Spatial pattern consistency and repeatability of proximal soil sensor data for digital soil mapping

Data from proximal soil sensors can facilitate digital soil mapping at high spatial resolutions. However, their use for predicting static soil properties, such as texture, is affected by spatio-temporal changes in environmental and measurement conditions. In this research study, seasonal changes in spatial patterns and repeatability of data provided by a platform that simultaneously measures the red (Red) and near infrared (NIR) reflectance, apparent soil electrical conductivity (ECa), temperature, and volumetric moisture content of topsoil (at 3–6 cm depth) were assessed. Test fields are located in Southern Finland with textures dominated by clay and fine sandy till. During single scans, mean relative differences between the data from duplicated measurement points ranged from ~4% to 6% and were the highest for temperature and Red values. The consistency of spatial patterns across seasons (spring and autumn 2021 and 2022) was the highest for ECa values, and the lowest for NIR. ECa and moisture were significant for predicting the clay contents at a cereal grain crop site, whereas temperature was significant at grass ley sites. Errors were generally lower when using spring data compared with autumn data (RMSE ranging from 4.8% to 11.1% for the data from different fields and measurement dates). For the fields, where static soil properties change at small spatial scales, spatially detailed moisture and temperature data support the understanding of seasonal changes in the spatial patterns derived from multi-sensor data, and the corresponding changes in the performance of calibration models.     

气候和土壤质地对土壤有机碳影响的区域差异研究

The agricultural soil carbon pool plays an important role in mitigating greenhouse gas emission ana unaerstanamg the son orgamc carbon-climate-soil texture relationship is of great significance for estimating cropland soil carbon pool responses to climate change. Using data from 900 soil profiles, obtained from the Second National Soil Survey of China, we investigated the soil organic carbon （SOC） depth distribution in relation to climate and soil texture under various climate regimes of the cold northeast region （NER） and the warmer Huang-Huai-Hai region （HHHR） of China. The results demonstrated that the SOC content was higher in NER than in HHHR. For both regions, the SOC content at all soil depths had significant negative relationships with mean annual temperature （MAT）, but was related to mean annual precipitation （MAP） just at the surface 0-20 cm. The climate effect on SOC content was more pronounced in NER than in HHHR. Regional differences in the effect of soil texture on SOC content were not found. However, the dominant texture factors were different. The effect of sand content on SOC was more pronounced than that of clay content in NER. Conversely, the effect of clay on SOC was more pronounced than sand in HHHR. Climate and soil texture jointly explained the greatest SOC variability of 49.0% （0-20 cm） and 33.5% （20-30 cm） in NER and HHHR, respectively. Moreover, regional differences occurred in the importance of climate vs. soil texture in explaining SOC variability. In NER, the SOC content of the shallow layers （0-30 cm） was mainly determined by climate factor, specifically MAT, but the SOC content of the deeper soil layers （30-100 cm） was more affected by texture factor, specifically sand content. In HHHR, all the SOC variability in all soil layers was predominantly best explained by clay content. Therefore, when temperature was colder, the climate effect became stronger and this trend was restricted by soil depth. The regional differences and soil depth influence underscored the importance of explicitly considering them in modeling long-term soil responses to climate change and predicting potential soil carbon sequestration.     

Effect of Continuous Rice–Wheat Rotation on Soil Properties from Four Agro‐ecosystems of Indian Punjab

In Indian Punjab, rice–wheat is a dominant cropping system in four agro‐ecosystems, namely undulating subregion (zone 1), Piedmont alluvial plains (zone 2), central alluvial plains (zone 3), and southwestern alluvial plains (zone 4), varying in rainfall and temperature. Static and temporal variabilities in soil physical and chemical properties prevail because of alluvial parent material, management/tillage operations, and duration of rice–wheat rotation. A detailed survey was undertaken to study the long‐term effect of rice–wheat rotation on soil physical (soil separates, bulk density, modulus of rupture, saturated and unsaturated hydraulic conductivities, soil water content, and suction relations) and chemical (organic carbon, pH, electrical conductivity) properties of different textured soils (sandy clay loam, loam, clay loam, and silty clay loam) in these four zones of Punjab. Soil samples (of 0‐ to 30‐cm depth) from 45 sites were collected during 2006 and were analyzed for physical and chemical properties. The results showed that sand content and pH increased whereas silt and organic carbon decreased significantly from zones 1 to 4. Compared to other textures, significantly greater organic carbon, modulus of rupture, and pH in silty clay loam; greater bulk density in clay loam, and greater saturated hydraulic conductivity in sandy clay loam were observed. Irrespective of zone and soil texture, in the subsurface soil, there was a hard pan at 15–22.5 cm deep, which had high soil bulk density, modulus of rupture, more silt and clay contents (by 3–5%) and less organic carbon and hydraulic conductivity than the surface (0–15 cm) layer. These properties deteriorated with fineness of the soil texture and less organic carbon content. Continuous rice–wheat cropping had a deleterious effect on many soil properties. Many of these soils would benefit from the addition of organic matter, and crop yields may also be affected by the distinct hardpan that exists between 15 and 22.5 cm deep.     

