Rivers, estuaries, reservoirs, and lakes are multi-use systems that supply water for agricultural, industrial, and human consumption while simultaneously assimilating both point- and non-point source discharges. Existing methods of data collection are generally limited to snapshots in space and time while a comprehensive view of spatial variability remains elusive. Accelerating the integration of existing in-situ sensors, geospatial analysis techniques, and reliable autonomous sampling platform technologies provide immediate improvements for sampling and assessment programs. We provide a demonstration of this integration for high spatial resolution sampling and analysis in a non-wadeable river with an inexpensive unmanned sampling platform (USV), standards sensor arrays, and widely used geospatial techniques. These are used to creating 2-D maps of temperature, conductivity, salinity, turbidity, chlorophyll florescence and chromophoric dissolved organic matter (CDOM). 2-D surface water quality maps show significant influences on local water quality from tributary confluences, submarine groundwater plumes, floodplain/riparian interfaces and other patchily distributed limnological features. Moreover, this project demonstrates how sensors, autonomous vehicles, and geospatial technologies work in concert to create a more comprehensive spatial picture compared to the standard systematic sampling grid with data displayed as means and standard deviations.