Using Soil Sensors to Assess Soil Salinity

An Introduction to Electromagnetic Sensors

Electrical conductivity (EC) is an intrinsic property of soil and is affected by many soil properties (Clay et al., 2001; Heilig et al., 2011; Logsdon, 2008; McNeill, 1992; Sudduth et al., 2005). One of the properties that affects soil electrical conductivity is the concentration of the cations and anions in the soil solution. Some of these ions are Cl−, SO42−, HCO3−, CO32−, Na+, K+, Mg2+, and Ca2+. As discussed in Chapter 4 [of the new Salinity and Sodicity book], laboratory measurement of the soil EC involves multiple steps, including collecting, drying, grinding, and mixing the soil with water. The EC soil water solution is then measured with a meter that quantifies the ability of a solution to transmit an electrical current. The ability of the solution to transmit an electrical current increases with ion concentration. Because different measurement approaches provide different EC values, it is important to consider the measurement approach when interpreting the values.

In general, within a measurement approach, the higher the EC value, the greater the salt concentration in the soil. Electrical conductivity can be measured in the field or laboratory. Field measurements are generally reported at apparent electrical conductivity (ECa) whereas laboratory measurements are reported as ECe or EC1:1. Field measurements of ECa complement and do not replace the laboratory measurement of EC.

Laboratory Measurements of Electrical Conductivity

Electrical conductivity measurements conducted in the laboratory can be combined with the measurement of K+, Na+, Ca2+, and Mg2+ to assess the risk of soil dispersion. In general, the higher the Na+ concentration, the higher the dispersal risk. However, this risk may be tempered if other soil cations are also present in high quantities. The classical approach to assess the risk of soil dispersion from high Na+ concentrations is to measure the exchangeable sodium percent (ESP) (100×Na/CEC). However, because the measurement of ESP is expensive, alternative techniques have been developed (see Chapter 4 of the new Salinity and Sodicity book). The most common approaches are to determine the sodium adsorption ratio (SAR) or sodium percentage (%Na). In the laboratory, the measurement of EC is attributed only to differences in the concentrations of the cations and anions in the soil solution, whereas in the field, ECa measurements can be influenced by many factors, including total dissolved salts, soil texture, bulk density, and temperature (He et al., 2018; Doolittle & Brevik, 2014). Because in-field ECa measurements are relatively inexpensive, they are well suited for conducting an initial assessment of salinity spatial variability. However, because many factors can influence ECa, care must be used when interpreting this information.

The Seven Steps for Using an Apparent Electrical Conductivity Sensor to Assess Soil Salinity

Soil sensors that measure ECa have been used to better understand the soil spatial and temporal variability.

Field Measurements of Apparent Soil Electrical Conductivity

There are a variety of sensors designed to measure EC in the field. These sensors may use different technologies. For example, the Veris MSP3 (Veris Technology) system generates a small electrical current that is transferred into the soil through a pair of electrode coulter disks. A second pair of coulters then measures the drop in voltage, which is proportional to the soil’s EC. A second method is utilized by an EM sensor (see chapter 5 of the Salinity and Sodicity book). This sensor does not come into physical contact with the soil, and it uses a coil to induce an EM field into the soil. The ECa is based on changes in the EM field. Electromagnetic sensors range from mobile to stationary, and they can be configured in multiple ways (Mat Su & Adamchuk, 2023). When comparing these two approaches, it is important to consider that they provide slightly different values (Mat Su & Adamchuk, 2023).

In the laboratory, the electrical conductivity of a solution is measured, whereas in the field, the ability of the soil to conduct an electrical current or modify and EM field is measured. These measurement approaches are generally correlated to each other; however, the relationship is dependent on temporal and spatial changes of many factors, including soil temperature, moisture, bulk density, and texture.

These sensors can be used to identify soil zones with high bulk densities, soil textural changes, and high salt concentrations. The primary benefit of these sensors is that they provide an inexpensive rapid assessment that is easy to interpret. By combining ECa sensor information with chemical analysis, locations, and elevation information, useful maps can be created. However, because ECa sensors are sensitive to many factors, ECa cannot be directly converted to ECe. To use ECa to assess salinity issues, a seven-step process should be used. In this example, you are asked by a client to help determine the problems and solutions in a field that has a patchwork of low and highly productive areas.

Step 1: Determine the Likely Problem

Visiting a site and obtaining site histories is an important first step in the creation of a remediation plan that removes excess salts from the soil and improves plant and soil health. This information may include identifying the location, conducting a farmer interview to obtain prior histories, making targeted measurements of the soil’s physical properties, analyzing historic yield monitor and remote-sensing data, and identifying the soil types and chemical characteristics. For example, the image shown in Figure 1 highlights areas with different ECa values. However, prior to assuming that salinity or sodicity are the primary problems, it is important to look for evidence supporting this suspicion. For example, does the soil classification suggest that it is a salt-affected soil (Chapter 3 of the Salinity and Sodicity book), or does prior soil sampling indicate that the EC or %Na are relatively high?

