Multispectral and hyperspectral imaging of submerged objects is a key technique in the airborne detection of environmental degradation in marine structures such as reefs, shellfish habitats, and seagrass beds. Additional applications involve detection of submerged ordnance in nearshore reef and surf zones, as well as contraband detection in drug interdiction operations. Unfortunately, the spectral response variability of targets, media (atmosphere and seawater), and camera optical components (e.g., intensifier and dielectric filter coatings) currently obviates accurate model-based detection of submerged objects from airborne imagery, based on spectral signature alone. In this paper, the first of a two-part series, we discuss and quantify various sources of target, media, and sensor errors that confound the signature-based recognition of submerged objects under realistic conditions. Analyses are based on data published primarily in the open literature, and are couched in terms of a model of signature recognition in which optical path perturbations are referred to the focal plane. Given such a model, the spatial and spectral detectability of submerged objects can be more readily predicted within the limits of accuracy incurred by standard measurements of ocean optical parameters.