This study investigates the potential of using multispectral Unmanned Aerial Vehicle (UAV) imagery to model the shallow water depths of the Kuibyshev Reservoir, Russia. Traditional methods like boom soundings and echo sounders, while accurate, are labor-intensive and costly. By leveraging multispectral data from UAVs, we aim to provide a more efficient and detailed approach to bathymetric mapping. Our methodology involved conducting bathymetric surveys with a Garmin GPS Map 178C and a Geoscan 401 Geodesy UAV equipped with a MicaSense RedEdge-MX camera. We performed correlation analysis and modelled depth using various regression techniques, identifying the Decision Tree Regressor as the top-performing model with an R² value of 0.98. Our findings suggest that UAV multispectral bathymetry is a viable alternative for local-scale shallow water mapping, with significant implications for reservoir management and ecological studies.