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Understanding the spatial variability of key parameters of flood probability distributions represents a strategy to provide insights on hydrologic similarity and building probabilistic models able to reduce the uncertainty in flood prediction in ungauged basins. In this work, we exploited the theoretically derived distribution of floods model TCIF (Two Component Iacobellis and Fiorentino model; Gioia et al., 2008), based on two different threshold mechanisms associated to ordinary and extraordinary events. The model is based on the hypotheses that ordinary floods are generally due to rainfall events exceeding a constant infiltration rate in a small source area, while the so-called outlier events responsible for the high skewness of flood distributions are triggered when severe rainfalls exceed a storage threshold over a large portion of the basin. Within this scheme, a sensitivity analysis was performed with respect to climatic and geomorphologic parameters in order to analyze the effects on the skewness coefficient and provide insights in catchment classification and process conceptualization. The analysis was conducted to investigate the influence on flood distribution of physical factors such as rainfall intensity, basin area, and particular focus on soil behavior

Influence of infiltration and soil storage capacity on the skewness of the annual maximum flood peaks in a theoretically derived distribution