that soil salinity was one primary concern to ECa with a determination coefficient of 0.792 in 0-10 cm layer, 0.711 in 10-20 cm layer and 0.544 in 20-40 cm layer, respectively. The maps of spatial distribution were predicted by Kriging interpolation, which showed that the high soil salinity was located near the drainage canal, which validated the trend effect caused by the irrigation canal and the drainage canal. And by comparing the soil salinity in different layers, the soluble salt accumulated to the top soil surface only in the area where the soil salinization was serious, and in the other areas, the soil salinity trended to increase from the top soil surface to 40 cm depth. Temporal changes showed that the soil salinity in November was higher than that in April, and the soil salinization trended to aggravate, especially in the top soil layer of 0-10 cm.

Comparison of Geonics EM38 and Dualem 1S electromagnetic induction sensors for the measurement of salinity and other soil properties

AbstractThe electromagnetic induction (EMI) Geonics EM38 (G‐EM38) and Dualem 1S (D‐1S) sensors are used frequently for assessment of soil salinity and other soil characteristics in irrigated agriculture. We compared these two sensors to determine whether they could be used interchangeably for the measurement of apparent soil electrical conductivity (ECa) in horizontal (ECa‐h) and vertical (ECa‐v) coil receiver modes. Readings were taken at 201 locations identified in three irrigation districts in both modes, and statistical comparisons were made on the raw data and from maps of a 2‐ha irrigated field made using 1680 horizontal mode readings. Both sensors gave the same ECa‐v readings (mean G‐EM38 and D‐1S difference = 0), whereas the ECa‐h readings were slightly greater with the Geonics EM38 than with the Dualem D‐1S (mean difference = 0.075 and 0.05 dS/m for the 201 and 1680 observations, respectively). The degree of coincidence between both sensors for soil profile ECa classification was acceptable: 82% for normal profiles (i.e. ECa‐h/ECa‐v < 0.9) and 90% for inverted profiles (i.e. ECa‐h/ECa‐v > 1.1). In practical terms, Geonics EM38 and Dualem 1S sensors could be used interchangeably with similar or very close results.

Measurement of soil electrical conductivity with soil electrical conductivity meter in seawater inundated farmland

Measurement of soil electrical conductivity with soil electrical conductivity meter in seawater inundated farmland

Field-scale monitoring of the long-term impact and sustainability of drainage water reuse on the west side of California's San Joaquin Valley

Diminishing freshwater resources have brought attention to the reuse of degraded water as a water resource rather than a disposal problem. Drainage water from tile-drained, irrigated agricultural land is degraded water that is often in large supply, but the long-term impact and sustainability of its reuse on soil is unknown. Similarly, nothing is known of the ramifications of terminating drainage water reuse. The objective of this study is (i) to monitor the long-term impact on soil chemical properties and thereby the sustainability of drainage water reuse on a marginally productive, saline-sodic, 32.4 ha field located on the west side of California's productive San Joaquin Valley and (ii) to assess spatially what happens to soil when drainage water reuse is terminated. The monitoring and assessment were based on spatial chemical data for soil collected during 10 years of irrigation with drainage water followed by 2 years of no applied irrigation water (only rainfall). Geo-referenced measurements of apparent soil electrical conductivity (EC(a)) were used to direct the soil sampling design to characterize spatial variability of impacted soil properties. Chemical analyses of soil samples were used (i) to characterize the spatial variability of salinity, Na, B, and Mo, which were previously identified as critical to the yield and quality of Bermuda grass (Cynodon dactylon (l.) Pers.) grown for livestock consumption and (ii) to monitor their change during the 12 year study. Soil samples were taken at 0.3 m increments to a depth of 1.2 m at each of 40 sample sites on five occasions: August 1999, April 2002, November 2004, August 2009, and May 2011. Drainage water varying in salinity (1.8-16.3 dS m(-1)), SAR (5.2-52.4), Mo (80-400 μg L(-1)), and B (0.4-15.1 mg L(-1)) was applied from July 2000 to June 2009. Results indicate that salts, Na, Mo, and B were leached from the root zone causing a significant improvement in soil quality from 1999 to 2009. Salinity and SAR returned to original levels or higher in less than two years after termination of irrigation. Boron and Mo showed significant increases. Long-term sustainability of drainage water reuse was supported by the results, but once application of irrigation water was terminated, the field quickly returned to its original saline-sodic condition.

