Nonstationarity due to climate variation and anthropogenic disturbances has altered high flow regimes. However, the extent of change has not been evaluated for undisturbed versus disturbed watersheds. This article aimed to determine how partitioning watersheds into undisturbed and disturbed categories can improve the performance of probability distributions for flood analysis throughout the United States. We utilized peak flow information for 26 reference (undisturbed) and 78 nonreference (disturbed) watersheds with drainage areas ranging from 135 to 42,367 km2 and record lengths of 100 to 140 years. Results indicated that flood quantile estimates of the Log Pearson Type III (LP3) distribution were likely being overestimated for return periods of 2 to 10 years, while flood estimates of 50 years and higher might be underestimated. In contrast, the Generalized Extreme Value (GEV) distribution outperformed LP3 in estimating floods with return periods of 50 years or more. These findings enhance flood frequency analysis and forecasting under nonstationary conditions.
