The white‐tailed deer (Odocoileus virginianus) is an ecologically important species in forests of North America. Effective management of forests requires accurate, precise estimates of deer population abundance to plan and justify management actions. Spotlight surveys in combination with distance sampling are a common method of estimating deer population abundance; however, spotlight surveys are known to have serious drawbacks such as high costs and sampling biases. Therefore, we tested the effectiveness of enumerating deer from unmanned aerial vehicle (UAV) flights, conducted 1 and 6 March 2018, to develop population and density estimates in 2 United States National Parks: Harpers Ferry National Historic Park (HAFE) and Monocacy National Battlefield (MONO). Concurrent spotlight surveys at MONO enabled us to compare estimates obtained by the 2 methods. Deer density estimates by 4 observers of UAV‐obtained thermal imagery from HAFE were 94.5 ± 3.9 deer/km2. Concurrent UAV and spotlight surveys at MONO found 19.7 ± 0.5 deer/km2 and 6.4 ± 4.9 deer/km2, respectively; suggesting that spotlight surveys may significantly underestimate deer densities. Despite the logistical challenges to UAV operation, our findings demonstrate that UAVs will become an invaluable tool for wildlife management as technology improves. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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 U.S. Mean elevation errors for the sUAS surveys were 0.07 m and 0.14 m for the semiarid and temperate sites, respectively; 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 accurate and efficient alternative to GPS surveys; we provide insights that can be used to decide whether sUAS or GPS techniques will be most efficient for post-flood surveying.

streamgage network has provided important hydrologic information about rivers and streams throughout the Nation. Traditional streamgage methods provide reliable stage and streamflow data but typically only monitor stage at a single location in a river and require frequent calibration streamflow measurements. Direct measurements are not always feasible, therefore improved sensors and methods are being deployed at gages to better document streamflow conditions between measurements. The technology and techniques of reach-scale monitoring allow the U.S. Geological Survey to collect more data across the full range of streamflow without requiring that a hydrographer be present. The U.S. Geological Survey Arizona Water Science Center's reach-scale monitoring program will enhance the Arizona streamgage network with more accurate streamflow measurements and provide more extensive streamflow records and geomorphological datasets for our agency partners and the public. Reach-scale monitoring installations and techniques are applicable to streams of the western United States and likely throughout the Nation.