Although numerous studies have investigated the effects of crop production practices on soil water dynamics, not much information is available on the impact of row position on solute transport. A field experiment was carried out to evaluate surface and subsurface solute transport properties in plant row, nontrafficked interrow, and trafficked interrow positions. For this purpose, a plot of 14 × 14 m in a strip-cropped field with soybean (Glycine max L. Merr), corn (Zea mays L.), and oat (Avena L.) was selected. After harvesting the crops, surface (top 2 cm) electrical conductivity measurements were made by time domain reflectometry at 45 locations during a chloride pulse leaching experiment. At the conclusion of the pulse leaching experiment, 120-cm deep soil cores were collected at the 45 locations to measure the soil profile chemical distributions. No crop or row position effects were observed for surface-determined pore water velocities (v), whereas profile-determined v was greater in plant row versus interrow positions when averaged over all crops. Overall, the profile-determined v was slightly greater than the surface determined v, probably because of lower effective or mobile water contents. The profile-determined dispersion coefficient (D) was smaller in row positions than interrow positions in soybean and corn, perhaps because of surface ponding in the interrow positions of the crops resulting in macropore flow. Profile-determined Dwas greater in the interrow positions of soybean than oat, again reflecting possible macropore flow. Overall, the mean soil profile dispersivity (λ = 2.97 cm) was larger than the surface soil (λ = 1.02 cm). The local surface solute transport varied by row positions, whereas profile solute transport was affected by both row position and crop, perhaps due to surface ponding producing macropore flow in the trafficked and nontrafficked interrows of soybean and the trafficked interrows of corn. Thus, a one-dimensional solute transport model with a spatially distributed flux or potential controlled upper boundary condition must be used to model this system.