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SOIL & WATER MANAGEMENT & CONSERVATION

Comparing Bulk Soil Electrical Conductivity Determination Using the DUALEM-1S and EM38-DD Electromagnetic Induction Instruments

Dep. of Biological and Irrigation Engineering Utah State Univ. Logan, UT 84322

D.A. Robinson

Dep. of Plants, Soils and Biometeorology Utah State Univ. Logan, UT 84322-4820
Currently at: Dep. of Geophysics, Stanford Univ. 397 Panama Mall Stanford, CA 94305

S.B. Jones

Dep. of Plants, Soils and Biometeorology Utah State Univ. Logan, UT 84322-4820

^* Corresponding author (hiruyabdu{at}cc.usu.edu).

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Earth conductivity instruments based on the principle of electromagnetic induction (EMI) are extensively used for mapping soil salinity and, increasingly, for mapping soil texture. Environmental variables such as temperature can impact sensor response beyond the effect of soil solution electrical conductivity. This study was conducted to compare the bulk soil electrical conductivity (EC_a)–depth relationship between the DUALEM-1S and Geonics EM38-DD devices and to determine the effect of variable temperature environments on instrument response. The relationship of EC_a to the depth below ground was investigated by raising each instrument in increments of 0.15 m up to 1.8 m above ground level. The effect of temperature on both instruments was investigated under two soil salinity levels at two sites. The instruments corresponded reasonably with theoretical models describing the EC_a–depth relationships, which are primarily coil-orientation dependent. Under the effect of variable-temperature test conditions, both instruments were prone to a higher margin of error (10–40%) at lower EC_a readings while the error became less significant (5%) at higher EC_a (>100 mS m^–1). The difference in response of the instruments can be ascribed to the temperature-dependent change in soil EC_a due to a 20°C diurnal temperature variation in addition to instrumental drift caused by temperature effects on the processing circuitry. The EM38-DD's real-time display and internal powering are its advantages while the lower priced DUALEM-1S does not need instrument calibration and can store data internally

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Electromagnetic induction instruments have been used extensively to make noninvasive apparent electrical conductivity (EC_a) measurements, which can be used to characterize soil salinity spatial variability across large areas (Corwin, 2005). These EMI instruments are cost effective and are gaining wider use due to their nondestructive nature, rapid response, and ease of integration into a mobile platform, from which real-time measurements can be made. The EMI-based EC_a measurements can be used in conjunction with soil sampling, directed from the EC_a surface response (Lesch et al., 1995a, 1995b). In field-scale studies, these measurements are used to infer soil spatial variability and to identify field-scale heterogeneities (Corwin and Lesch, 2003). Several factors influence EC_a measurements, including soil salinity, water content, porosity, structure, temperature, clay content, mineralogy, cation exchange capacity, and bulk density (Rhoades et al., 1999; Friedman, 2005). The EMI-based EC_a measurements can be used as proxy for inferring these soil properties by assuming relative homogeneity in all but the property of interest.

The EMI-based EC_a measurements with the Geonics EM38 (Geonics Inc., Mississauga, ON) have been used by researchers attempting to infer different properties and characterize a wide range of processes at the field scale for a host of different applications (Hendrickx and Kachanoski, 2002). Doolittle et al. (1994) estimated claypan depth via EC_a measurements in central Missouri soils via direct calibration between EC_a and topsoil depth above the claypan. Jaynes et al. (1995) correlated EMI-derived EC_a measurements to herbicide partition coefficients to predict herbicide application leaching potentials in specific areas of an EMI-surveyed field. Anderson-Cook et al. (2002) exploited the positive correlation between EC_a and previous year crop yields to statistically classify four different soils. Sudduth et al. (2001) developed a procedure using EC_a measurements to infer topsoil depth in claypan soils. Corwin and Lesch (2003, 2005) outlined standard operating procedures for EC_a surveys applied to precision agriculture, specifically surveys that calibrate EC_a to the electrical conductivity of saturation extract samples (EC_e) for use in salinity studies, and discussed several different applications of field-scale EC_a maps. Corwin and Lesch (2003) used EC_a measurements to infer EC_e to assess salinity effects by comparing EC_e measurements within fields to crop yields and chemical analyses. Taylor et al. (2003) used the recently developed DUALEM-2 (DUALEM Inc., Milton, ON) to identify the locations and depths of septic system failure.