基于磁感式探测的分层土壤盐分精确解译模型

为了精准解译面域尺度土壤盐分特征,有必要建立分层土壤盐分信息精确解译模型。该文应用通径分析方法,研究获得了土壤全盐量、土壤含水率、体积质量、黏粒质量分数、地下水电导率、地下水埋深等作用因子对土壤表观电导率值的方差贡献率及作用强弱排序。依据各作用因子的方差贡献率大小,结合设定的累积贡献率阀值,选取出磁感式土壤表观电导率的主导作用因子,确定为磁感式土壤盐分信息解译模型的参数体系。采用多因子及互作项逐步回归法,通过引入因子间的互作效应建立优化的基于磁感式探测的分层（0～20,＞20～60,＞60～100,＞100～160 cm）土壤盐分信息解译模型。验证结果表明,模型解译误差基本在10%以内,达到了较高精度水平。     

Modelling soil salinity across a gilgai landscape by inversion of EM38 and EM31 data

The soil in arid and semi‐arid areas is often markedly saline, which can severely limit agricultural productivity. Increasingly, geophysical methods are being implemented to map the levels and areal extent of soil salinity. One of the most effective methods is electromagnetic (EM) induction with instruments designed to measure apparent soil electrical conductivity (EC_a). This study describes the generation of electromagnetic conductivity images (EMCIs) by inverting EC_a data obtained with the EM38 and EM31 devices along two closely‐spaced transects by the EM inversion approach in the EM4Soil package. The EM38 EC_a data are shown to be a more effective predictor of soil EC_e. Calibration equations based on calculated true electrical conductivity (σ) and measured electrical conductivity of a saturated soil‐paste extract (EC_e) provide reliable estimates of EC_a. The patterns of σ in a test of the method in soil developed over thick alluvium on a clay plain in central New South Wales, Australia, compare favourably with existing pedological mapping; the mounds and depressions of gilgai were strongly differentiated from the more sandy alluvial sediments that characterize prior stream channels. The overall approach is potentially useful for generating a single calibration equation that can be used to predict EC_e at various depths in the soil. Improvements in EMCI modelling can also be sought by joint inversion of EM with other geophysical datasets.     

Influences of nitrogen treatments and irrigation methods on soil chemical properties

Abstract

Changes in soil chemical properties were investigated in conjunction with an ongoing study of fertility and irrigation relationships of cotton. Four irrigation methods and five nitrogen fertilization rates were the primary focus of the study. The four irrigation regimes studied were: high frequency center pivot, low frequency center pivot, furrow irrigated, and unirrigated. Nitrogen rates were 0, 30, 60, 90, and 120 lb N/A. Soil samples were collected from each plot in 6‐in‐ increments to a depth of 24 in. in 1982 and again in 1986 after four years of continuous cotton production. The soil samples were analyzed for pH, organic matter (OM), P, K, electrical conductivity (EC), and NO₃ ^‐‐N. All background soil characteristics were found to vary with depth with the exception of NO₃ ^‐‐N. The follow‐up sampling and testing in 1986 showed significant differences in soil properties as a function of irrigation, N‐fertilization, depth, and their interactions. Nitrates were accumulated in the 18 to 24‐in. depth under high (120 lb N/A) fertilization, and in the 0 to 6‐in. depth under the four lower treatments (0, 30, 60, and 90 lb N/A). Soil pH was highest in the furrow and high frequency center pivot irrigated regimes and lowest in the unirrigated regime. Soil pH also decreased with depth. Electrical conductivity of the soil was highest in the high frequency regime and not significantly different among the other three irrigation methods. The 0M content of the soil was greatest in the high frequency regime but not significantly different in the low frequency, furrow, or unirrigated blocks. Soil 0M was found to decrease with depth through 18 in. in all cases. The P and K status of the soil was not changed as a result of the N fertilization or irrigation treatments.     