In the information collection stage, it is important to consider that multiple problems can have similar symptoms. For example, compaction by itself or when combined with salinity and sodicity can produce similar symptoms. A rapid approach to assess compaction is to determine the soil texture, friability, and penetrometer resistance (Kumar et al., 2016). Soil texture is the relative amount of sand, silt, and clay, whereas friability is the tendency for a soil to crumble into smaller fragments. Penetrometer resistance is the resistance of soil to the insertion of a probe. Friability and penetrometer resistance decrease with increasing soil water. Sodium can affect both values by dispersing the soil aggregates.

The measurement of the soil bulk density and water infiltration can provide additional information. Bulk density is the dry weight of soil per unit volume of soil, and relative water infiltration can be measured by digging a small hole and measuring how fast the water disappears. Sodium-dispersed soils can have high bulk densities and low water infiltration rates. When inspecting the site, it is important to collect a soil sample for laboratory analysis to determine the soil EC and the amount of exchangeable Na+ on the exchange sites (ESP, SAR, or %Na). See Chapter 4 [of the new Salinity and Sodicity book] for details on chemical analysis.

Step 2: Select a Sensor and Measurement Approach

To develop corrective solutions, the source and extent of the problem must be identified. There are many approaches to assess the extent of a salinity and sodicity problem, including analyzing soil samples collected from a grid design for ECe and ESP or using an EM sensor to create an ECa map (Doolittle & Brevik, 2014). If you choose to collect and analyze soil samples for EC, then a soil-sampling protocol must be selected. There are many options to collect soil samples, ranging from composite soil samples from management zones to grid soil sampling (Clay & Carlson, 2016). When selecting a sensor, consider costs, skill requirements to collect the samples, and desired outcomes. Whenever possible, the sampling protocol should match the problem. For example, if the problem is concentrated in the surface soil, then the sensor should concentrate on the soil surface, whereas if the problem is concentrated at a lower soil depth, then a sensor should be selected that measures deeper in the soil profile (Corwin & Yemoto, 2020). Clues about the location of the salinity and sodicity problem may be provided in the soil name (Chapter 3 of the Salinity and Sodicity book), inspecting the site, or by collecting soil samples from targeted areas for analysis.

Step 3: Calibrate the Sensor

All data collection protocols start with ensuring that the equipment is well-maintained and calibrated. To assess temporal and spatial changes in soil salinity and sodicity, ECa sensors should be calibrated prior to use. Calibration can be conducted by at least two approaches. The first approach is to use the sensor to measure ECa followed by collecting soil samples from the study area, that are analyzed for ECe, followed by comparing the ECa and ECe values. The second approach is to follow the manufacturer calibration procedures. It is essential to standardize the device to a uniform output to accurately make comparisons from one year to the next. Temperature calibrations may also be required.

Step 4: Conduct the Survey

Conducting a survey starts with creating a sampling design. The sampling design should be based on identifying the extent of the problem. Two basic approaches can be used to conduct the survey. In the first approach, a stop-and-go measurement approach is used. In a stop-and-go approach, a grid is overlayed on the field. At each grid point, the location and elevation are measured with a global position satellite (GPS) system, and a sensor measures the ECa. At selected sampling points, a soil sample is collected that will be analyzed for EC using an appropriate protocol.

In the second approach, an EM sensor and GPS system is driven across a field. This sensor measures ECa, elevation, and location/elevation simultaneously. When using this approach, the surveyor selects the distance between the transects. Where possible, the transects should be perpendicular to elevation. The survey should avoid field edges because these areas often are compacted or have high EC resulting from runoff from roads.

Step 5: Analyze the Soil Samples

Soil samples should be analyzed as soon as possible using an appropriate protocol. In most situations, the samples should be analyzed for EC, pH, Cl−, NO3−, SO42−, Na+, K+, Ca2+, and Mg2+ and for the relative amount of Na+ on the soil’s cation exchange sites. The ratio between Na and the CEC is the ESP. However due to cost, the ESP value is often replaced by the SAR or %Na values. Additional information for analyzing soil samples is available in Chapter 4 (of the new Salinity and Sodicity book), and information about GPS is available in Shannon et al. (2018).

Step 6: Convert ECa to ECe or EC1:1

After the EM survey has been conducted and the associated soil samples are analyzed, the relationship between ECa and ECe/EC of a 1:1 soil/water mixture (EC1:1) can be determined. For this analysis, it might be necessary to separate the field into management zones. Management zones can be based on a soil survey or elevation map. Across the field or within a zone, determine the relationship and equation relating ECa to ECe or EC1:1. Based on this relationship, convert the ECa to ECe or EC1:1.

