A model-based approach is implemented to attribute changes in the seasonal extreme river flows to meteorological drivers. A semidistributed model that simulates daily runoff from daily series of meteorological variables was employed together with a multisite, multivariable weather generator. Ensembles of synthetic meteorological variables were synthesized using the weather generator and were used to drive the hydrological model. In order to systematically assess the relative importance of each of the meteorological variables in explaining the detected changes in the flood behavior, the variables were generated by accounting for the year to year variability of the distribution of one of the variables at a time while keeping the distributions of the others temporally stationary. The approach was tested on eight case study catchments from different parts of Germany. The results show the ability of the approach in identifying the meteorological variable that is associated with the detected change in the extreme flow. Changes in precipitation were found to be the major meteorological drivers of the trends detected in the seasonal extreme flows in most of the investigated catchments. Temperature was found to be less important in explaining any of the changes in all catchments.