Evaluation of soil water content in tilled and cover-cropped olive orchards by the geoelectrical technique

Electrical Resistivity Imaging (ERI) was performed in southern Italy, under semi-arid climate, on a Haplic Calcisol soil of two rainfed olive orchards managed according to different soil management (Tillage – T, and Cover Cropping – CC), applied for 8 years. The main aim was to test the usefulness of such geoelectrical method for the assessment of spatial and temporal variability of soil water content for water balance studies. For that purpose, the quality of univariate relationships between soil electrical resistivity (ρ) and volumetric soil water content (θ v) was tested. Three geoelectrical measurement campaigns were performed in the autumn–spring period of 2006–2007. For each campaign, 3 two-dimensional (2-D) geoelectrical tomographies were carried out in the pole–dipole array using a fixed electrode spacing of 0.25 m. 2-D apparent resistivity pseudosection data sets have been inverted using the software TomoLab®. Each covered soil section was 3 m in depth and 11.5 m long. On 14 November 2006 and 18 April 2007 campaigns the ERI were followed by soil samplings carried out with auger directly below the respective geoelectrical profiles. Direct measurements of soil electrical conductivity and soil water content were conducted on the soil samples in situ and in the laboratory. Volumetric soil water content, θ v (mm mm −1), was significantly related to soil electrical resistivity data, ρ (Ω m), by the exponential model θ v = 1.641 ρ − 0.599 (R = 0.866, n = 84). This relation allowed to assess the change of soil water content in the two orchards during the autumn–spring period and to reveal that the CC plot was more efficient to intercept and store rainwater. ERI technique allowed to highlight differences between the systems in the dynamics of water distribution along the soil profile as an effect of the adopted soil management. In particular, such technique consented to easily evaluate the extent of water content of the deepest soil layers (> 1.0 m) evidencing a significant water reserve in the CC plot, convenient for the root system of rainfed olive trees in the driest months. Finally, the soil water content evaluated by means of the ERI technique was used for the short-term application of soil water balance which showed interesting data on the progress of water consumption during the autumn–spring period, particularly useful as operative indications for cover crops management.

Evaluation of a Geonics EM31-3RT probe to delineate hydrologic regimes in a tile-drained field

A world-wide need to use water resources efficiently necessitates more effective approaches to study water and contaminant transport in soil. This study examined the effectiveness of a multi-receiver electromagnetic induction probe (Geonics EM31-3RT) and modeling software (EMIGMA) to delineate hydrological regimes at field scale. The site consisted of 20 (15 m × 15 m) tile-drained plots in Southern Ontario, Canada. Measurements of apparent soil electrical conductivity (ECa) and magnetic susceptibility were obtained using the EM31-3RT in each plot at four distances (0, 2.25, 4.5 and 7.5 m) from the tile drain, and on three occasions (August 22, 26 and 29) in 2003. The EMIGMA was used to simulate a depth profile of electrical conductivity (ECs) from EM31-3RT readings. The near-surface soil showed significantly (p < 0.01) smaller ECa values than at greater depth. The ECa measurements made directly over the tile drains were smaller than those observed further away due to the presence of the drains. Cluster analysis indicated that the largest ECa values were at the lower elevations of the site related to the redistribution of moisture from higher elevations. The effect of tile drains and rainfall events on ECa was simulated well by EMIGMA, with smaller ECs values above the drains compared to further away, and showing an increase in ECs in the near-surface soil after rain. This study suggests that EM31-3RT measurements combined with EMIGMA simulation of electrical conductivity can provide valuable information on depth profiles of ECa and water dynamics in soil.

Comparison of Sampling Strategies for Characterizing Spatial Variability with Apparent Soil Electrical Conductivity Directed Soil Sampling