The reliability of data collected using EMI instruments depends on the thermal stability of the instrument, while the EC_a measurement averaging down the soil profile depends on the configuration of the instrument coils (Wait 1951; 1955). Researchers using the EM38 for field mapping have observed progressive instrument drift affecting the EC_a measurements during mapping days (Sudduth et al., 2001; Robinson et al., 2004). Sudduth et al. (2001) investigated accuracy issues in the collection of soil EC_a data and recommended a calibration to document and adjust for instrument drift. The EM38 data were collected at four 50-m calibration transects during the day, whereby a maximum of >10% EC_a deviation was observed. Robinson et al. (2004), on the other hand, were able to register a drift of 20% in the hot southwest USA, where the EM38 instrument panel temperature reached 60°C.

The depth-weighted response of an EMI instrument depends on coil orientation with respect to the half space and spacing of the coils (Wait, 1955, 1951). Rhoades et al. (1999) conducted several studies to determine the EC_a–depth distributions for the measurement of salinity profiles and for analyzing saline seeps. The EC_a–depth relation is calculated by successively raising the EMI instrument and measuring the respective contribution of each soil interval to EC_a (Corwin and Rhoades, 1982). Corwin and Rhoades (1990) produced empirical calibration and statistical analysis equations to calculate the EC_a–depth relationships for different soil types using the EM-38.

The purpose of this study was to characterize the DUALEM-1S instrument and compare it with the Geonics EM38-DD. Characterization of the EC_a averaging with depth was conducted on low- and high-EC_a soils, and compared with theoretical models. Side-by-side experiments were conducted to compare instrument thermal stability on low- and high-EC_a soils.

	THEORETICAL CONSIDERATIONS

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Ground conductivity meters pass an alternating current through a transmitter coil, which produces a primary magnetic field (H_p). The primary magnetic field induces small alternating currents in the soil. The induced current loops produce an induced magnetic field (H_i) proportional to the current within the loops. The secondary magnetic field, a combination of the primary and the induced magnetic fields (H_s = H_p + H_i), induces a small alternating current in a receiver coil. The receiver coil measures the amplitude and phase of the secondary magnetic field, which consists partly of signals from soil layers at different depths corresponding to the different loops. All of the measured signals are amplified and summed into an output voltage, which is directly related to a depth-weighted average EC_a calculated from (McNeill, 1980)

[1]

where f is frequency (Hz), µ_o is the permeability of free space (4 x 10^–7 H m^–1), s is the interdipole spacing (m), H_s is the secondary magnetic field at the receiver coil (H m^–1), and H_p is the primary magnetic field at the transmitter coil (H m^–1).

The amplitude and phase of the secondary magnetic field measured by the receiver coil differ from the primary field owing to soil properties and transmitter–receiver spacing and orientation (i.e., horizontally or vertically oriented) with respect to the soil surface (Hendrickx and Kachanoski, 2002).

The transmitters and receivers of EMI devices consist of wound coils that can be treated as magnetic dipoles since the separation between transmitters and receivers is more than several coil diameters. The magnetic field from each dipole penetrates the earth and the vertical dipole has a greater depth of penetration than the horizontal dipole because the vertical field couples more effectively with material down in the earth than does the horizontal field. Figure 1 shows that the magnetic fields of the vertical dipoles entering the soil surface are more dense than the horizontal dipoles.

View larger version (55K): [in this window] [in a new window]   Fig. 1. Transmitter and receiver dipole orientations of the EM38-DD and DUALEM-1S (instruments are oriented parallel to the surface). The loops of wire form a solenoid and a dipole is created when current passes through the wire. The EM38-DD (top) has its transmitter and receiver dipoles oriented in horizontal–horizontal (H–H) and vertical–vertical (V–V) modes. The DUALEM-1S (bottom) also uses a V–V and a vertical–horizontal (V–H) mode for the dipoles in its transmitter and receiver.

In Fig. 1, the three combinations are illustrated. Horizontal–horizontal (H–H): in this combination, both the transmitter and receiver dipoles are oriented parallel to the earth's surface. The bottom unit (horizontal dipole mode) in the EM38-DD uses this combination. Vertical– vertical (V–V): in this combination the dipoles are oriented perpendicular to the earth's surface. The top unit (vertical dipole mode) in the EM38-DD and the horizontal co-planar mode in the DUALEM-1S use this combination. Vertical–horizontal (V–H): the transmitter dipole is vertical, while the receiver dipole is horizontal and its axis intersects the transmitter. The perpendicular mode in the DUALEM-1S uses this combination.

