The Effect of Changes in Bulk Density on Soil Electrical Conductivity as Measured with the Geonics EM-38

Brevik, Eric C.; Fenton, Thomas E.

doi:10.2136/sh2004.3.0096

Cited by 33 publications

(17 citation statements)

References 10 publications

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“…Averaged values for clay and stone content were 18 and 7%, with a standard deviation of 2.5 and 6%, respectively. The average ρ b value was 1.76 Mg m -3 , and standard deviation for the field was 0.10 Mg m -3 ; ρ b variations of this level are unlikely to significantly influence the ECa readings (Brevik and Fenton, 2004). Stone content showed great spatial variability across the catchment, with higher stone contents occurring mainly on the south facing slopes, in the northern part of the catchment (Fig.…”

Section: Resultsmentioning

confidence: 91%

Temporal stability of electrical conductivity in a sandy soil

Pedrera‐Parrilla

Brevik

Giráldez

et al. 2016

International Agrophysics

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Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.

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Section: Resultsmentioning

confidence: 91%

Temporal stability of electrical conductivity in a sandy soil

Pedrera‐Parrilla

Brevik

Giráldez

et al. 2016

International Agrophysics

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“…In this respect, the initial EC of rain water and its residence time in the soil may play a key role along with the mineralogical composition of the soil. Soil compaction affects EC due to the reduced porosity and increased soil particle-to-particle contact (Corwin et al, 2008;Brevik and Fenton, 2004). Soil temperature also affects EC, which increases approximately 1.9 % per degree centigrade (U.S.D.…”

Section: Introductionmentioning

confidence: 99%

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

Martini

Werban

Zacharias

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ , with particular focus on the temporal variability of the spatial patterns of ECa and θ . To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ , and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ , and the use of EMI-based ECa data with respect to hydrological applications.

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“…Bronson et al [16] concluded that ECa can be used as potential tool to provide information about soil properties such as clay content and extractable Ca in the U.S. Southern High Plains, but that spatial covariance needs to be considered as it can improve estimation of ECa. Changes in bulk density resulting from management practices within or between fields on the order of 0.12 to 0.13 g·cm −3 lead to changes in soil ECa affecting soil interpretations made in the field using the EM-38 [17]. Previous studies on ECa relationship with soil properties and crop yields either on small field scale or watershed scale, were carried out without considering the effects of topographic positions (such as shoulder, backslope, and deposition slope).…”

Section: Introductionmentioning

confidence: 99%

Spatial Relation of Apparent Soil Electrical Conductivity with Crop Yields and Soil Properties at Different Topographic Positions in a Small Agricultural Watershed

2016

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Use of electromagnetic induction (EMI) sensors along with geospatial modeling provide a better opportunity for understanding spatial distribution of soil properties and crop yields on a landscape level and to map site-specific management zones. The first objective of this research was to evaluate the relationship of crop yields, soil properties and apparent electrical conductivity (ECa) at different topographic positions (shoulder, backslope, and deposition slope). The second objective was to examine whether the correlation of ECa with soil properties and crop yields on a watershed scale can be improved by considering topography in modeling ECa and soil properties compared to a whole field scale with no topographic separation. This study was conducted in two headwater agricultural watersheds in southern Illinois, USA. The experimental design consisted of three basins per watershed and each basin was divided into three topographic positions (shoulder, backslope and deposition) using the Slope Position Classification model in ESRI ArcMap. A combine harvester equipped with a GPS-based recording system was used for yield monitoring and mapping from 2012 to 2015. Soil samples were taken at depths from 0-15 cm and 15-30 cm from 54 locations in the two watersheds in fall 2015 and analyzed for physical and chemical properties. The ECa was measured using EMI device, EM38-MK2, which provides four dipole readings ECa-H-0.5, ECa-H-1, ECa-V-0.5, and ECa-V-1. Soybean and corn yields at depositional position were 38% and 62% lower than the shoulder position in 2014 and 2015, respectively. Soil pH, total carbon (TC), total nitrogen (TN), Mehlich-3 Phosphorus (P), Bray-1 P and ECa at depositional positions were significantly higher compared to shoulder positions. Corn and soybeans yields were weakly to moderately (<±0.75) correlated with ECa. At the deposition position at the 0-15 cm depth ECa-H-0.5 was weakly correlated (r < ±0.50) with soil pH and was moderately correlated (r = ±0.50-±0.75) with organic matter (OM), calcium (Ca) and sulfur (S). Slope variation from 1%-20% at the research site had a strong influence on soil properties at watershed scale. When data from all topographic positions were combined together in all basins spatial interpolation between Mehlich-3 P and ECa-H-0.5 resulted in a larger cross validation RMSE compared to individual shoulder and backslope positions. Results demonstrated that topographic position should be considered while making correlations of ECa with soil properties. Methods of delineating topography positions presented in this paper can easily be replicated on other fields with similar landscape characteristics and EMI sensor based survey techniques can certainly improve and help in making detailed prediction maps of soil properties.

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The Effect of Changes in Bulk Density on Soil Electrical Conductivity as Measured with the Geonics EM-38

Cited by 33 publications

References 10 publications

Temporal stability of electrical conductivity in a sandy soil

Temporal stability of electrical conductivity in a sandy soil

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

Spatial Relation of Apparent Soil Electrical Conductivity with Crop Yields and Soil Properties at Different Topographic Positions in a Small Agricultural Watershed

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