Spatial variability has a profound influence on a variety of landscape-scale agricultural issues including solute transport in the vadose zone, soil quality assessment, and site-specific crop management. Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity [Formula: see text] is a potential means of characterizing the spatial variability of any soil property that influences [Formula: see text] including soil salinity, water content, texture, bulk density, organic matter, and cation exchange capacity. Arguably the most significant step in the protocols for characterizing spatial variability with [Formula: see text]-directed soil sampling is the statistical sampling design, which consists of two potential approaches: model- and design-based sampling strategies such as response surface sampling design (RSSD) and stratified random sampling design (SRSD), respectively. The primary objective of this study was to compare model- and design-based sampling strategies to evaluate if one sampling strategy outperformed the other or if both strategies were equal in performance. Using three different model validation tests, the regression equation estimated from the RSSD data produced accurate and unbiased predictions of the natural log salinity levels at the independently chosen SRSD sites. Design optimality scores (i.e., D-, V-, and G-optimality criteria) indicate that the use of the RSSD design should facilitate the estimation of a more accurate regression model, i.e., the RSSD approach should allow for better model discrimination, more precise parameter estimates, and smaller prediction variances. Even though a model-based sampling design, such as RSSD, has been less prevalent in the literature, it is concluded from the comparison that there is no reason to refrain from its use and in fact warrants equal consideration.

Measured and Modeled Dielectric Properties of Soils at 50 Megahertz

Commercial soil water sensors of the capacitance and impedance type generally operate at low (&lt;200 MHz) frequencies where the soil dielectric properties are frequency dependent, especially for soils high in clay. In this work, we examined the dielectric properties of four soil materials (fine sand, sandy loam, loam, and clay) at 50 MHz using Hydra impedance sensor real and imaginary permittivity measurements and time domain reflectometry (TDR) apparent permittivity and bulk soil electrical conductivity (EC) measurements. The results showed that the Hydra sensor real and imaginary permittivity increased with increasing soil clay content and that relaxation loss was a significant part of the total energy loss, except for the fine sand, where the relaxation loss was zero. Model calculations showed that the relative contribution of surface conductivity to bulk soil EC increased over the contribution of pore water conductivity as clay content increased. Application of a soil permittivity model showed that the observed real permittivity ε′ and relaxation loss εrel″ for all soils except the fine sand could not be explained using simple mixing rules. The underestimation of the modeled ε′ and εrel″ for soils with non‐negligible clay content was attributed to interfacial polarizations that were not included in the model. The modeled contribution of bound water to relaxation loss was found to be small.

Comparing temperature correction models for soil electrical conductivity measurement

There are various factors that affect soil electrical conductivity (EC) measurements, including soil texture, soil water content, cation exchange capacity (CEC) and others. Temperature is an important environmental variable, and different models can be used to correct for its effect on EC measurements and standardize the measurements to 25°C. It is relevant to analyze these models and to determine whether they are consistent with each other. Some models were wrongly cited. We found that the exponential model of Sheets and Hendrickx as corrected by Corwin and Lesch in 2005 performs the best. The ratio model also performs well between 3°C and 47°C.

프로브형 가시광-근적외선 센서를 이용한 토양의 탄소량 측정

An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and <TEX>$R^2$</TEX> of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination (<TEX>$R^2$</TEX>) of 0.7 or higher.

Mobile and georeferenced electromagnetic sensors and applications for salinity assessment

Soil salinity is a major threat in irrigated agriculture because of its negative on-site (decreased productivity) and off-site (salinization of irrigation return flows) effects. The delineation of the spatial variability of soil salinity is best suited using non-invasive geophysical measurements of the apparent soil electrical conductivity (ECa) using mobile GPS-based systems. Two simple and cost-effective Mobile Georeferenced Electromagnetic Sensors (MGES) developed in Aragón and Navarra (Spain) are described. These devices involve electromagnetic instruments towed by all terrain vehicles and combined with GPS units and data acquisition systems that collect both ECa readings and GPS coordinates. Two applications of the MGES aimed at delineating ECa maps for (1) selecting the most suitable crops in a 43-ha saline site (Hondo de Espartosa) and (2) correlating ECa with drainage water salinity to ascertain the salinity-source areas in a new 715 ha irrigated basin (Barranco de Lerma) were examined. These examples demonstrate the MGES surveying capacities for management of salt-affected agricultural areas.

