Effect of Soil Texture, Water Content and Temperature on Apparent Soil Electrical Conductivity

2011 ◽  
Author(s):  
Hamid Farahani
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Soil Texture ◽  
Soil Electrical Conductivity

ESTIMATING SPATIAL VARIATIONS OF SOIL WATER CONTENT USING NONCONTACTING ELECTROMAGNETIC INDUCTIVE METHODS

1988 ◽  
Vol 68 (4) ◽  
pp. 715-722 ◽  
Author(s):  
R. G. KACHANOSKI ◽  
I. J. VAN WESENBEECK ◽  
E. G. GREGORICH
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Solution ◽  
Soil Texture ◽  
Spatial Variations ◽  
Bulk Soil ◽  
Soil Electrical Conductivity ◽  
Solution Conductivity

The relationships among the spatial variations of soil water content, soil texture, soil solution electrical conductivity, and bulk soil electrical conductivity were examined for a field characterized by net drainage and low concentrations of dissolved electrolytes. Bulk soil electrical conductivity was measured over various depths at 52 locations within a 1.8-ha field using noncontacting electromagnetic inductive meters. Soil water content (0–0.5 m depth) was measured at the same locations using the time domain reflectometry method. Measurements of soil texture and soil solution conductivity were obtained from core samples from 37 of the sampling locations. Soil water content at the site ranged from 0.06 to 0.36 m3 m−3. Clay content ranged from 2.5 to 44% percent and bulk soil electrical conductivity ranged from 0.0 to 0.21 S m−1. Significant correlation existed among almost all of the measured variables. Regression analysis indicated soil solution conductivity had no effect on measured bulk soil electrical conductivity for soil water contents less than 0.25 m3 m−3. Bulk soil electrical conductivity explained 96% of the spatial variation of soil water content independent of a wide range of soil texture. Autocorrelations of soil water content were similar to autocorrelations for bulk soil electrical conductivity. Under conditions similar to those in the study area, it should be possible to infer spatial variations in soil water content quickly by measuring bulk electrical conductivity using noncontacting electromagnetic inductive meters. Key words: Spatial variability, soil water, electrical conductivity, soil texture

scholarly journals Applying Nitrogen Site-Specifically Using Soil Electrical Conductivity Maps and Precision Agriculture Technology

2001 ◽  
Vol 1 ◽  
pp. 767-776 ◽  
Author(s):  
E.D. Lund ◽  
M.C. Wolcott ◽  
G.P. Hanson
Keyword(s):  
Electrical Conductivity ◽  
Case Studies ◽  
Crop Yield ◽  
Soil Texture ◽  
Precision Agriculture ◽  
Management Practices ◽  
N Availability ◽  
Soil Electrical Conductivity ◽  
Variable Yield ◽  
Wide Range

Soil texture varies significantly within many agricultural fields. The physical properties of soil, such as soil texture, have a direct effect on water holding capacity, cation exchange capacity, crop yield, production capability, and nitrogen (N) loss variations within a field. In short, mobile nutrients are used, lost, and stored differently as soil textures vary. A uniform application of N to varying soils results in a wide range of N availability to the crop. N applied in excess of crop usage results in a waste of the grower’s input expense, a potential negative effect on the environment, and in some crops a reduction of crop quality, yield, and harvestability. Inadequate N levels represent a lost opportunity for crop yield and profit. The global positioning system (GPS)-referenced mapping of bulk soil electrical conductivity (EC) has been shown to serve as an effective proxy for soil texture and other soil properties. Soils with a high clay content conduct more electricity than coarser textured soils, which results in higher EC values. This paper will describe the EC mapping process and provide case studies of site-specific N applications based on EC maps. Results of these case studies suggest that N can be managed site-specifically using a variety of management practices, including soil sampling, variable yield goals, and cropping history.

scholarly journals Using Multivariate Geostatistics to Assess Patterns of Spatial Dependence of Apparent Soil Electrical Conductivity and Selected Soil Properties

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Glécio Machado Siqueira ◽  
Jorge Dafonte Dafonte ◽  
Montserrat Valcárcel Armesto ◽  
Ênio Farias França e Silva
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Clay Content ◽  
Data Sets ◽  
Soil Electrical Conductivity ◽  
Multivariate Geostatistics ◽  
Northwestern Spain

The apparent soil electrical conductivity (ECa) was continuously recorded in three successive dates using electromagnetic induction in horizontal (ECa-H) and vertical (ECa-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the ECadata sets was used to devise an optimized sampling scheme consisting of 40 points. Soil was sampled at the 0.0–0.3 m depth, in these 40 points, and analyzed for sand, silt, and clay content; gravimetric water content; and electrical conductivity of saturated soil paste. Coefficients of correlation between ECaand gravimetric soil water content (0.685 for ECa-V and 0.649 for ECa-H) were higher than those between ECaand clay content (ranging from 0.197 to 0.495, when different ECarecording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the ECadata sets recorded at successive dates and the analyzed soil properties. Ordinary and universal cokriging methods have improved the estimation of gravimetric soil water content using the data of ECaas secondary variable with respect to the use of ordinary kriging.

The effect of soil electrical conductivity on moisture determination using time-domain reflectometry in sandy soil

2000 ◽  
Vol 80 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Z. J. Sun ◽  
G. D. Young ◽  
R. A. McFarlane ◽  
B.M. Chambers
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Saline Soil ◽  
Time Domain Reflectometry ◽  
Propagation Time ◽  
Soil Electrical Conductivity ◽  
Volumetric Soil Water Content ◽  
Volumetric Soil Water

A series of laboratory experiments was conducted, in order to systematically explore the effect of soil electrical conductivity on soil moisture determination using time domain reflectometry (TDR). A Moisture Point MP-917 soil moisture instrument (E.S.I. Environmental Sensors Inc., Victoria, BC, Canada) was used to measure propagation time (time delay) of a step function along a probe imbedded in fine sand with different moisture and salinity. The volumetric soil water content was independently determined using a balance. With the help of the diode-switching technique, MP-917 could detect the reflection from the end of the probe as the electrical conductivity of saturated soil extract (ECe) increased to 15.29 dS m−1. However, the relationship between volumetric soil water content and propagation time expressed as T/Tair (the ratio of propagation time in soil to that in air over the same distance) deviated from a linear relationship as the conductivity exceeded 3.72 dS m−1. At the same water content, the time delay in a saline soil was longer than that in a non-saline soil. This leads to an over-estimation of volumetric soil water content when the linear calibration was applied. A logarithmic relationship between volumetric soil water content and T/Tair has been developed and this relation includes soil electrical conductivity as a parameter. With this new calibration, it is possible to precisely determine the volumetric water content of highly saline soil using TDR. Key words: Time domain reflectometry, time delay, bulk electrical conductivity (σ), volumetric soil water content (θ), relative permittivity or dielectric constant (εr), propagation velocity Vp

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