Floods are major natural disasters that, in several occasions, can be responsible for life losses and severe economic damages. Flood forecasting and alert systems are needed to anticipate the arrival of these events and mitigate their impacts. They are particularly important for risk management and response in the nowcasting of flash floods. In this case, precipitation fields are crucial and is important to consider uncertainties coming from the observed precipitation fields used as input data to the system. One approach to take into account these uncertainties is to generate an ensemble of possible scenarios of observed precipitation. The aim of this study is to investigate the potential of a framework that applies a geostatistical conditional simulation method to generate an ensemble of precipitation fields that can be used as input to a distributed rainfall–runoff model to produce probabilistic flood alert maps. The Var region (southeastern France) and 17 events are used to validate the approach. Results show that the proposed method can be useful to generate realistic precipitation scenarios and, ultimately, to provide information on the probabil- ity of discharges exceeding critical flood thresholds. It can be a solution to combine information from radar fields and rain gauges to generate precipita- tion ensembles and quantify uncertainties in input data for hydrological modelling.