The study by Hanbeen Kim and Gabriele Villarini assesses the projected changes in flooding across the contiguous United States (CONUS) using outputs from 28 global climate models and four scenarios of the Coupled Model Intercomparison Project Phase 6. The findings indicate that CONUS is expected to experience an overall increase in flooding, particularly under higher emission scenarios. Subregional differences are observed, with the Northeast and Southeast showing a higher tendency towards increasing flooding, while the Northwest and Midwest exhibit a shift towards higher values. The study highlights the need for incorporating climate change into future infrastructure designs and water resource management to mitigate flood risks. The authors use a regression-based approach to project changes in flood magnitude, considering the dense network of streamgages and the dense network of thousands of streamgages by the U.S. Geological Survey (USGS). The results suggest that annual maximum peak discharge is projected to become more extreme, with a larger tendency towards larger peaks, especially for smaller return periods. The study also examines the role of seasonal climate drivers and the dependence of projected flood hazards on human-modified basins, emphasizing the importance of accounting for non-stationarity in flood frequency analyses.The study by Hanbeen Kim and Gabriele Villarini assesses the projected changes in flooding across the contiguous United States (CONUS) using outputs from 28 global climate models and four scenarios of the Coupled Model Intercomparison Project Phase 6. The findings indicate that CONUS is expected to experience an overall increase in flooding, particularly under higher emission scenarios. Subregional differences are observed, with the Northeast and Southeast showing a higher tendency towards increasing flooding, while the Northwest and Midwest exhibit a shift towards higher values. The study highlights the need for incorporating climate change into future infrastructure designs and water resource management to mitigate flood risks. The authors use a regression-based approach to project changes in flood magnitude, considering the dense network of streamgages and the dense network of thousands of streamgages by the U.S. Geological Survey (USGS). The results suggest that annual maximum peak discharge is projected to become more extreme, with a larger tendency towards larger peaks, especially for smaller return periods. The study also examines the role of seasonal climate drivers and the dependence of projected flood hazards on human-modified basins, emphasizing the importance of accounting for non-stationarity in flood frequency analyses.