The location and distribution of landform shape and size describe and categorize many features of a catchment. Landforms indicate soil types, arability of land, geological features, hydrological influences, and even shallow groundwater systems. This paper describes an objective method for delineating major landforms of a catchment on the basis of hydrological terrain analysis. It allows comparisons to be made within and between catchments. The method uses the UPNESS index from the Fuzzy Landscape Analysis Geographic Information System (FLAG) model (Roberts et al., 1997) that is derived from digital elevation data. UPNESS was developed as an index of surface and shallow subsurface water accumulation. In the method presented in this paper, we fit a five-parameter sigmoidal function to the cumulative distribution function (cdf) of the natural log (ln) of UPNESS. The point of inflection of the cdf of the UPNESS index is defined from the first derivative of the five-parameter sigmoidal function as the point of maximum concavity. The second and third points are defined by determining the maximum upward concavity and minimum downward concavity from the second derivative of a five-parameter sigmoidal function (referred to as break points). The inflection and break points from the UPNESS index are used to segment the cdf into three regions that represent four different landform elements. Landform categories based on these points represent ridge tops and upper slopes, midslopes, lower slope, and in-filled valley/alluvial deposits. The shape of the cdf curve indicates the dominance of major landforms within a catchment, providing an objective means for classifying this catchment characteristic. Examples are given showing how landform discrimination compares to geological maps. The landforms index presented in this study offers a useful technique for differentiating complex landforms from a landscape using terrain analysis that attempts to represent dominant hydrological soil formation processes.