EM38 for volumetric soil water content estimation in the root-zone of deep vertosol soils

Hossain, Md. Belal; Lamb, David; Lockwood, Peter; Frazier, Paul

doi:10.1016/j.compag.2010.07.003

Cited by 28 publications

(12 citation statements)

References 21 publications

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“…EMI sensors have been largely tested for a quite large number of environmental issues such as: the detection of buried utilities and services (El-Qady et al, 2014), the detection and tracing of archaeological remains (De Smedt et al, 2013), the imaging of permafrost (Dafflon et al, 2013), the depth-to-clay estimation (Saey et al, 2009), the definition of groundwater levels (Sherlock and McDonnell, 2003;Buchanan and Triantafilis, 2009), the assessment of soil pollution and soil quality (Corwin and Lesch, 2005), the spatial pattern delineation of the soil textures (Abdu et al, 2008) and plant communities (Robinson et al, 2008c), the interpretation of hydrological/biogeochemical processes (Robinson et al, 2009) , 1997;Akbar et al, 2005;Hezarjaribi and Sourell, 2007;Huth and Poulton, 2007;Robinson et al, 2009;Hossain et al, 2010;Padhi and Misra, 2011;Hedley et al, 2013) or in sites with no-or limited vegetation (Sheets and Hendrickx, 1995; 9 published papers also shows that the spatial and temporal variance of SM explained by EMI-EC a data is highly varying. Figure 1 provides a summary of the reported R 2 of the linear fit in the reviewed papers.…”

Section: In This Regards Methods Based On Cosmic-ray Neutrons Andmentioning

confidence: 99%

Field test of a multi-frequency electromagnetic induction sensor for soil moisture monitoring in southern Italy test sites

Calamita

Perrone

Brocca

et al. 2015

Journal of Hydrology

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Section: In This Regards Methods Based On Cosmic-ray Neutrons Andmentioning

confidence: 99%

Field test of a multi-frequency electromagnetic induction sensor for soil moisture monitoring in southern Italy test sites

Calamita

Perrone

Brocca

et al. 2015

Journal of Hydrology

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“…ECa has been frequently used in the establishment of soil management zones and in the inference of several edaphic physicochemical properties and their respective spatial variation . In agricultural soils, ECa has been used to characterize soil salinity (Rhoades et al, 1989); soil texture (Sudduth et al, 2003); soil depth ; soil moisture (Hossain et al, 2010); soil organic matter (OM) (Corwin & Lesch, 2005a) and cation exchange capacity (Kitchen et al, 2000). However, various authors have shown inconsistent relationships between ECa and soil characteristics, probably due to the fact that ECa is influenced by complex site dependent soil properties interactions (Corwin et al, 2003;Sudduth et al, 2005).…”

Section: Data Collection Using the Veris 3100mentioning

confidence: 99%

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Peralta

Cicore

Marino

et al. 2015

Span. j. agric. res.

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The spatial variability in soils used for livestock production (i.e. Natraquoll and Natraqualf) at farm and paddock scale is usually very high. Understanding this spatial variation within a field is the first step for site-specific crop management. For this reason, we evaluated whether apparent electrical conductivity (ECa), a widely used proximal soil sensing technology, is a potential estimator of the edaphic variability in these types of soils. ECa and elevation data were collected in a paddock of 16 ha. Elevation was negatively associated with ECa. Geo-referenced soil samples were collected and analyzed for soil organic matter (OM) content, pH, the saturation extract electrical conductivity (EC ext ), available phosphorous (P), and anaerobically incubated Nitrogen (Nan). Relationships between soil properties and ECa were analyzed using regression analysis, principal components analysis (PCA), and stepwise regression. Principal components (PC) and the PC-stepwise were used to determine which soil properties have an important influence on ECa. In this experiment elevation was negatively associated with ECa. The data showed that pH, OM, and EC ext exhibited a high correlation with ECa (R 2 =0.76; 0.70 and 0.65, respectively). Whereas P and Nan showed a lower correlation (R 2 =0.54 and 0.11 respectively). The model resulting from the PC-stepwise regression analysis explained slightly more than 69% of the total variation of the measured ECa, only retaining PC1. Therefore, EC ext , pH and OM were considered key latent variables because they substantially influence the relationship between the PC1 and the ECa (loading factors>0.4). Results showed that ECa is associated with the spatial distribution of some important soil properties. Thus, ECa can be used as a support tool to implement site-specific management in soils for livestock use.Additional key words: multivariate techniques; soil properties; geographic information system; lowland soils; spatial variability. Abbreviations used: ECa (apparent soil electrical conductivity); EC ext (electrical conductivity of the saturation extract); GWR (geographically weighted regression); Nan (anaerobically incubated nitrogen); OM (soil organic matter content); P (available phosphorous); PCA (principal component analysis); PC (principal component).Citation: Peralta, N. R.; Cicore, P. L.; Marino, M. A.; Marques da Silva, J. R.; Costa, J. L. (2015). Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production.

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“…We used the non-destructive Slingram method to characterize the EC of the first 2 m of soil. This method has often been used to study interactions between plants and soils (Myers et al, 2007;Hossain et al, 2010). A previous study (Grellier et al, 2013a), dedicated to methodology, validated the geophysical method, which was used and was simplified in this study to assess our ecological questions regarding tree encroachment (cf.…”

Section: Introductionmentioning

confidence: 99%

Soil clay influences Acacia encroachment in a South African grassland

Grellier

Florsch

Janeau³

et al. 2014

Ecohydrology

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Because of technical difficulties in measuring soil properties at a large scale, little is known about the effect of soil properties on the spatial distribution of trees in grasslands. We were interested in the associations of soil properties with the phenomenon of tree encroachment, where trees increase in density at the expense of grasses. The spatial variation of soil properties and especially soil texture may modify the properties of hydraulic conductivity, and the availability of soil water and mineral nutrients, which in turn may affect the spatial distribution of encroaching trees. Through the development of a geophysical method (Slingram) using an electromagnetic device EM38 and Bayesian inversion, we were able to accurately map soil electrical conductivity (EC) of a Luvisol in a grassland of South Africa. EC measured at the 0·8 to 2 m depth on a 1·5 ha area is a proxy for clay content and was correlated with the spatial distribution of four size classes of the encroaching Acacia sieberiana. Tree location (all sizes considered) was significantly correlated with EC. Tall acacias (>3m height) were totally absent from patches with EC >24 mS m−1. For all other size classes from medium trees to seedlings, tree density decreased with increasing EC. This suggests that high clay contents at depth associated with high EC values may prevent the establishment and/or survival of trees and influence the spatial distribution of A. sieberiana. This result also shows that geophysical tools may be useful for demonstrating important ecological processes. Copyright © 2014 John Wiley & Sons, Ltd.

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EM38 for volumetric soil water content estimation in the root-zone of deep vertosol soils

Cited by 28 publications

References 21 publications

Field test of a multi-frequency electromagnetic induction sensor for soil moisture monitoring in southern Italy test sites

Field test of a multi-frequency electromagnetic induction sensor for soil moisture monitoring in southern Italy test sites

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Soil clay influences Acacia encroachment in a South African grassland

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