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The Scientific World Journal
Volume 2014, Article ID 712403, 11 pages
http://dx.doi.org/10.1155/2014/712403
Research Article

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

1Centro de Ciências Agrárias e Ambientais, Universidade Federal do Maranhão, BR-222, Km 04, s/n, Boa Vista, 65500-000 Chapadinha, MA, Brazil
2Departamento de Ingeniería Agroforestal, Escuela Politécnica Superior, Universidad de Santiago de Compostela, Campus Universitario, s/n, 27002 Lugo, Spain
3Departamento de Engenharia Agrícola, Universidade Federal Rural de Pernambuco, Dois Irmãos, 52171-900 Recife, PE, Brazil

Received 24 June 2014; Revised 26 August 2014; Accepted 28 August 2014; Published 31 December 2014

Academic Editor: Ana Maria Tarquis

Copyright © 2014 Glécio Machado Siqueira et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The apparent soil electrical conductivity (E) was continuously recorded in three successive dates using electromagnetic induction in horizontal (E-H) and vertical (E-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the E data 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 E and gravimetric soil water content (0.685 for E-V and 0.649 for E-H) were higher than those between E and clay content (ranging from 0.197 to 0.495, when different E recording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the E data 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 E as secondary variable with respect to the use of ordinary kriging.