Catchments exhibit heterogeneity in biophysical properties at different scales, making prediction and understanding catchment function a challenge.  One source of this complexity stems from the interactions between the spatiotemporal variability of hydrological states and fluxes and the difficulty in quantifying spatial structure and organization of soils. At the Hubbard Brook Experimental Forest in New Hampshire, we are embracing the structure and organization of soils and using soil functional groups that reflect dominant pedogenic and hydrologic process histories to understand the spatial relations between runoff sources and solute export and retention.  Our approach is based on a hydropedological conceptual model developed from over 175 soil characterization pits, 25 continuously recording groundwater wells, a matric potential sensor network, and both soil and soil solution chemistry in a 42 ha forested catchment.  These podzolized soils were classified into five functional groups called hydropedologic units (HPUs), which were established according to soil morphology.  We show that soil morphological spatial patterns can be predicted from a multinomial logistic regression model with 70% accuracy using topographic metrics determined from a LiDAR-derived DEM.  These soil spatial patterns also correlate with distinct groundwater dynamics, water flux direction, and chemical characteristics producing laterally and non-laterally developed podzols in predictable locations throughout the catchment.  This hydropedological approach provides insight into the spatial and temporal contributions streamflow generation and solute export from headwater catchments.