Effects of charcoal production on maize yield,chemical properties and texture of soil

The effects of charcoal production on soil textural and chemical properties were investigated in Ejura, Ghana. The aim was to study the effects of heating and charcoal residue on maize yield, soil texture and soil chemical properties. Composite samples were taken from the 0–10 cm layer of soil at charcoal-making sites and from adjacent fields (control). Twelve sites were randomly selected for the study across the range of the Kotokosu watershed. Maize was planted in four selected locations on charcoal site soils (CSS) and adjacent field soils (AFS) to assess the impact of charcoal production on crop yield. There was a significant increase in soil pH, base saturation, electrical conductivity, exchangeable Ca, Mg, K, Na and available P in the soil at the kiln sites as compared to the adjacent soils. A relative change of up to 329% was observed in K while organic C and total N decreased by 9.8% and 12.8%, respectively. Organic C and total N were highly correlated ( P <0.01) and both parameters significantly ( P <0.05) depended on clay minerals in the soils. Soil texture was also modified with a significantly higher sand content and lower clay fraction in the CSS. The grain and biomass yield of maize increased by 91% and 44%, respectively, on CSS as compared to AFS. Further research to ascertain the long-term effects of charcoal production on the soil environment and the fertility of tropical soils is needed.     

Assessment of soil texture class on agricultural fields using ECa,Amber NDVI,and topographic properties

Soil texture (ST) is relatively stable over time, although it may change due to erosion, clay eluviation, and other processes. Soil texture affects soil quality, productivity and management. Therefore, indirect, accurate methods for assessing of soil texture classes (STCs) are needed in agricultural practice. A study was performed on four production fields in northern and central Poland to compare the fitting performance of STC models based on apparent electrical conductivity (ECa), topographic properties (elevation, slope gradient and wetness index) and Amber NDVI measurements. One common and accurate indicator of STCs was not found for all study fields. On average, ECa was most accurate in indicating areas of different STCs within the fields, but it tended to overestimate the size of sandy areas on loamy fields and vice versa. The accuracy of STC assessment using ECa measurements may be biased due to imperfect soil drainage, high elevations, which increase evaporation and STC variation with depth. STC assessment using Amber NDVI measurements may be useful, particularly on flat and sandy fields, but the results are affected by the same factors as ECa, and additionally by crop growth stages and by the weather conditions in the period preceding the measurements. Despite the good quantitative results of the STC assessment by elevation (one field) and by the topographic wetness index (another field), both terrain attributes failed to accurately indicate the distribution of some STC areas within each field. Therefore, in landscapes developed from deposits of the last glaciation relevant ST differences might not sufficiently be detected by the analysis of terrain attributes alone. The selection of STC predictors and evaluation of the assessment quality must consider both the quantitative indicators such as correlation and determination coefficients describing relationships between ST and ECa, NDVI and topography and percentage of a field area with accurately indicated STC and the distribution of areas with different STCs within a field. The use of ECa, NDVI values, and topographic properties for STC assessment may be useful in reducing costs of soil sampling and analysis, but cannot replace it.     

Interpreting method of regional soil salinity 3D distribution based on inverse distance weighting

为了建立面域三维土壤盐分信息精准解译与表征技术方法,该研究以反距离权重空间数据插值方法结合电磁感应式表观土壤电导率快速测定技术为基础,成功构建出典型干旱区土壤盐分分层精确解译模型,对研究区土壤盐分进行了精度解析与评估,以三维图形方式直观揭示了土壤盐分空间分布特征。研究区不同区位土壤盐分呈现出不同的剖面分布类型特征,研究区主体土壤属于中度以上盐渍化。该研究将为土壤盐分三维空间分布特征解析与评估提供可靠技术方法。     

基于反距离权重插值的土壤盐分三维分布解析方法

为了建立面域三维土壤盐分信息精准解译与表征技术方法,该研究以反距离权重空间数据插值方法结合电磁感应式表观土壤电导率快速测定技术为基础,成功构建出典型干旱区土壤盐分分层精确解译模型,对研究区土壤盐分进行了精度解析与评估,以三维图形方式直观揭示了土壤盐分空间分布特征。研究区不同区位土壤盐分呈现出不同的剖面分布类型特征,研究区主体土壤属于中度以上盐渍化。该研究将为土壤盐分三维空间分布特征解析与评估提供可靠技术方法。     

