Regional flood frequency analysis at multiple durations: A comparison of duration consistency in quantile and parameter regression techniques

This study compares two regional flood frequency analysis (RFFA) approaches—the parameter regression technique (PRT) and the quantile regression technique (QRT)—in the context of retention-based hydrologic applications, which require consistent design flood estimates across durations. Using a moving-window approach to estimate average streamflow over fixed durations, we assess whether predicting distribution parameters (PRT) or quantiles directly (QRT) affects the accuracy and duration consistency of flood estimates at ungauged locations. Both methods show similar predictive accuracy at return periods up to 50 years. However, the PRT more reliably preserves duration consistency: at 32 stations, the QRT produced inconsistent estimates at return periods beyond 2 years, while the PRT did not. These inconsistencies were not explained by record length or catchment characteristics. Additionally, at 64 of 239 stations, out-of-sample estimation of the median (index) flood was duration-inconsistent, suggesting difficulties in differentiating between the order of magnitude of floods across durations. Such inconsistencies were not observed in the spread and shape parameters estimated by the PRT. A quantile-based reparameterization of the generalized extreme value distribution was used to align both methods around the median flood, making it easier to compare how the methods behave across durations.