Many modern hydrological models require data inputs provided by automated digital terrain analysis functions incorporated into GIS. These inputs include fields representing surface flow directions, up-slope contributing areas, and sub-catchment partitions. Existing raster-based terrain analysis tools, including both those in off-the-shelf GIS packages and those in the recent literature, were designed to work with digital elevation data in mountainous topography. For highly variable topography, which may include large flood plains, lakes, wetlands, and other relatively flat areas, existing tools cannot accommodate the variable signal-to-noise in the source elevation data without significant human intervention to handle special cases. A general model for calculating flow directions, up-slope contributing areas, and sub-catchment partitions that automatically adapts to the variable information content of grid-based elevation data sets is presented here. The model uses a combination of breadth-first search and global optimization to extract the maximum amount of signal from any location within the data. The model is demonstrated to work well in handling topography dominated by large flood plains, lakes and other flat areas without the need for a large number of empirical rules. An important contribution of the approach is the handling of explicit hydrologic features, which makes the spatial representation closely related to hydrological processes. The results have important implications for developing hydrological models that are tractable in large, heterogeneous watersheds using moderate resolution data.