Enormous amounts of hydrologic data are required to accurately simulate subsurface contaminant transport. Effectively supplementing measurements of hydrologic parameters such as permeability and porosity with ''soft'' information obtained from the interpretation of geologic cores and geophysical logs can improve the simulation of contaminant transport while reducing the measured data that are required. A method is presented herein for generating hydraulic conductivity fields comprised of several geological materials with hydraulic conductivities that can range over several orders of magnitude. This method utilizes indicator fields that are designed to allow random variation at the megascopic scale but are constrained by observations inferred from geophysical logs and geologic core data. The statistical description of random hydraulic conductivity values of distinct geological materials at the macroscopic scale may be obtained by conventional parameter estimation techniques. The combined approach can then be used to generate realizations of a hydraulic conductivity field for subsequent use in flow and transport simulations. The structural constraints confine realizations to vary about a nominal model in a physically reasonable manner. The uncertainty may be viewed as arising from two different scales. Variation in hydraulic conductivity at the macroscale may be viewed as an intrinsic statistical property of the particular geologic material but where measurements may be made in order to ascertain the statistical description. On the other hand, uncertainty at the megascale level arises from the fact that the large-scale system structure is only partially observable. It is the latter area where soft geologic information and geological knowledge can be useful in confining the uncertainty in the model to geologically reasonable limits. ¿ American Geophysical Union 1993