Relative Response
The governing equations for the EMI relative response, , of the three different orientations are (McNeill, 1980; Wait, 1962)

[2]

[3]

[4]

where z is the depth divided by the transmitter–receiver spacing.

Figure 2A shows the relative sensitivity of the three coil orientations relative to an increase in depth. Both the H–H and V–H orientations are sensitive at the surface, and rapidly lose their sensitivity with an increase in depth. The V–V orientation is insensitive at the ground surface but the sensitivity rapidly increases with depth, peaking at 0.4 m.

View larger version (22K): [in this window] [in a new window]   Fig. 2. (A) Relative sensitivity and (B) cumulative response with respect to depth of the three coil orientations (horizontal–horizontal [H–H], vertical–vertical [V–V], and vertical–horizontal [V–H]) of the DUALEM-1S and EM38-DD instruments.

[5]

Equations for the cumulative response of different orientations from a depth (z) to infinity have been given by McNeill (1980) and Wait (1962). We have adapted the equations so that they give cumulative responses from the surface to a given depth (z) of each orientation (Fig. 2B):

[6]

[7]

[8]

Since the cumulative response is exponential, we need to define a depth beyond which the orientation response is relatively insensitive—the depth of exploration (DOE). For our study, we have defined the DOE to be the depth from which 70% of the cumulative response comes. The DOE for the V–V orientation is 1.5 m, while the H–H and V–H orientations achieve the same response at a DOE of 0.75 and 0.5 m, respectively (Fig. 2B).

In a layered earth, EC_a is calculated by summing the conductivity and depth-weighted contribution of each layer. In a system with three distinct layers overlying uniform earth, the bulk electrical conductivity is given by (McNeill and Bosnar, 1999)

[9]

where _1,2,3 are the conductivities of each corresponding layer, ₄ is the conductivity of the uniform earth underlying the three layers, and R(Z_1,2,3) are the cumulative responses at the bottom of each respective layer.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Instrument Description
The DUALEM-1S (DUAL-geometry Electro-Magnetic; Table 1) is a geoconductivity sensor with a transmitter operating at the frequency of 9 kHz and two receivers with different orientations. In the horizontal coplanar geometry, hereafter referred to as V–V_DLM, both the transmitter and the receiver—with a 1-m separation—use vertical dipoles. The other setup, perpendicular geometry, referred to as V–H_DLM hereafter, still uses a vertical dipole transmitter while the receiver located 1.1 m away uses a horizontal dipole. The DOE for the V–V_DLM setup is about 1.5 m while for the V–H_DLM it is about 0.5 m. The transmitter and the receiver, as well as the processing circuitry, are housed in a fiber resin composite casing. The instrument does not come with a display unit and data is transmitted serially through a nine-socket DB-9 connector. The instrument outputs the apparent conductivity and in-phase readings of both orientations; the roll and pitch of the instrument; as well as the time of the data recording, the applied voltage, and the internal temperature of the sensor. The instrument is capable of storing 50000 records in its internal memory for further access.

Study Sites
Greenville Farm (Millville Series)
The Millville series located at the Utah Agricultural Experiment Station's Greenville Farm receives a mean annual precipitation of 422 mm and the mean annual temperature is 8.6°C. The site has a xeric soil moisture regime and a mesic soil temperature regime. The area surrounding the Millville soil pedon is used for irrigated crops and a distinguishable plow layer can be observed in the A horizon. The pedon contains <1% rock fragments and the texture (silt loam) is uniform with depth. The pH of 8.2 is due to the highly disseminated CaCO₃. The parent material of the Millville soil is a fine-textured alluvium (silts and very fine sand) due to lower energy distal fan and overbank flood deposits. The soil is classified as a coarse-silty, carbonatic, mesic Typic Haploxeroll. Soil samples were taken every 0.3 m down to a depth of 1.5 m and were analyzed for water content using oven drying; EC_e was measured using the saturation paste extraction method (Soil Survey Staff, 2004; Fig. 3A ).

View larger version (35K): [in this window] [in a new window]   Fig. 3. (A and D) Profile saturation extract electrical conductivity (ECe), volumetric soil water content (v), and apparent electrical conductivity [ECa(inversion)] data; and ECa–height above ground relationships as modeled using uniform earth and three-layer models for the (B and E) DUALEM-1S and (C and F) EM38-DD at Greenville Farm and Cache Junction sites at various coil orientations (horizontal–horizontal [H–H], vertical–vertical [V–V], and vertical–horizontal [V–H]).

