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Summary: In the general context of field experiment design, this paper presents a modeling study that quantifies the respective impact of rainfall estimation and soil variability on the simulated discharge for an extreme event in southern France. The CVN distributed hydrological model, built within the LIQUID® modeling platform is used. The method is illustrated for two medium sized catchments, Saumane (99km2) and Uzès (88km2) using raingauges and two radar estimates. The soil properties are extracted from an existing soil database provided for the whole region. The model parameter specification uses available observation and a priori hydrological knowledge. No parameter adjustment is performed. For model evaluation on the regional scale, simulated maximum peak discharges are compared with post-flood estimations for 32 catchments. The area of these catchments ranges from 2.5 to 99km2 and model results are satisfactory. Then, the study focuses on the Saumane and Uzès catchments. A sensitivity analysis highlights the role of the Manning roughness coefficient on the simulated hydrographs dynamics. The impact of the bottom boundary condition of the infiltration and water redistribution module is also shown for the gauged Saumane catchment. Then the impact of rainfall input and soil spatial variability is presented. The results show that (i) the use of radar data is necessary to properly simulate the flood dynamics; (ii) although radar volume-scanning strategy has been shown to give more accurate results on a pixel/gauge comparison of the rainfall estimations, it is not necessarily the case when catchment averaged amounts are considered, especially for catchments in mountainous areas; (iii) the impact of the variability in soil properties on the simulated discharges is of the same order of magnitude as the impact of differences in rainfall estimation; (iv) the flood dynamics presents two phases: the first one, mainly controlled by the soil properties and the second one, since the soils are saturated, controlled by the rainfall variability. Therefore, uncertainties on both observations need to be mitigated in order to improve flash-flood understanding. [Copyright &y& Elsevier]