Deep infiltration through a sandy alluvial fan in semiarid Niger inferred from electrical conductivity survey,vadose zone chemistry and hydrological modelling

In semiarid southwestern Niger, most of the groundwater recharge is indirect and occurs through endoreic ponds. Elsewhere in the landscape, there is no evidence of deep infiltration, with a possible exception for gullies and alluvial fans on sandy slopes. In order to verify this hypothesis, a detailed geophysical and geochemical survey was conducted on a large, representative mid-slope fan (6 ha). At this site, distributed hydrological modelling conducted over the encompassing endoreic catchment (190 ha) showed high losses of runoff water by infiltration. Electromagnetic mapping and 2-D electrical imaging survey were used to investigate the 35 m deep vadose zone; in addition, 8 boreholes were drilled following the geophysical survey to constrain the interpretation. Variations in apparent electrical conductivity measured in boreholes appear to be mainly linked with changes in the soil solution mineralization. An extrapolation throughout the area shows that apparent electrical conductivity of the ground is systematically lower below channels; this suggests localised leaching through the unsaturated zone. A physically-based, 2-D distributed hydrologic model was used to estimate the amount of surface water loss by infiltration for the 1992–2002 period. Depending on year, infiltrated volumes range from 1000 to 24 000 m³. This represents between 5% and 16% of the runoff that reaches the final outlet of the basin, an endoreic valley bottom pond where recharge to the aquifer has been shown to occur. Because leaching of the vadose zone is observed down to a depth of 10 m below channels, episodic groundwater recharge through sandy mid-slope fans is highly probable during rainy years.     

干旱区棉田表层土壤盐渍化时空变异研究

明确土壤盐渍化时空变异特征是确保干旱区棉田精准灌溉和作物良好生长发育的基础。考虑棉田不同灌溉节点和灌溉方式,利用大地电导率仪(EM38-MK2),在棉花生育期内进行3次表观电导率数据和土样的采集,采用局部建模和全局建模的思路构建表观电导率与实测电导率间的反演模型。综合利用经典统计方法和地统计学方法,分析表层土壤盐渍化的时空变异特征。结果表明,表观电导率与实测电导率建立的局部模型具有较好精度,R²均大于0.79,而全局模型的R²仅为0.52,表明局部模型优于全局模型;不同时期表层电导率变异性差异较大,3月和10月变异系数均小于50%,属中等变异,而7月变异系数大于50%,属强变异;各时期半变异函数的最优模型均为球状模型,基台值与块金值之比均小于25%,表明表层盐分变异主要由气候,蒸降比、地下水埋深度等结构性因素引起;研究区盐渍化土壤面积由播种前的0.49%增加到棉花收获后的98.23%,在棉花生育期内,表层土壤以轻度盐渍化和中度盐渍化为主;土壤盐渍化空间变异强度主要以中等变异为主,强变异次之,弱变异所占面积最小,而强变异集中分布在研究区南端,弱...     

Organic carbon stocks in topsoil and subsoil in long-term ley and cereal monoculture rotations

Soil organic C (SOC) in agricultural soils is affected by cropping system. In order to compare the impact of ley-dominated and cereal monoculture rotations on soil properties, a series of experiments was started in Sweden in the early 1980s. This study quantified the effect of rotations and N fertilisation on SOC stocks and microbial community composition. After 35 years, soil samples taken down to 50-cm depth at two sites with contrasting soil texture (clay and loam) were analysed for soil C and N, bulk density and phospholipid fatty acid (PLFA) content. Significant increases in SOC concentrations and stocks were found in the ley-dominated rotation compared with the cereal monoculture rotation, the difference being 0.36 and 0.59 Mg C ha^?1 year^?1 in the topsoil (0–20 cm) for sites with the clay and loam texture, respectively, in average over N fertiliser levels. Nitrogen fertilisation increased SOC stocks significantly in the cereal monoculture, but not in the ley-dominated rotation. In the loam, SOC responses in the subsoil were almost as high as those in the topsoil, but they were insignificant in the clay soil. These results indicate that soil texture and structure can have a great impact on the potential of subsoils to sequester C, which requires attention when scaling up SOC sequestration rates for regional or global assessments.     

