Floods affected approximately two billion people around the world from 1998–2017, causing over 142,000 fatalities and over 656 billion U.S. dollars in economic losses. Flood data, such as the extent of inundation and peak flood stage, are needed to define the environmental, economic, and social impacts of significant flood events. Ground-based global positioning system (GPS) surveys of post-flood high-water marks (HWMs) and topography are commonly used to define flood inundation and stage, but can be time consuming, difficult, and expensive to conduct. Here, we demonstrate and test the use of small unmanned aircraft systems (sUAS) and close-range remote sensing techniques to collect high-accuracy flood data to define peak flood stage elevations and river cross sections. We evaluate the elevation accuracy of the HWMs from sUAS surveys by comparison with traditional GPS surveys, which have acceptable accuracy for many post-flood assessments, at two flood sites on two small streams in the United States. Mean elevation errors for the sUAS surveys were 0.07 m and 0.14 m for the semiarid and temperate sites respectively, and those values are similar to typical errors when measuring HWM elevations with GPS surveys. Results demonstrate that sUAS surveys of HWMs and cross sections can be an inexpensive and efficient alternative to GPS surveys, and we provide insights that can be used to decide whether sUAS or GPS techniques will be most efficient for post-flood surveying.