Alluvial (torrential) fans, especially those created from debris-flow activity, often endanger built environments and human life. It is well known that these kinds of territories where human activities are favored are characterized by increasing instability and related hydrological risk; therefore, treating the problem of its assessment and management is becoming strongly relevant. The aim of this study was to analyze and model the geomorphological aspects and the physical processes of alluvial fans in relation to the environmental characteristics of the territory for classification and prediction purposes. The main geomorphometric parameters capable of describing complex properties, such as relative fan position depending on the neighborhood, which can affect their formation or shape, or properties delineating specific parts of fans, were identified and evaluated through digital elevation model (DEM) data. Five machine learning (ML) methods, including a hybrid Euler graph ML method, were compared to analyze the geomorphometric parameters and physical characteristics of alluvial fans. The results obtained in 14 case studies of Slovenian torrential fans, validated with data of the empirical model proposed by Bertrand et al. (2013), confirm the validity of the developed method and the possibility to identify alluvial fans that can be considered as debris-flow prone.

In this paper, debris-flow modeling is shown specifically on the basis of a potential debris flow from the Hrenovec torrential watershed above the village of Kropa in NW Slovenia. This site was chosen, because in this particular torrential watershed a small surficial landslide turned into a debris flow during a storm on September 18, 2007. Fortunately, the debris flow stopped inside the torrential channel above the village of Kropa. Using public available data on rainfall and topography, we developed two scenarios of debris-flow triggering with an estimated magnitude of 50,000 m3. According the first scenario, a debris flow triggers during rainfall with the 100-year return period, and according the second one, it triggers during extreme rainfall as measured during the storm on September 18, 2007. For both scenarios, we used for debris-flow modeling a commercial two-dimensional mathematical model Flo-2d. The obtained results are shown in the form of computed flow depths and velocities over a cartographic background. The results show to possible catastrophic consequences in the village of Kropa, much worse that set in by torrential flood during the storm on September 18, 2007.