In using cokriging to study soil spatial variability, a key step is to determine cross-variograms. A recently developed approach was utilized to compute pseudo-cross-variograms, from which cross-variograms can be formulated. The approach does not require a large number of common locations where data are available for all variables used in the cokriging modeling and estimation processes. In this study, with only one-thirteenth of the original data for NO3 and Ca, valid cross-variograms, each with the electric conductivity (EC) were obtained by using pseudo-cross-variograms. Based on the cross-variograms, cokriging with EC improved the estimation of NO3 and Ca significantly. Cokriging yielded a smaller mean squared error (MSE) and kriging variance, and a higher correlation between estimates and measurements. Using 20 points of NO3 and 130 points of EC, cokriging provided a similar distribution pattern for NO3 as that generated with 100 points of NO3. Cokriging with EC reduced MSE and the mean kriging variance of the estimated Ca up to 78% and 85%, respectively, as compared with kriging.