Characterizing spatial variability in soil water content for precision irrigation management

2017 ◽  
Vol 8 (2) ◽  
pp. 418-422 ◽  
Author(s):  
A. de Lara ◽  
R. Khosla ◽  
L. Longchamps
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Irrigation Management ◽  
Soil Electrical Conductivity ◽  
Field Scale ◽  
Management Zones ◽  
Mean Differences ◽  
Precision Irrigation

One among many challenges in implementing precision irrigation is the reliable characterization of the soil water content (SWC) across spatially variable fields. For this purpose, commercial retailers are employing apparent soil electrical conductivity (ECa) to create irrigation prescription maps. The accuracy of this method at the field scale has received little attention from the scientific community. Hence, the objective of this study was to characterize spatial distribution of soil water content at the field scale for the purpose of precision irrigation management. Results showed mean SWC to be different across ECa derived management zones, indicating that soil ECa was able to characterize mean differences in SWC across management zones.

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.

Laboratory Characterization of a Commercial Capacitance Sensor for Estimating Permittivity and Inferring Soil Water Content

2006 ◽  
Vol 5 (3) ◽  
pp. 1048-1064 ◽  
Author(s):  
Mike Schwank ◽  
Timothy R. Green ◽  
Christian Mätzler ◽  
Hansruedi Benedickter ◽  
Hannes Flühler
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Capacitance Sensor ◽  
Laboratory Characterization

Time series outlier and intervention analysis: Irrigation management influences on soil water content in silty loam soil

2012 ◽  
Vol 111 ◽  
pp. 105-114 ◽  
Author(s):  
Basem Aljoumani ◽  
Jose A. Sànchez-Espigares ◽  
Nuria Cañameras ◽  
Ramon Josa ◽  
Joaquim Monserrat
Keyword(s):  
Time Series ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Irrigation Management ◽  
Intervention Analysis ◽  
Silty Loam ◽  
Loam Soil
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