Multiscaling analysis and random cascade modeling of dye infiltration

Abstract

We aimed at investigating whether the spatial variability of infiltration in field soils, as visualized through dye infiltration experiments, is characterized by a multiscaling behavior. Digitized high‐resolution dye images from three sites in an experimental catchment in Tunisia were analyzed using three indicators of scaling: empirical probability distribution functions, power spectra, and raw statistical moments. The two former indicators suggested a general scaling behavior of the data, which through the moments' analysis was found to be of multiscaling type. Random cascade processes are frequently used to model multiscaling processes, and we fitted the “universal multifractal” (UM) model of Schertzer and Lovejoy [1987] to our data. The UM model closely reproduced the empirical K(q) functions, and simulated fields reproduced key features in the observed ones. The results indicate that multiscaling random cascade modeling is useful for statistically describing flow processes and solute transport under field conditions.