Short‐Term Sustainability of Drainage Water Reuse: Spatio‐Temporal Impacts on Soil Chemical Properties

Greater urban demand for finite water resources, increased frequency of drought resulting from erratic weather, and increased pressure to reduce drainage water volumes have intensified the need to reuse drainage water. A study was initiated in 1999 on a 32.4-ha saline-sodic field (Lethent clay loam series; fine, montmorillonitic, thermic, Typic Natrargid) located on the west side of California's San Joaquin Valley (WSJV) with the objective of evaluating the sustainability of drainage water reuse with respect to impact on soil quality. An evaluation after 5 yr of irrigation with drainage water is presented. Geo-referenced measurements of apparent soil electrical conductivity (EC(a)) were used to direct soil sampling at 40 sites to characterize the spatial variability of soil properties (i.e., salinity, Se, Na, B, and Mo) crucial to the soil's intended use of growing Bermuda grass (Cynodon dactylon (l.) Pers.) for livestock consumption. Soil samples were taken at 0.3-m increments to a depth of 1.2 m at each site in August 1999, April 2002, and November 2004. Drainage water varying in salinity (0.8-16.2 dS m(-1)), SAR (5.4-52.4), Mo (80-400 microg L(-1)), and Se (<1-700 microg L(-1)) was applied to the field since July 2000. An analysis of the general temporal trend shows that overall soil quality has improved due to leaching of B from the top 0.6 m of soil; salinity and Na from the top 1.2 m, but primarily from 0 to 0.6 m; and Mo from the top 1.2 m. Short-term sustainability of drainage water reuse is supported by the results.

The use of tritium content as an indicator of the groundwater contamination by sanitary landfills leachates in the region of Belo Horizonte City, Brazil

Tritium content in the leachate of sanitary landfills, in concentrations well above those observed in global precipitation, can be used as a tracer for the evaluation of the contamination of groundwater in piezometers of the landfills and in neighbouring tubular wells. This possibility was first investigated in Brazil for sanitary landfills in the region of Belo Horizonte City. Tritium levels together with the content of metals present in water and the measurement of soil electrical conductivity, proved to be valuable for these studies and also as a tracer for hydrodynamic studies of the surface water in the Ressaca creek.

Delineating site-specific management zones for pH-induced iron chlorosis

Iron chlorosis can limit crop yield, especially on calcareous soil. Typical management for iron chlorosis includes the use of iron fertilizers or chlorosis tolerant cultivars. Calcareous and non-calcareous soil can be interspersed within fields. If chlorosis-prone areas within fields can be predicted accurately, site-specific use of iron fertilizers and chlorosis-tolerant cultivars might be more profitable than uniform management. In this study, the use of vegetation indices (VI) derived from aerial imagery, on-the-go measurement of soil pH and apparent soil electrical conductivity (ECa) were evaluated for their potential to delineate chlorosis management zones. The study was conducted at six sites in 2004 and 2005. There was a significant statistical relationship between grain yield and selected properties at two sites (sites 1 (2005) and 3), moderate relationships at sites 2 and 4, and weak relationships at site 5. For sites 1 (2005) and 3, and generally across all sites, yield was predicted best with the combination of NDVI and deep ECa. These two properties were used to delineate chlorosis management zones for all sites. Sites 1 and 3 showed a good relationship between delineated zones and the selected properties, and would be good candidates for site-specific chlorosis management. For site 5, differences in the properties between mapped zones were small, and the zones had weak relationships to yield. This site would be a poor candidate for site-specific chlorosis management. Based on this study, the delineation of chlorosis management zones from aerial imagery combined with soil ECa appears to be a useful tool for the site-specific management of iron chlorosis.

Feasibility study of monitoring the total available water content using non‐invasive electromagnetic induction‐based and electrode‐based soil electrical conductivity measurements

AbstractIrrigation is by far the largest consumer of water in the world. At the same time the need for irrigation may differ between different zones of a particular field due to spatial soil variability. In particular total available water content (TAWC) has effects on irrigation frequency and depth. The objective of our study was to compare the ability of two fast, non‐destructive and sensor‐based apparent soil electrical conductivity (ECa) measurement methods: A contact and electrode‐based sensor (VERIS 3100, both shallow and deep modes); A non‐contact, electromagnetic induction (EMI)‐based sensor (Geonics EM38, both horizontal and vertical orientations) to monitor the within‐field variation of the TAWC. The ECa data, standardized to 25°C (EC25), were collected on a 1 s interval corresponding to 2–3 m data spacing on transects spaced approximately 4–6 m apart. Based on the ECa spatial variability pattern, and to cover the range of ECa values present, 29 calibration points were located using a differential Global Positioning System (DGPS) to develop field‐specific relationships between ECa data and TAWC in the upper 60 cm of soil. However, we found better correlations between TAWC and the VERIS 3100 readings. Calibration equations to estimate TAWC from the shallow mode of VERIS 3100 data exhibited a good fit to the data and had the highest correlation (R2 = 0.77), whereas calibrations to EM38 data (both vertical and horizontal orientation) were low and apparently could not adequately reflect the spatial variability of the TAWC due to the influence of the more highly variable topsoil. We identified six TAWC zones based on fuzzy k‐means unsupervised classification as an optimum number of irrigation management zones within our field (Zone 1: 99–105, Zone 2: 105–116, Zone 3: 116–127, Zone 4: 127–138, Zone 5: 138–149, Zone 6: 149–161 mm per 60 cm). We concluded that under traditional irrigation conditions, Zones 1 and 2 were over‐irrigated whereas Zones 4, 5 and 6 were deficit irrigated. Copyright © 2007 John Wiley &amp; Sons, Ltd.

