While standard 2.5-acre grid soil sampling provides a uniform data map, it frequently miscalculates actual soil boundaries by ignoring localized topography. This analysis evaluates the efficiency of topography-driven landscape position models—categorizing fields into distinct summits, slopes, and alluvial depressions. By tying soil sampling directly to hydrological and landscape runoff positions rather than arbitrary geometric grids, operators can significantly optimize variable-rate fertilizer applications, predict localized crop yields more accurately, and reduce input waste across variable terrain.