Agricultural soil erosion is a serious problem on farms because it contributes to crop yield declines and beyond farms because it is a source of sediment and chemical pollutants. Ephemeral gullies effectively convey runoff and connect agricultural uplands to off-site waters, so control of this phenomenon would benefit multiple societal sectors. Soil conservationists often employ predictive soil erosion models to develop conservation plans, but commonly used models cannot account for ephemeral gully erosion. Future models with the capability to simulate such concentrated flow erosion must be verified with field measurements. This work sought to quantify the measurement uncertainty of a recently developed tool based on geo-referenced close-range digital photogrammetry and to apply it to naturally evolving channels in agricultural fields. Repeated photogrammetric surveys were conducted to create a set of point clouds, which were compared to define the two standard deviation (2σ) uncertainty in average elevation change between two point clouds as ± 1.29 to ± 2.55 mm (depending on surface relief), the 2σ relative vertical uncertainty of individual point clouds as 0.916 mm, and the 2σ geo-referenced vertical accuracy of entire point clouds as 8.26 cm. Utilization of the method at field monitoring sites resulted in average watershed-scale (0.47 to 3.19 ha) estimates of ephemeral gully erosion rates of 3.93, 0.847, and 0.415 Mg ha-1 for three time intervals during 2013 and 2014. For the average soil bulk density of approximately 1.2 Mg m-3, the vertical change uncertainty applied to estimate soil mass moved by ephemeral gully erosion resulted in an average sediment flux uncertainty of ± 0.175 Mg. The small uncertainties determined in the validation study and the plausible rates of soil loss by topographically concentrated overland flow quantified in the field study reflect the reliability of the data, which contributes to their utility for future refinement of soil erosion models that explicitly predict ephemeral gully erosion.