## 3 Methodology and Database
### Spatial Analysis
#### 3.3.1 Simulation 1  
The first simulation model was performed with the main purpose of assessing the general state of response of the ravine to the extreme event. The maximum flow simulation was performed in order to identify the main hotspots regarding the erosion power and in order to make decisions regarding the spatial identification of the locations for the implementation of hydro-amelioration works. Therefore, based on the spatial geometry databases and the unitary flow hydrograph implemented in the HEC-RAS program and through the unsteady flow data module, a simulation model was established, which generates spatial databases (flow velocity, stream power, shear stress), based on which decisions can be made to identify hydro-ameliorative sites (Figure 8A-D). The overall analysis of the three simulated parameters highlights the impact of the average flow on the analysed ravine. Therefore, we can observe the erosion of the drainage channel along its entire length (Figure 8C), as well as the high flow rate of the water in the main channel (Figure 8B). Regarding the shear stress (Figure 8D), it can be correlated with the maximum water depth at maximum flow (Figure 8A), obtaining high values of this indicator where large water depths are spatially identified. The general analysis of the ravine highlights three hotspots that concern the subsequent evolution of the analysed torrential process. The first hotspot is identified in Sector II and manifests itself over a larger area than in the depth of the erosion. The second hotspot is identified between Sector II and Sector III and is spatially identified with the first threshold, with highlights both in terms of deep erosion and in terms of banks lateral erosion. The third hotspot is spatially identified in Sector III, which is the lower sector of the analysed ravine and is also spatially identified with the second erosion threshold having a stronger effect on the deep erosion than on banks erosion. Regarding the general analysis of the ravine, here, the influence of the identified hotspots on the entire torrential area but also on the upstream and downstream sectors is highlighted. Thus, the upstream part of the ravine is characterized by a high erosion power and a high flow rate of water, both controlled by the first hotspot, which is (from the point of view of drainage) the transition between the ravine itself and the torrent's receiving basin. The surface is characterized by high slopes and incipient erosion processes (streams, gullies). The erosion power intensifies in the immediate vicinity of hotspot II so that it can be observed in the downstream, both a high erosion power and a high shear stress. This is mainly due to the water fall from approx. 3.2 m, correlated with a steep slope of the sector between hotspot 1 and 2, which also contributes to high runoff speeds in this area. Hotspot 3 is primarily influenced by the high slope of the upstream channel correlated with a small slope of the downstream sector. This favours the incipient spatial development through deep erosion of the threshold that overlaps spatially with this hotspot. The general analysis of the ravine highlights its accentuated dynamics in need of specific hydro-ameliorative and related works for the stabilization of the erosion processes. In order to identify the optimal spatial locations for the hydro-amelioration works, the longitudinal profile of the ravines riverbed was analysed, considering the water erosion power at maximum flow (Figure 9) correlated with the general condition of the analysed riverbed sectors. Figure 8: (**A**) Maximum depth; (**B**) velocity; (**C**) stream power; (**D**) shear stress. The analysis of the three hotspots has as its main purpose to identify the location of the hydro-amelioration works based on the analysis of stream power and the general condition of the ravine. This highlights the fact that from the erosion power point of view, hotspot 2 raises the biggest problems, thus identifying the greatest erosion in depth (Figure 9).