Research questions related to a reliable estimate of flood discharges has always interested both hydrologists and civil engineers. Over the decades numerous methods have been proposed and used more or less successfully, all of them with known limitations restricting their use to a wide range of conditions and problems. In the past, the characteristics of hydrological extremes were mostly estimated by the methods of statistical analyses. As this type of methods is not suitable to estimate design discharges of high return periods, and by default does not account for uncertainty, a new family of methods is slowly taking place of the traditional approaches. Many of these methods are based on a combination of stochastic rainfall models (weather generators) and rainfall-runoff models, which enables to generate an arbitrary number of synthetic floods even in places with short or no records of river discharges available. In addition, as this type of methods produces flood hydrographs, they can also be used in a multivariate flood frequency analysis to estimate joint probabilities of two or more flood characteristics. This study presents a methodology for flood frequency analysis that combines stochastic models of both rainfall amounts and air temperatures with a lumped rainfall-runoff model to transfer the outputs of the stochastic models into a series of corresponding river discharges. Both of the stochastic models are single-site weather generators that produce continuous time series of mean areal daily rainfall amounts and air temperatures. In this study, the method was used to generate a time series of 10,000 years of mean daily discharges, which was used to build a flood frequency curve and to estimate extreme flood discharges of given return periods. The method was applied to a mountainous catchment of the River Váh in Slovakia.