Measurement Response vs. Depth
To study the effect of depth on measurement response, the instruments were lifted from the ground surface to conduct depth sounding. The instruments were raised using a polyvinyl chloride pipe as a guiding support, keeping the instrument parallel to the ground. Five sets of measurements for each instrument were taken at the two study sites by lifting the instruments in increments of 0.15 m up to 1.8 m above the ground. The measurements were obtained directly from the EM38-DD display, while an Allegro CX with HGIS software was used to collect the measurements from the DUALEM-1S.

Measurement Response vs. Temperature
To study the effects of temperature, EM readings from the two instruments were recorded throughout the day at two locations with high and low EC_a values. On 1 July 2005, the instruments were placed at the Greenville Farm and on 8 July the instruments were positioned at the Cache Junction Farm. At both locations, the instruments were separated by a distance of 4 m and the measuring instruments were placed midway between them. A CR10 datalogger (Campbell Scientific, Logan, UT) was used to record the readings from the six thermocouples placed on the instruments (a thermocouple each by the receiver dipoles and panel of the EMI instruments) and the surrounding environment (one 0.15 m belowground and another 0.3 m aboveground in the air). The EM38-DD data was acquired using a handheld geographic information system (HGIS, StarPal Inc., Fort Collins, CO) program inside an Allegro CX handheld field computer (Juniper Systems, Logan, UT). The DUALEM-1S data was recorded internally and later downloaded to a computer.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Measurement Response vs. Depth
Data from Cache Junction and Greenville Farm was used to determine the EC_a–depth relationship of the different orientations of the two instruments. This data can be used in conjunction with EC_a layer models, such as Eq. [9], to invert the data to determine the approximate bulk conductivity of the soil layers. Performing the inversion is a way of comparing the data collected with the two instruments. When the instruments are raised above the earth's surface, the cumulative response for each step is reduced correspondingly by the effect of the height above the ground. The EC_e and water content measurements with 0.3-m depth increments are presented in Fig. 3A and 3D for the two soils. These data show that the Greenville Farm data had a higher EC_e layer over two lower EC_e layers (Fig. 3A) and that the Cache Junction site had a higher conductivity layer between two lower conductivity layers (Fig. 3D). We tried two inversion approaches, the first assuming a uniform earth using Eq. [6] to [8] and the second assuming three layers over a uniform earth (Eq. [9]) based on the observed changes in EC_e as a function of depth (Fig. 3A and 3D). We chose layer depths for the Greenville Farm and Cache Junction sites of 0 to 0.6, 0.6 to 1.2, and 1.2 to 1.5 m, corresponding approximately with the observed changes in EC_e with depth. The predicted EC_a response was then fitted to the measured EC_a response by minimizing the error between the two and by allowing the bulk conductivity of the three layers and the uniform earth to vary.

The results for the Greenville Farm are presented in Fig. 3B and 3C. The broken lines show the fit for the uniform earth and demonstrate a poor fit with the data for both instruments. The application of the three-layer inversion improves the fit for the DUALEM-1S data but is still poor for the EM38 data. The RMSE for the DUALEM-1S over a uniform earth was 0.30 for the V–V_DLM and 0.27 for the V–H_DLM orientations, respectively. This improved to a RMSE of 0.09 and 0.05 for V–V_DLM and V–H_DLM for the three-layer model. The result of the inversion is presented as the dotted line in Fig. 3A, and, although providing a good fit, it fails to capture the dominant higher conductivity layer over the two lower conductivity layers.

The EM38-DD showed the largest divergence from the models, V–V_EM38 having a RMSE of 0.79 and H–H_EM38 having a RMSE of 1.2 for the uniform earth model. Interestingly, the use of the three-layer model didn't lead to a major improvement, with RMSEs of 0.54 and 1.00 for V–V_EM38 and H–H_EM38, respectively. The difference between the measured and modeled data for the EM38-DD is due to the difficulty calibrating the EM38-DD at low conductivity values, resulting in poor quality measurements. To achieve a calibration with V–V_EM38 reading twice H–H_EM38, the EC of the horizontal had to be raised; this sets a threshold below which EC cannot be measured, resulting in poor data at low conductivities for this soil.

