# Investigation of Rain-On-Snow Floods under Climate Change
## 3 Results and Discussion
### Climate Change Scenarios
#### 3.2.1 Seasonality  
As a first step of the study, we investigated changes in the seasonality of the ROS floods due to the climate change. For this purpose, we applied the methodology shown in Section 2.4 where we investigated how the direction (i.e., day) of ROS floods and the strength of seasonality change. Figure 3 shows a few randomly selected examples of the seasonality characteristics of ROS floods for two selected case studies and for some GCM/RCM models. Circles of different colors indicate ROS floods that occurred in different periods from 1981 to 2100. Based on all ROS floods in a specific period we also calculated the resultant (i.e., mean) event. Results demonstrate that for the Soca River case study most of the events occur in autumn and a few of them also in spring (Figure 3). For the Gradascica River case study, the situation is a bit different because ROS floods are occurring from October to April and many events also occur in the winter period (Figure 3). In Slovenia, floods usually occur in autumn period, which was also shown by [31] who investigated flood characteristics of the Litija gauging station on the Sava River. A similar flood timing can also be found in neighboring countries such as Austria. For example, in [35] it was stated that in central and southern parts of Austria extreme flood events mostly occur in autumn. In [36], it was pointed out that largest floods occur in autumn in Carinthia (Southern Austria) and that strength of seasonality (r) is generally around 1. On the other hand, seasonality is less explicit for the Litija station on the Sava River [31]. Based on the selected five GCM/RCM models we also calculated median values for four investigated 30-year periods. The median values of strength of seasonality r for the 1981-2010 (i.e., baseline) period were 0.77 and 0.70 for the Soca and Gradascica case studies, respectively. Table 2 shows relative differences in the strength of seasonality compared to the baseline period for all three considered catchments. One can notice that for the Soca case study the strength of seasonality could decrease in the future, which could indicate a larger diversity in the timing of ROS floods. A similar conclusion can be made for the 2011-2040 period for the Gradascica River case study while for the 2041-2070 and 2071-2100 periods seasonality could be more explicit. One can also note that the changes are in the range of 15% (Table 2). For the Soca River case study, the median of the MD for the baseline period is in mid-October. Due to climate change, we could expect that the occurrence of the majority of ROS floods could shift by a few weeks towards the beginning of November (Table 2). Moreover, for the Gradascica River case study the median value of the MD for the baseline period indicates that ROS floods are the most frequent in end-December. We can conclude that climate change in case of the two considered catchments could in general lead to a somewhat different seasonal occurrence of ROS floods (i.e., a few weeks later) and that ROS floods could occur over a larger time span of the year, which could lead to a smaller strength of seasonality. The same climate-change-induced shifts in flood timings in the Balkan region were also reported by [37]. However, stronger seasonality in the future can be observed for some cases shown in Figure 3.  
Moreover, there are some differences among the investigated cases (i.e., GCM/RCM models) with respect to the number and seasonal timing of ROS floods (Figure 3). For example, for the baseline period for the Soca River case study, strength of seasonality r could vary from 0.53 to 0.82 with a median value of 0.77. Similar behavior can also be observed for the MD variable, which is in the range from 248 (i.e., start of September) to 298 (i.e., end of October) with a median value of 286 (i.e., mid-October). Similar conclusions can be made for other periods and the other case study where the difference among investigated cases can be more than 50%.