## 1 Introduction  
Debris flows are characterized as one of the most dangerous and least predictable types of landslides [1; 2]. Following certain natural disasters, flow-type landslides frequently occur. In Serbia, numerous such events occurred in 2014 due to the Tamara cyclone effect. Specifically, over 200 flow-type landslides were recorded in the western part of Serbia, with many others identified indirectly through satellite image analysis [3; 4]. Many of these incidents were unexpected, even in areas designated as relatively stable according to hazard maps. Some cases were particularly complex, involving both sliding and flowing processes and a significant volume of material, rendering them challenging for numerical modeling. Various runout methods have been developed over time, ranging from empirical relationships between runout and landslide initial characteristics [5], to analytical methods [1; 6; 7; 8], and finally to dynamic and complex numerical methods [9; 10; 11]. The complexity of modeling lies in the consideration of numerous input parameters, including the appropriate rheology law, accurate depth of the source area, entrainment parameters, and the definition of geotechnical parameters such as porosity, friction coefficients, and the variation in pore water pressure over time and space [12; 13]. Some software is designed for ease of use but is also continuously developed and improved to enhance numerical capabilities in line with the needs and complexity of real-world scenarios. In cases involving large deformations, large-scale phenomena, and hazard prediction, propagation models (runout models) have proven to be highly effective. After identifying unstable areas where mass flows are likely to occur, current programs utilizing dynamic numerical models are used to predict flow patterns and pinpoint potential impact zones. Today, numerous numerical models are available for risk assessment and runout analysis, and selecting the most appropriate simulation code has become a significant concern due to advances in computational technology. Running multiple simulations to predict specific events or conducting a detailed back-analysis can be valuable. This approach enables a comparison of numerical outcomes, helps identify key differences, and allows for a more precise assessment of potential risks. However, beyond the capabilities of the chosen simulation code, various other factors--such as the presence of erosion and the accurate definition of parameters--can greatly influence the results. RAMMS is widely utilized for back-calculating models of avalanches and debris flows. Its inclusion of entrainment calculation has been thoroughly tested in study areas [14]. The model operates in 2D, tracking the changing volume over time using Voellmy rheology, a method commonly employed in debris flow modeling. The initial models for this study area were developed using RAMMS, facilitating the straightforward determination of certain input parameters. This involved utilizing terrain data with a resolution of \(5\times 5\) m (presented here are the final models based on this resolution DTM) and identifying zones of potential maximum erosion depth. For accurate interpretation, detailed field characterization of the cases being modeled was essential. These study areas were delineated through various field research methods: Electrical Resistivity Tomography (ERT), detailed UAV scanning of the wider area to generate post-event orthophotos, and a DTM with a 5 cm resolution. Additionally, laboratory tests were conducted to analyze granulometry and consistency across different samples. SPH (Smoothed Particle Hydrodynamics) is a meshless method utilized across various fields. Geoflow SPH, proposed by [10], has been implemented and tested over the years on numerous cases [10; 15; 16], including different scenarios and flume tests. For the first time in this study, the extraction of the source area from the topographical model was employed to enhance the accuracy of entrainment calculation.