The measurements made in the Cache Junction soil are presented in Fig. 3E and 3F. In this higher conductivity soil, the uniform earth model correlated well with the data from both instruments. The fitting to the DUALEM-1S data gave a RMSE of 1.7 for V–V_DLM and 2.2 for V–H_DLM (Fig. 3E). The EM38-DD was better, giving a RMSE of 0.88 for the V–V_EM38 orientation and 1.4 for the H–H_EM38 orientation (Fig. 3F). The use of the three-layer model improved the RMSE for the DUALEM-1S to 0.19 for V–V_DLM and 0.16 for V–H_DLM and marginally for the EM38-DD to 0.80 for V–V_EM38 and 1.4 for H–H_EM38. The results of the inversion at Cache Junction for the DUALEM-1S are presented in Fig. 3D. This time the inversion did a better job of picking out the high and low conductivity layers. The use of these models demonstrates the different abilities of the instruments to measure under different conditions, bringing out the important point that with a small range of EC_a response (0–20 mS m^–1), the DUALEM-1S does much better than the EM38-DD due to its internal, automatic calibration. The application of these simple inversion models shows that the results leave much to be desired. Inversion of these data could be very useful in vadose zone research for determining depth to conductive layers (salts, water tables, or clay layers), and should form the basis of future research with these instruments.

Measurement Response vs. Temperature
Both instruments were placed on bare soil while EC_a and temperature data were collected from 10:30 to 18:30 h. At the low conductivity site (Greenville Farm), the air temperature ranged from 24 to 40°C, while the soil temperature climbed from 18 to 32°C at 0.15 m below the soil surface. The instrumental temperature variations of the DUALEM-1S and the EM38-DD are presented in Fig. 4A and 4B, respectively. The DUALEM-1S casing reached a maximum temperature of around 40°C while the maximum temperature for V–V_EM38 panel was >50°C. Figures 4C and 4D show the EMI responses of the coil orientations of the DUALEM-1S and EM38-DD, respectively. The mean response of the V–V_DLM was 8.05 mS m^–1 with a SD of 0.87 and the V–H_DLM had a mean response of 10.4 mS m^–1 with a SD of 0.35, whereas the mean response of the V–V_EM38 was 19.9 mS m^–1 with a SD of 1.7 and the H–H_EM38 had a mean response of 19.6 mS m^–1 with a SD of 1.4.

View larger version (36K): [in this window] [in a new window]   Fig. 4. The electromagnetic induction (EMI) response of the EM38-DD and DUALEM-1S instruments at various coil orientations (horizontal–horizontal [H–H], vertical–vertical [V–V], and vertical–horizontal [V–H]) at Greenville Farm and Cache Junction throughout the day: variation of the temperature for both instruments as well as air and soil temperature at (A and B) Greenville Farm and (E and F) Cache Junction; and the EMI response of both instruments as well as the predicted EMI response using Archie's extended model (Eq. [10]) for (C and D) Greenville Farm and (G and H) Cache Junction.

It is evident from the statistics that a larger EMI response deviation from the initial reading is observed when the instruments are measuring low EC_a values. At the low conductivity site, the EM38-DD had a maximum difference of 23% (6.3 mS m^–1) for the V–V_EM38 and 22% (8.3 mS m^–1) for H–H_EM38. The maximum difference for the DUALEM was 13% (1.8 mS m^–1) for V–H_DLM and a high 42% (4.8 mS m^–1) for V–V_DLM. The percentage difference in the EMI readings during the day at the high conductivity site was much smaller than at the low conductivity site. Maximum differences of 5.2% (6.4 mS m^–1) and 6.6% (8.0 mS m^–1) were observed for V–V_EM38 and H–H_EM38, respectively, while maximum differences of 5.0% (5.7 mS m^–1) and a low 1.2% (1.1 mS m^–1) were recorded for V–V_DLM and V–H_DLM, respectively.

The difference in response can be ascribed to two things: (i) the change in temperature of the soil during the day, which would tend to increase the ground conductivity, and (ii) instrument drift caused by the inability of the processing circuitry to fully compensate for instrument heating. To differentiate between these two competing factors, we modeled EC_a to determine what the response of the instruments should be in the soil. As inputs for the model, we used water content measured from soil samples, porosity, and soil temperature measured at 0.15-m depth. We recognize that by using the temperature measured at 0.15 m, the values would be an upper bound to the actual EC_a sensed by the instruments; however, we would expect both instruments to show a trend similar to the modeled EC_a.