Step 7: Graphic Display

One of the goals for conducting the survey is to assist in soil sampling and implementing remediation treatments. Prior to displaying the data set, check it for errors that need to be removed. When displaying the map, let the software process the data and create a map. When using this approach, it is important to compare the map with the field and the producer’s knowledge. In many situations, overlaying the ECa map on an elevation map makes sense (Figure 2). Low areas in production fields often have high ECa values. High values are often linked to areas with high ECe values or contain compacted soil zones, whereas low values may be associated to coarse-textured soil. If the maps are not useful, try adjusting the boundary ECe values of the zones. There are several approaches to convert ECa to ECe. The most common is to determine the relationship between ECa and ECe and make the conversion based on this relationship. This generally involves determining the ECa and ECe values at selected points, followed by determining the equation that relates the two values.

In summary, EM surveys are not designed to replace but to compliment traditional plant and soil health measurements. To create a useful EM map, technical know-how is required about GPS, the EM sensor, and data processing. Electromagnetic values are influenced by many factors, such as texture, moisture content, salt concentration, temperature, and bulk density, so when converting ECa to ECe, it is important to understand relationships among these parameters. If more than one property is found to be highly correlated to ECa, a multivariate model may be required. A sensor that measures ECa is a relatively low-cost approach for creating directed soil maps, and when the sensor is maintained, standardized, and calibrated, it can be used to create management zones.

Case Studies on the Use of Apparent Electrical Conductivity Information

He et al. (2018) collected 1,088 soil samples from a 12.2- by 12.3-m grid within a 8.1-ha (20 ac) field. Soil samples were analyzed for EC1:1, pH1:1, soil dispersion, and the concentration of Ca2+, Mg2+, Na+, and K+. At the sampling points, ECa was measured with an EM 38 when the sensor was in the horizontal and vertical dipole modes. Soils at the North Dakota site were Natruaquoll and Calciaquolls. There was a strong correlation between apparent horizontal dipole EC (ECah) and %Na (r2 = 0.71), ECah and ECe (r2 = 0.79), and ECe and %Na (r2 = 0.77).

All geo-referenced data were entered into the ArcGIS 10.0, and interpolation maps of %Na, EC1:1, ECah, and apparent vertical dipole EC were prepared using the ordinary inverse-distance-weight interpolation. Finally, a management zone map was created in Management Zone Analyst 1.0.1 using the ECah and %Na data sets. After the zones were delineated, composite soil samples from each zone could be collected to determine the gypsum requirement.

Amezketa (2007) evaluated the ability of using ECa information for mapping saline/sodic soils in Navarre, Spain. The fields were underlain by saliferous rock strata, and ECa was measured from an orthogonal grid that varied depending on the field size. Soil water content was approximately field capacity, and ECa values were corrected to a reference temperature of 25°C (77°F). About 10–30 soil-sampling sites that corresponded to a full range of EM 38 measurements were surveyed within each field (site selected with the help of ESAP-RSSD program). Multiple linear regression (preloaded prediction model) included in ESAP-calibrate was then used to estimate the calibration equation by pairing ECa readings with laboratory-analyzed soil property data. The ECa and SAR values were strongly correlated (r >0.91). These results were attributed to autocorrelation (r >0.93) between ECe and SAR in all fields. The calibration models accounted for 87% of the observed variability in salinity and 84% in sodicity. Soil salinity and sodicity raster maps were prepared by IDS interpolation of EM-estimated profile average ECe and SAR values.

Ganjegunte et al. (2013) used an EM sensor to measure salinity and sodicity in turfgrass soil watered with saline water. Tall fescue (Lolium arundinaceum) and Kentucky bluegrass (Poa pratensis) were irrigated with water that had EC values of 0.6 and 2.98 dS/m. At the end of the study, ECa was measured using an EM 38 only in the horizontal coil configuration. Locations and ECa were measured every 4.3 m (14.1 ft) in transects separated by 20 m (65.6 ft). After completing the survey, 24 locations were selected for soil sampling. At each point, soil samples were collected in 15-cm (6 inch) increments to a depth of 75 cm (29.5 inches). Soil samples were analyzed for ECe, pH, concentration of Na+, Ca2+, and Mg2+ using plasma spectroscopy and for SAR. Based on a strong relationship between ECa and ECe, point kriging using a linear model was used to create an ECe map based on the ECa data. These findings showed that kriging can be used to create an ECe map based on EM data.

Summary

Electrical conductivity can be measured in the field continuously using either physical contact or EM induction. With physical contact, an electrical current is injected into the soil, and the detector measures the resulting voltage, whereas an EM meter does not make direct contact but instead uses a coil to produce an EC field. Both sensors measure the ECa, which is different from laboratory-derived EC values. This article discussed the feasibility of using laboratory measurements to convert field-measured ECa data into ECe values. A seven-step process for this site-specific conversion was proposed. The primary benefits of the EC sensor approach are the low cost and the increased speed at which useful information can be collected. As a result, the EC sensor approach reduces the cost of conducting a salinity and sodicity survey.

Acknowledgments

Funding for this article was provided by South Dakota State University, South Dakota Corn Utilization Council, USDA-AFRI (SD00G656-16 and SD00H555-15), and USDA-NRCS-CIG (69-3A75-285).

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