Spatial soil sampling design using apparent soil electrical conductivity measurements

Siqueira, Glécio Machado; Dafonte, Jorge Dafonte; Paz‐González, Antonio; Vázquez, Eva Vidal; Armesto, Monteserrat Valcarcel; Filho, Osvaldo Guedes

doi:10.1590/1678-4499.445

Cited by 4 publications

(3 citation statements)

References 31 publications

(23 reference statements)

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“…It can be used as a direct indicator of the soil condition including the influence of recreational load Sarah et al, 2015). Also, information on soil electrical conductivity can be used to design an optimal placement of test polygons for the spatial modeling of the other soil and ecological properties whose number of samples is limited due to the complexity of carrying out field studies (Siqueira et al, 2016). The results obtained indicated an important role of relief predictors for explanation of the spatial variability of soil electrical conductivity.…”

Section: Discussionmentioning

confidence: 97%

Recreation and terrain effect on the spatial variation of the apparent soil electrical conductivity in an urban park

et al. 2020

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Recreation is an important cultural ecosystem service and is able to significantly affect soil heterogeneity and vegetation functioning. This study investigated the role of the relief and tree stand density in the apparent soil electrical conductivity variation within an urban park. The most suitable variogram models were assessed to evaluate the autocorrelation of the regression models. The map of the spatial variability of apparent soil electrical conductivity was built on the basis of the most suitable variogram. The experimental polygon was located in the Botanical Garden of Oles Honchar Dnipro National University (Dnipro City, Ukraine). The experimental polygon was formed by a quasi-regular grid of measurement locations located about 30 m apart. The measurements of the apparent electrical conductivity of the soil in situ were made in May 2018 at 163 points. On average, the value of soil apparent electric conductivity within the investigated polygon was 0.55 dSm/m and varied within 0.17–1.10 dSm/m. Such environment predictors as tree stand density, relief altitude, topographic wetness index, and potential of relief to erosion were able to explain 48% of the observed variability of soil electrical conductivity. The relief altitude had the greatest influence on the variation of soil electrical conductivity, which was indicated with the highest values of beta regression coefficients. The most important trend of the electric conductivity variation was due to the influence of relief altitude and this dependence was nonlinear. The smallest values of the soil electrical conductivity were recorded in the highest and in lowest relief positions, and the largest values were detected in the relief slope. Recreational load can also be explained by the geomorphology predictors and tree stand density data. These predictors can explain 32% of the variation of recreational load. The variogram was built both for the soil apparent electrical conductivity dataset and for the residuals of the regression model. As a result of the procedure of the models’ selection on the basis of the AIC we obtained the best estimation of the variogram models parameters for the electrical conductivity and for the regression residuals of the electrical conductivity. The level of recreation was correlated statistically significantly with the apparent soil electrical conductivity. The residuals of regression models in which geomorphological indicators and tree stand density were used as predictors have a higher correlation level than the original variables. The soil electrical conductivity may be a sensitive indicator of the recreation load.

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Section: Discussionmentioning

confidence: 97%

Recreation and terrain effect on the spatial variation of the apparent soil electrical conductivity in an urban park

et al. 2020

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“…Field evaluations of soil apparent electrical conductivity (EC a ) (mS m -1 ) was carried out using an electromagnetic induction device (EM38) (GEONICS, 1999), which measures the horizontal dipole (EC a -H), with readings within the soil layer 0.0-0.4 m and the vertical dipole (EC a -V), with readings within the layer 0.0-1.5 m, following the procedures described by Siqueira, Silva and Dafonte (2015) and Siqueira et al (2016b).…”

Section: Methodsmentioning

confidence: 99%

“…The determination of the EC a measured by electromagnetic induction is related to different soil properties because its readings are the result of the interactions between soil porous spaces, which are filled with air or water, interactions between soil particles, and structure state SILVA;DAFONTE, 2015;SIQUEIRA et al, 2016a). Thus, information on the correlations of EC a measured by electromagnetic induction to other soil properties in different types of soil and crops is important SILVA;DAFONTE, 2015;SIQUEIRA et al, 2016b).…”

Section: Introductionmentioning

confidence: 99%

Spatial Continuity of Electrical Conductivity, Soil Water Content and Texture on a Cultivated Area With Cane Sugar

Silva

Siqueira

et al. 2018

Rev. Caatinga

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Spatial variability of soil attributes affects crop development. Thus, information on its variability assists in soil and plant integrated management systems. The objective of this study was to assess the spatial variability of the soil apparent electrical conductivity (ECa), electrical conductivity of the saturation extract (ECse), water content in the soil (θ) and soil texture (clay, silt and sand) of a sugarcane crop area in the State of Pernambuco, Brazil. The study area had about 6.5 ha and its soil was classified as orthic Humiluvic Spodosol. Ninety soil samples were randomly collected and evaluated. The attributes assessed were soil apparent electrical conductivity (ECa) measured by electromagnetic induction with vertical dipole (ECa-V) in the soil layer 0.0.4 and horizontal dipole (ECa-H) in the soil layer 0.0-1.5 m; and ECse, θ and texture in the soil layers 0.0-0.2 m and 0.2-0.4 m. Spatial variability of the ECa was affected by the area relief, and had no direct correlation with the electrical conductivity of the saturation extract (ECse). The results showed overestimated mean frequency distribution, with means distant from the mode and median. The area relief affected the spatial variability maps of ECa-V, ECa-H, ECse and θ, however, the correlation matrix did not show a well-defined cause-and-effect relationship. Spatial variability of texture attributes (clay, site and sand) was high, presenting pure nugget effect.

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Mapping Soil Texture Using Geostatistical Interpolation Combined With Electromagnetic Induction Measurements

García‐Tomillo

Mirás-Avalos²,

Dafonte

et al. 2017

Soil Science

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Spatial soil sampling design using apparent soil electrical conductivity measurements

Cited by 4 publications

References 31 publications

Recreation and terrain effect on the spatial variation of the apparent soil electrical conductivity in an urban park

Recreation and terrain effect on the spatial variation of the apparent soil electrical conductivity in an urban park

Spatial Continuity of Electrical Conductivity, Soil Water Content and Texture on a Cultivated Area With Cane Sugar

Mapping Soil Texture Using Geostatistical Interpolation Combined With Electromagnetic Induction Measurements

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