<p>In the traditional flood frequency analysis, researchers typically assume the flood events result from a homogeneous flood population. However, actually flood events are likely to be generated by distinct flood generation mechanisms (FGMs), such as snowmelt-induced floods and rainfall-induced floods. To address this problem in flood frequency analysis, currently, the most popular practice for mixture modeling of flood events is to use two-component mixture distributions (TCMD) without a priori classification of distict FGMs, which could result in component distributions without physical reality or lead to a larger standard error of the estimated quantiles. To improve the mixture distribution modeling in Norway, we firstly classify the flood series of 34 watersheds into snowmelt-induced long-duration floods and rainfall-induced short-duration floods based on an index named flood timescale (FT), defined as the ratio of the flood volume to peak value. A total of ten types of mixture distributions are considered in the application of FT-based TCMD to model the flood events in Norway. The results indicate that the FT-based TCMD model can reduce the uncertainty in the estimation of design floods. The improved predictive ability of the FT-based TCMD model is largely due to its explicit recognition of distinct FGMs, enabling the determination of the weighting coefficient without optimization.</p>
Flood frequency analysis of Manas River Basin in China under non‐stationary condition