An extended version of Archie's Law (Friedman, 2005), accounting for unsaturated conditions, was used to model the expected ground conductivity response that the EMI instruments would measure. We adopted Friedman's (2005) simplification, which uses a unit value as the exponent of porosity (n), thus obtaining an equation with only one empirical fitting parameter (d):

[10]

where _v is volumetric water content, and according to Corwin and Lesch (2005):

[11]

The modeling was conducted such that each orientation would measure 70% of the cumulative response. The V–V_EM38 and V–V_DLM achieved this by measuring down to a depth of 1.5 m while the V–H_DLM and H–H_EM38 attained such a response by measuring down to 0.5 and 0.75 m, respectively. The parameter d was chosen to fit the first point of the model to the first data point at the beginning of the experiment. The model, derived experimentally using coarse-textured soils, has limitations in clay soils but demonstrates the expected upward trend in EC_a as temperature increases. Table 2 lists the parameters used for modeling the responses of the different coil orientations at the two sites.

View this table: [in this window] [in a new window]   Table 2. Soil parameters of volumetric soil water content (v), saturation extract electrical conductivity (ECe), porosity (n), and the empirical fitting parameter d for modeling the effect of soil temperature on apparent electrical conductivity using Eq. [10].

General Observations
Some of the strong features of the EM38-DD are: a real-time LCD display, a built-in handle, portable internal powering, and years of applied research experience; while a complicated instrumental calibration procedure, exposed control knobs, and a commonly overheating black panel are drawbacks. The DUALEM-1S has avoided some of the problems associated with the EM38-DD by not having any control knobs, having a yellow casing to minimize radiation absorption, and by incorporating an automatic instrument calibration. This automated instrument calibration is a distinct advantage for users working with low conductivity soils, for instance, when used for texture mapping.

Even though the DUALEM-1S can store 50000 records in its internal memory, it lacks a built-in display unit, making an external logging or display unit necessary. The DUALEM-1S also requires an external power source and does not come with a handle for manual measurements. This means the instrument is less suited to single measurements and more suited to applications such as mobile mapping where continuous measurements are made. At the time of testing, the price of the DUALEM-1S was approximately two-thirds the cost of the EM38-DD. Both instruments can be connected to various logging programs running on handheld field computers or laptops for recording georeferenced EMI response while field mapping.

	CONCLUSIONS

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
The EC_a response measurement down a profile can be useful in determining depth to conductive layers (salts, water tables, or clay layers), aiding researchers involved in agriculture and hydrology; but one needs to be aware of the limitations of the EMI instrument used. The measured response of the instruments with depth could be better fitted to inverse models using the DUALEM-1S data compared with the EM38-DD output. This was much more apparent for measurements in the low conductivity soil where instrument calibration difficulty made data inversion unfeasible using the EM38-DD. Results from the simple three-layer model over a conductive earth indicate that advanced optimization techniques or inversion models are required to obtain improved predictions of conducting layer structure. Our measurements across a range of temperatures indicate that, at low EC_a, both the EM38-DD and DUALEM-1S are more susceptible to instrument drift; this reduces considerably at higher values of EC_a. The V–H_DLM configuration of the DUALEM-1S appears to correspond well with predicted values of EC_a at low bulk soil EC values. The EM38-DD readings appeared to be more temperature sensitive at lower EC_a, exhibiting the opposite trend to the expected increase in EC_a as temperature increased. An improved method of temperature correcting for the instruments is required and should improve the accuracy of the instruments. For those using these instruments for an extended period to map soil properties (e.g., soil texture) where EC_a values tend to be low, we recommend that the mapping is performed on a cooler day or that the instruments are protected from direct sunlight. In this instrument comparison, the EM38-DD's real-time display and internal powering proved to be its advantages while the lower priced DUALEM-1S is less temperature sensitive, does not require manual instrument calibration, and can store data internally.

	ACKNOWLEDGMENTS

 
We would like to acknowledge funding provided by Inland Northwest Research Alliance and the National Research Initiative Competitive Grant no. 2002-35107-12507 from the USDA Cooperative State Research, Education, and Extension Service. We would also like to thank Dr. Grant E. Cardon of Utah State University Extension for the use of the EM38-DD. David Robinson's time was funded in part by Grant 04-47287 from the National Science Foundation for the development of the CUAHSI Hydrologic Measurement Facility. This research was supported by the Utah Agricultural Experiment Station, Utah State Univ., Logan, and approved as Journal Paper no. 7816.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Abbreviations: DOE, depth of exploration; EC, electrical conductivity; EMI, electromagnetic induction.

Received for publication December 6, 2005.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION THEORETICAL CONSIDERATIONS MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 

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