In view of climate change, multiple studies predict a rise in the frequency of wet snow avalanches relative to dry snow avalanches. This should be taken into account in future avalanche hazard mapping, as using numerical models without considering specific snow types may lead to less accurate results in many cases. Reliable and predictive dynamical numerical models require extensive validation with real-world observations. However, such data are often lacunose or, at best, approximative, significantly reducing the accuracy of models’ validation and hindering their development. Additionally, model parameters must consider the snow and avalanche type. In Slovakia, the Centre for Avalanche Prevention of the National Mountain Rescue Service (HZS) has, in recent years, collected detailed information on avalanche events and runout zones, including drone photogrammetry and, in some cases, even live video footage from webcams. This allowed us to apply the TRENT2D* model to perform reconstructions of two events recorded in the Žiarska Valley, Western Tatras, Slovakia, one from April 2023 and one from January 2024. Both events share the same avalanche path, called Prìslop, have similar volumes, but have a significant difference: the first event resulted from a wet slab that released when the flow from liquid water, caused by prolonged warming, weakened the bond with the ground, the second was a dry slab that fell in subzero temperatures and slid on top of a hard layer. This difference is deeply reflected in the nature of the deposit and more importantly in the dynamic behaviour in the avalanche track and runout zones. Indeed, the two events required significantly different model parameters due to the difference in snow type – wet in 2023 and dry in 2024. In light of the obtained results, we will suggest that, in the future, it would be beneficial to veer towards a methodology for avalanche mapping that separately considers wet and dry occurrences before overlapping the results to represent in the maps the overall hazard.