Abstract
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.
Highlights
Floods are largely uncontrollable phenomena that threaten infrastructure, property, and human life around the globe
Results demonstrate that small unmanned aircraft systems (sUAS) surveys of high-water marks (HWMs) and cross-sections can be an accurate and efficient alternative to global positioning system (GPS) surveys; we provide insights that can be used to decide whether sUAS or GPS techniques will be most efficient for post-flood surveying
At Underwood Creek, HWMs were identified along the margin of the flood on both banks by the color change caused by vegetation that had been laid down during the event and in some locations, by debris lines
Summary
Floods are largely uncontrollable phenomena that threaten infrastructure, property, and human life around the globe. 142,000 fatalities and over 656 billion U.S dollars in economic losses [1]. In Houston, Texas, for example, widespread inundation over large urban areas caused by Hurricane Harvey in 2017 resulted in damage totaling 130 billion U.S dollars [2]. As large floods have become more frequent and damaging over the past century in the U.S and around the globe [3,4], flood-magnitude data are critical for future flood prediction, understanding the risks to human health and safety, design of flood protection and critical infrastructure, and planning efforts to reduce the magnitude of losses due to flooding. Widespread flood extents are commonly assessed from high-water marks (HWMs) that indicate the Remote Sens.
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