The present study focuses on quantifying the impact of the choice of spatio-temporal resolution and hydrology models on the projection of extreme flow and their link to the catchment size. We use two process-based distributed hydrology models forced with a large-ensemble regional climate model (50-member ClimEx dataset) over the 1990-2100 period at different spatio-temporal scales. The extreme summer-fall flow corresponding with each spatio-temporal resolution was extracted by pooling the members together and computing the empirical cumulative distribution function. The results show that by refining the time-step from daily to sub-daily, the summer-fall extreme flow projected over the future period exceeds that of the reference period for the small but not large catchments. By increasing the catchment size, the hydrology model’s contribution to the variability of extreme flow increases. Moreover, the choice of spatial resolution affects the extreme flow’s trend in terms of magnitude, significance, and direction. But no pattern regarding the catchment size and spatial discretization variations exists.