The amount of wave and tidal energy entering an estuary from the ocean is highly influenced by the entrance morphology, therefore, the ability to accurately detect and measure bathymetric changes in morphology is highly desirable for coastal managers. As in-situ bathymetric data collection is often costly and/or logistically challenging, bathymetry derived from multispectral and hyperspectral imagery has become widely used. This paper details an ongoing investigation into the suitability of using UAV captured multispectral imagery to develop a repeatable methodology to detect and measure inlet morphological variability. Specifically, this study utilises multispectral imagery to derive bathymetric models using the empirical algorithm first proposed by Stumpf et al (2003) to determine inlet variability through time. This paper and presentation documents an ongoing field campaign of UAV multispectral imagery capture, the development of bathymetric models from this imagery and the validation of these bathymetric models using contemporaneous single beam sonar surveys. The study inlet, Moonee Creek, is on the south-east Australian coast and is a small, microtidal, wave dominated inlet. The ability to document inlet variability in a rapid and resource-effective way will help manage current and future challenges within estuarine systems and will help create more resilient communities. This study hopes to provide a methodology that will help understand the variability of coastal inundation under varying morphological entrance scenarios, which will support current and future coastal management decision making and planning.