Current soil maps contain qualitative attributes which are challenging to integrate into agronomic models or decision support systems. In this paper, a new approach is proposed that will enable the use of soil maps as a suitable information system of soils hydrostructural properties for agronomic and environmental models. This enhancement is possible through a new methodology for characterizing the soil units on the basis of the multi-scale soil-water functionality of the pedon which is a representative soil mapping unit delineated by pedologists according to the geomorphology. The hydro-functional mapping units should represent soil mapping units that are theoretically homogenous from the perspective of the pedostructure parameters of the pedon. For the purpose of this study, the Haggerty-Cox property, West Lafayette, Indiana, USA was selected. The soil data ''soil mapping units and physical characteristics'' of the study area were obtained from SSURGO. Due to time and cost constraints, the research was restricted to three SSURGO soil units (SwA, Starks-Fincastle complex with 0-2% slope; MsC2, Miami silt loam, 6-12% slopes; and HoA, Hononegah fine sandy loam with 0-2% slopes) to check their spatial homogeneity according to the pedostructure parameters (PS). The discriminant statistical analysis for the area of study shows that the PS parameters are unique for each soil mapping unit and can be effectively used to characterize these units and validate their delineation. The resulting hydro-functional soil mapping units match SSURGO units but have additional physical attributes. In general, subsurface horizons (B) are more distinguishable than surface horizons (Ap), and using pedostructure parameters from both potential and shrinkage curves gives the highest distinguishing value. Results confirm that the pedostructure parameters are discriminant characteristics of the hydrostructural functioning of soils as delineated by pedologists. Having the hydro-functional soil mapping units will assist in the decision support system data analysis, which in turn, will allow for the prediction of water and chemical transport and interactions.