Spatial estimation of surface soil texture using remote sensing data

Understanding the spatial distribution and variability of soil texture is essential for land use planning and other activities related to agricultural management and environmental protection. This study was conducted to evaluate Landsat Enhanced Thematic Mapper (ETM) remote sensing data as auxiliary variables for spatial estimation of surface soil texture using a limited number of soil samples taken from a site located in the city of PingduShandong ProvinceChina. Three methods of evaluating variability in surface soil texture were evaluated: (1) multiple stepwise regression (MSR) based on the relationship between surface soil sandsilt and clay contents and remote sensing data; (2) kriging of surface soil sandsilt and clay contents; (3) cokriging with remote sensing data. Correlation analysis showed that surface soil sandsilt and clay contents were significantly correlated with Landsat ETM digital number (DN) of six bands (Bands 1–5 and Band 7)and the DN of Band 7 explained most of the variability in soil sandsilt and clay contents. The DN of Band 7 was selected as auxiliary data for the estimation of surface soil texture. The cross-validation results indicated that both MSR and kriged estimates had low reliability due to the variations in landscape and the low-density sampling in the study area. Cokriging with remote sensing data significantly improves estimates of surface soil texture compared with MSR and kriging.     

积分方法用于校定逆转型土壤盐渍剖面的磁感式电导

Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity （ECa） and soil electrical conductivity of a saturated soil paste extract （ECe） or a 1：5 soil water extract （EC1：5） using an electromagnetic induction instrument （EM38）. The modeled coefficients, one of the successful and classical methods hitherto, were chosen to calibrate the EM38 measurements of the inverted salinity profiles of characteristic coastal saline soils at selected sites of Xincao Farm, Jiangsu Province, China. However, this method required three parameters for each depth layer. An integration approach, based on an exponential decay profile model, was proposed and the model was fitted to all the calibration sites. The obtained model can then be used to predict EC1：5 at a certain depth from electromagnetic measurements made using the EM38 device positioned in horizontal and vertical positions at the soil surface. This exponential decay model predicted the EC1：5 well according to the results of a one-way analysis of variance, and the further comparison indicated that the modeled coefficients appeared to be slightly superior to, but not statistically different from, this exponential decay model. Nevertheless, this exponential decay model was more significant and practical because it depended on less empirical parameters and could be used to perform point predictions of EC1：5 continuously with depth.     

陕西三种类型土壤剖面硝酸盐累积、分布与土壤质地的关系

研究了陕北黄绵土,关中土与陕南水稻土土壤剖面中硝酸盐的分布与累积,分析了硝酸盐淋移与土壤剖面粘粒含量的关系。结果表明,黄绵土由于粘粒含量少,土壤疏松,氮肥施入土壤后硝化作用速度快,氮素多以硝态氮存在于土壤中,遇到过量的灌溉或降水,容易引起硝酸盐淋失。在米脂的川道地,施肥2个月后,硝酸盐峰值在50cm左右,4个多月后,峰值下移至100cm左右,6个月后,该峰值下降到130cm左右,一年内,硝酸盐的峰值已经消失,分布在130至350cm之间。因此,在黄绵土地区可以灌溉的川道地,氮素损失的主要途径是硝酸盐淋失。关中土,粘粒含量相对较高,硝化作用速度快,但由于在80120cm有一粘化层,阻碍了水分与硝酸盐的向下淋移,使得大部分硝酸盐累积在0100cm土层,其累积量占到0400cm总累积量的64%～74%,而200400cm仅占到7%～13%。而且淋移到100cm以下的硝酸盐,也通过反硝化损失了。陕南水稻土,由于深层土壤水饱和,硝酸盐难以向下淋移,氮素主要累积在土壤表层。由于下层土壤长期处于厌气条件,即使淋移到下层的硝酸盐也通过反硝化作用而损失掉了。     

