Estimating the spatial variability of soil physical and chemical properties is a prerequisite for soil and crop-specific management. The objectives of this study were to determine the degree of spatial variability and variance structure of soil physical and chemical properties on a 40-ha agricultural field in Las Cruces, New Mexico, to observe any change in the variance structure caused by the cropping system and to suggest future sampling designs to make efficient management decisions. Soil samples were collected at the center of a regular grid of 50 m × 50 m and on the grid line during November 2008 and 2009 from 0 to 15 cm of depth. The software package GS+ was used to model the variance structure of sand, silt, clay, soil bulk density, saturated hydraulic conductivity (Ks), pH, electrical conductivity (EC), nitrate-nitrogen (NO3-N), chloride, and volumetric water content at six different matric potentials (−33, −100, −300, −500, −1,000, and −1,500 kPa). The coefficient of variation ranged from 4% (pH) to 141% (Ks). The semivariograms showed that the range of spatial dependence varied from 86 m (pH, 2008) to 563 m (Ks) for all measured soil properties. Cross-semivariograms showed that NO3-N and EC were spatially correlated; therefore, kriging or cokriging can be used to estimate NO3-N values throughout the growing season from easily available EC data. Correlograms with Moran I indicated that a distance of 140 m was sufficient to yield independent samples for measured soil physical and chemical properties. The kriged contour maps showed positional similarities. These contour maps of soil properties, along with their spatial structures, can be used in making better future sampling designs and management decisions.