Oliver E. J. Wing

TL;DR: This article used a 30 m resolution model of the entire conterminous US with a 2D representation of flood physics to produce estimates of flood hazard, which match to within 90% accuracy the skill of local models built with detailed data.

TL;DR: The authors used a 30 m resolution model of the entire conterminous US with a 2D representation of flood physics to produce estimates of flood hazard, which match to within 90% accuracy the skill of local models built with detailed data.

TL;DR: In this article, the authors developed a two-dimensional hydrodynamic model of the conterminous U.S. using only publicly available data and validated these simulations against the complete catalogue of Federal Emergency Management Agency (FEMA) Special Flood Hazard Area (SFHA) maps and detailed local hydraulic models developed by the USGS.

TL;DR: In this article, the authors report a new and significantly enhanced analysis of US flood hazard at 30m spatial resolution, which includes updated hydrography data, new methods to determine channel d...

TL;DR: The authors applied machine learning techniques and high-resolution population data to reinvestigate the impact of population distributions on flood exposure and showed that populations are generally represented as risk-averse and largely avoiding obvious flood zones.