The ability to predict the spatial distribution of tree root system variables (e.g., the Root system Area (RA), the maximum root diameter, the number of roots in diameter classes, the density of fine roots, etc.) under different environmental conditions is relevant to several scientific disciplines and to engineering practice. In this work, three well known analytical models from the literature are assembled into a unique framework called the Root Distribution Model (RDM). RDM models the expected vertical and horizontal distribution of coarse and fine root system variables for mature plants growing in different environmental conditions ranging from moderately humid to arid climates. All soil and moisture dynamic parameters are physically based, which make the model straightforward to calibrate via a single tuning parameter. At this investigative stage, it is shown that the model has the flexibility to represent a broad range of situations where soil moisture may result from precipitation inputs or from water level fluctuations due to either the presence of a water course or of deep aquifers or both. Accordingly, the distribution of the sectional RA may be either positively or negatively skewed, as well as show a peculiar bi-modal structure. The model can be used to study the impact of changing scenarios affecting precipitation, aquifer and channel hydrology.