The quantification and prediction of soil properties is fundamental to further understanding the Critical Zone (CZ). In this study we aim to quantify and predict soil properties within a forested catchment, Marshall Gulch, AZ. Input layers of soil depth (modeled), slope, Saga wetness index, remotely sensed normalized difference vegetation index (NDVI) and national agriculture imagery program (NAIP) bands 3/2 were determined to account for 95% of landscape variance and used as model predictors. Target variables including soil depth (cm), carbon (kg/m 2 ), clay (%), Na flux (kg/m 2 ), pH, and strain are predicted using multivariate linear step-wise regression models. Our results show strong correlations of soil properties with the drainage systems in the MG catchment. We observe deeper soils, higher clay content, higher carbon content, and more Na loss within the drainages of the catchment in contrast to the adjacent slopes and ridgelines.