基于EM38长江河口地区土壤盐渍化特征研究

运用电磁感应仪EM38,结合GIS技术和地统计方法对长江河口地区土壤含盐量的空间变异性进行研究,结果表明:EM38所测土壤表观电导率与土壤电导率(EG_(1:5))的相关系数均达到1%显著水平,其中以EM_h+EM_v为自变量的多元回归方程的拟合效果最好.盐分含量统计特征表明,土壤盐分含量变幅较大,且随着深度的增加变化幅度逐渐减小,各层土壤盐分含量均值介于0.713 6～0.813 7 g/kg之间,且随着深度的增加盐分含量均值逐渐增大,总体上盐分分布具有一定的底聚性;各土层含盐量均呈现中等变异强度.变异系数相差较大,在水平方向上含盐量的变异随深度的增加而逐步趋弱.盐分含量空间分布表明,各层土壤盐分含量由南向北、自东向西有逐渐降低的趋势,随着深度的增加土壤含盐量不断升高.盐化土面积百分比表明,该地区大部分为非盐化土,轻度盐化土和中度盐化土所占比例较小,但由于含盐母质和地下水矿化度两个主要因素的影响,土壤盐渍化的发生存在巨大的潜在性威胁,运用EM38测值解译所得土壤盐分含量真实地反映了研究区的土壤盐渍化状况,为该地区土壤盐渍化的改良及防范提供依据.     

Determination of Soil Type Boundaries using Electromagnetic Induction Scanning Techniques

Information on the spatial distribution of soil texture and soil water is vital in understanding crop yield variation. Such information allows improved management of all agricultural inputs. One of the limiting factors in the mapping of soil texture information, however, is cost.Confusion matrix analysis was used to determine whether bulk apparent electrical conductivity (ECa) data derived from electro-magnetic induction (EMI) scanning at field capacity, and clustered using a k-means algorithm, accurately delineates soil textural boundaries in a field containing clay loam and sandy loam soils.The ECa map was compared to two soil surveys, the first conducted at one sample per hectare and the second at four to eight samples per hectare. Using confusion matrix analysis a significantly stronger relationship was measured between the ECa map and soil units of the more intensive soil map, than with the lower sampling density soil survey. This relationship was between two classes of soil with a difference in clay content of 12% and two clusters with a difference in mean ECa of 16·9 mS m⁻¹.     

Morphological,chemical, and physical characteristics of shrink‐swell soils in a mediterranean semiarid region

Abstract

Heavy clay soils with swell‐shrink properties comprise most of the arable land in northern Jordan. These soils are classified as Vertisols. Vertisols occupy a large and important part of the agricultural land in Jordan where rainfed agriculture is practiced. Five sites were selected to represent Vertisols occurring in different precipitation zones. Soil characterization was carried out to provide useful information to understand the genesis and behavior of these soils. Vertisols in northern Jordan occur on flat to gently sloping plains. Clay, silt, and sand fractions were uniformly distributed indicating active pedoturbation. Clay content is moderate to high, and the higher the rainfall the higher the clay content. The high cation exchange capacity (CEC)/clay ratio suggest montmorillonitic and mixed mineralogy. Calcium (Ca) was the most dominant extractable cation followed by magnesium (Mg), sodium (Na), and potassium (K). The similar patterns of distribution for the electrical conductivity values and soluble cations throughout the studied soil sites indicate the low leaching rate, eluviation, and illuviation processes within these studied sites. All soils belong to the Haploxererts soil great group.     

Use of an electromagnetic technique to determine sodicity in saline-sodic soils

Soil sodicity is an increasing problem in arid‐land irrigated soils that decreases soil permeability and crop production and increases soil erosion. The first step towards the control of sodic soils is the accurate diagnosis of the severity and spatial extent of the problem. Rapid identification and large‐scale mapping of sodium‐affected land will help to improve sodicity management. We evaluated the effectiveness of electromagnetic induction (EM) measurements in identifying, characterizing and mapping the spatial variability of sodicity in five saline‐sodic agricultural fields in Navarre (Spain). Each field was sampled at three 30‐cm soil depth increments at 10–30 sites for a total of 267 soil samples. The number of Geonics‐EM38 measurements in each field varied between 161 and 558, for a total of 1258 ECa (apparent electrical conductivity) readings. Multiple linear regression models established for each field predicted the average profile ECe (electrical conductivity of the saturation extract) and SAR (sodium adsorption ratio of the saturation extract) from ECa. Despite the lack of a direct causal relationship between ECa and SAR, EM measurements can be satisfactorily used for characterizing the spatial distribution of soil sodicity if ECe and SAR are significantly auto‐correlated. These results provide ancillary support for using EM measurements to indirectly characterize the spatial distribution of saline‐sodic soils. More research is needed to elucidate the usefulness of EM measurements in identifying soil sodicity in a wider range of salt and/or sodium‐affected soils.