The statistical description of the spatial variability of soil properties is a preliminary step to the application of other quantitative techniques, for example, optimal spatial interpolation by kriging. The spatial correlation between the experimental data is characterized by the covariance function that is usually inferred from the experimental measurements. An appealing method for performing this inference is maximum likelihood estimation.
This paper describes the results of the application of maximum likelihood estimation to the inference of the spatial covariance of infiltration measurements for a small catchment. Because there are a large number of experimental data, the approximate maximum likelihood method has been used to overcome the computational burden imposed by the calculation of the complete likelihood. As will be shown, this method, used in conjunction with classical graphical variogram analysis (method of moments), provides more objective inference of covariance parameters.