Drivers of flash flood frequency and intensity in the United States: a quantitative analysis of hydrometeorological interactions
Abstract
Abstract. Inconsistent changes in precipitation and flooding have spurred investigations into the underlying mechanisms, yet the quantitative understanding of interactions between precipitation, temperature, and land cover in streamflow dynamics remains limited. We investigate streamflow changes in 294 small and medium-sized catchments across the contiguous United States (CONUS), using over 30 years of sub-daily data from the USGS river-watching network. We find that 17.3 % of catchments exhibit significant increases in flash flood frequency, and 6.5 % show significant increases in flashiness, while the majority experience no substantial changes. Despite a 67 % increase in sub-daily heavy precipitation frequency, only 23 % show flood frequency increases, indicating complex catchment-specific hydrometeorological interactions. To quantify the contributions of precipitation, temperature, and land cover changes, we employ a novel time-space varying distributed unit-hydrograph (TS-DUH) model integrated with the DRIVE hydrological model and random forest regression. The results reveal that land cover changes across the CONUS have remained stable over the past four decades, with 90.8 % of catchments showing minimal flow change (within ±3 %) from 1985 to 2015. Precipitation emerges as the primary driver of streamflow changes, but rising temperature and evapotranspiration mitigate this effect, with simulations showing a 3.6 % reduction in flood frequency and an 8.0 % reduction in flood intensity since the 1980s. Additionally, our results show 10 % increase in impervious surfaces could lead to 20 % peak flow increase, highlighting the importance of urbanization in flood risk. These findings enhance the understanding of spatial-temporal variation in flash flooding, providing crucial insights for better flood hazard mitigation strategies.
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Authors: Ying Hu, Huan Wu, Yiwen Mei, Zhijun Huang, Aihui Wang, Chaoqun Li, Bing Sui
Institutions: Chinese Academy of Sciences, Sun Yat-sen University, Nanjing University of Information Science and Technology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Institute of Atmospheric Physics