Temporal Trends in Extreme Precipitation Events in Eight Flood‐Prone US Inland Cities (1981–2023)

Extreme precipitation is one of the leading drivers of hydrometeorological hazards and urban flood risk across the United States. However, most previous analyses focus on broad geographic scales, often obscuring the local variability and urban microclimate effects critical for understanding risk in metropolitan areas. This study investigates temporal trends in the frequency and magnitude of extreme precipitation events at the HUC12 watershed scale in eight flood‐prone inland US cities for 1981–2023. Gridded daily precipitation was extracted from the PRISM dataset. Extreme events were identified using the N‐largest and annual maximum methods, and trends were assessed using a Monte Carlo Simulation (MCS) framework. Multiple hypothesis testing across watersheds was addressed with the Benjamini‐Hochberg False Discovery Rate (FDR) correction. Results reveal substantial heterogeneity across cities, with Louisville, Springfield, Phoenix, Oklahoma City, and Kansas City showing statistically significant upward trends in extreme precipitation frequency and/or magnitude after FDR correction. Notably, Louisville displays widespread increases across most watersheds, indicating strong field significance. In many sites, clusters of significant trends suggest the influence of localized factors. Despite limitations with gridded data, these findings demonstrate that urban areas may be at increasing risk.