Development of TDR Penetrometer through Theoretical and Laboratory Investigations: 2. Measurement of Soil Electrical Conductivity

Abstract A TDR penetrometer was introduced to allow simultaneous measurements of dielectric permittivity and electrical conductivity during cone penetration. This study focused on the theoretical development and experimental evaluation of electrical conductivity measurement using the TDR penetrometer. Theoretical development takes into account the cable resistance and nonconducting cone shaft, leading to a new data reduction equation and calibration procedure. Measurement sensitivity and spatial sampling bias were experimentally evaluated for various probe configurations. The results show that the measurement sensitivity of interest may be controlled by the geometric factor of the probe. The complication and implications of the spatial weighting bias are discussed. A prototype TDR penetrometer was calibrated and used to perform simulated penetration tests in a soil. Experimental results do not show significant errors in electrical conductivity due to the penetration disturbance, verifying the effectiveness of the TDR penetrometer for electrical conductivity measurement.

COMPARISON OF ELECTROMAGNETIC INDUCTION, CAPACITIVELY-COUPLED RESISTIVITY, AND GALVANIC CONTACT RESISTIVITY METHODS FOR SOIL ELECTRICAL CONDUCTIVITY MEASUREMENT

In situ measurement of apparent soil electrical conductivity (ECa) is an important precision agriculture tool usefulfor determining spatial changes in soil properties. Three near-surface geophysical methods are available for rapid,continuous measurement of ECa in agricultural fields. These methods are electromagnetic induction (EMI), capacitivelycoupled resistivity (CCR), and galvanic contact resistivity (GCR). Acceptance for using geophysical methods to gauge spatialchanges in soil properties hinges to a significant degree on there being consistency of the measured ECa spatial patternbetween geophysical methods. Testing of all three methods was conducted on two adjacent test plots having fine-grained soilsand during two time periods with dissimilar shallow hydrologic conditions. Different operational modes for each of the threegeophysical methods were evaluated, including three primary electromagnetic field frequencies (8190, 14610, and 20010 Hz)used for the EMI method, four spacing distances (0.625, 1.25, 2.5, and 5.0 m) between the two dipoles employed with the CCRmethod, and two different Schlumberger electrode array lengths (0.7 and 2.1 m) utilized for the GCR method. Therefore, atotal of nine geophysical method - operational mode combinations were tested.<br><br>Based on spatial correlation analysis, the areal ECa patterns measured by the nine method - operational modecombinations showed substantial similarity to each other, with one exception. The exception was the short electrode arraymode of the GCR method that when paired with the various modes of the other two geophysical methods, exhibited an averagecorrelation coefficient, r, that ranged between only 0.30 and 0.45. All other average r values for pairs of different geophysicalmethod - operational mode combinations ranged between 0.62 and 0.97. Spatial correlation coefficients, for both test plots,between the same method - operational mode combination, but at two different times in which hydrologic conditions varied,ranged from 0.55 to 0.95 for eight of the nine method - operational mode combinations, with the GCR short electrode arrayhaving values of 0.32 and 0.58. Regarding the test plot EC average or median, there were substantial differences in valuesobtained by the three geophysical methods. Electromagnetic vertical sounding measurements along with results obtained byCCR, and GCR surveying, when combined, indicate that for both test plots, from the surface to a depth of a little over 2 m,soil electrical conductivity generally increased first and then decreased. Most importantly, although the measured ECamagnitudes vary between the three geophysical methods, results show that EMI, CCR, and GCR all provide useful andconsistent information on soil electrical conductivity spatial patterns.