The emergence of multi-beam echo sounders (MBES) as an applicable surveying technology in shallow water environments has expanded the extent of geomorphic change detection studies to include river environments that historically have not been possible to survey or only small portions have been surveyed. The high point densities and accuracy of MBES has the potential to create highly accurate digital elevation models (DEM). However, to properly use MBES data for DEM creation and subsequent analysis, it is essential to quantify and propagate uncertainty in surveyed points and surfaces derived from them through each phase of data collection and processing. Much attention has been given to the topic of spatially variable uncertainty propagation in the context of the construction of DEM and their use in geomorphic change detection studies. However little work has been done specifically with applying spatially varying uncertainty models for MBES data in shallow water environments. To address this need, this report presents a review of literature and methodology of uncertainty quantification in a geomorphic change detection study. These methods are then applied and analyzed in a geomorphic change detection study using MBES as the data collection technique.