## 3 Results and Discussion
As the failure wave moves along the river channel, it continuously changes its height, speed, width, and other parameters. The wave front separating the zones of water level rise and fall may be steep near the failed hydrodynamically hazardous object (HHO) and relatively flat at a considerable distance from it. The resulting model, using the small Kurchum River as an example, can be used to model and predict the flooding of entire river systems. In early March 2019, an analysis of data on the flood situation in the region was carried out and a preliminary forecast was made about the high probability of flooding in the Beskaragay district. This forecast was confirmed on 28 March 2019, when groundwater levels rose, and settlements in this area were flooded [34]. Figure 5 shows the results of the analysis of flooding of the territory near settlements in the region, carried out on the basis of actual data and modeling using the analytical system being developed. Figure 3: Wave crest propagation on the Kurchum River, using a MIKE model. Legend: the red line shows the water flow rate (in m\({}^{3}\)/s), while the blue line and light blue area show the water level (absolute marks in m). The horizontal axis shows the distance from the initial cross-section (SP), and the maximum value is about 400 km. (**a**) a sharp peak in flow (\(\sim\)2000 m\({}^{3}\)/s); (**b**) the peak of the outflow wave flow has shifted downstream and has also become less pronounced (\(\sim\)1400 m\({}^{3}\)/s); (**c**) further movement of the wave downstream is observed, the peak flow rate is already lower (\(\sim\)900 m\({}^{3}\)/s); (**d**) the flood wave has weakened significantly (flow rate does not exceed \(\sim\)400 m\({}^{3}\)/s); (**e**) the flood wave has almost completely weakened (the flow rate is minimal, less than \(\sim\)200 m\({}^{3}\)/s). Figure 5a shows the actual recorded flood zone based on observations for the period February-March 2019. The yellow areas correspond to the actual areas that were under water as a result of the flood. Figure 5b shows the simulated flood zone calculated using the analytical system. The pink areas superimposed on the yellow ones show intersections, i.e., coincidences between the actual and simulated data. The degree of coincidence of the simulated flood zones with the actually observed zones was calculated using the methodology described in Section 2 (Materials and Methods), resulting in 91.89% for 2019, 89.09% for 2020, and 95.91% for 2021. An analysis of the discrepancies between the model simulation results and the actual observed flood extents revealed several potential sources of error that could have influenced the accuracy of the predictions. One of the primary factors is the accuracy and resolution of the digital elevation model (DEM) used in the hydrodynamic simulations. The DEM was derived from Sentinel-2 data with a spatial resolution of up to 10 m and Sentinel-1 data with a resolution of up to 5 m. While these datasets provide high-quality elevation information for regional-scale studies, they may not capture small-scale topographic variations of the floodplain, such as local depressions, levees, or micro-relief features, which can significantly affect the extent of flooding, especially along the boundaries of the flood zones. Another important source of discrepancy arises from the input hydrological data. The model was forced using streamflow time series from gauging stations at the boundaries, but lateral inflows, local runoff, and contributions from ungauged catchments were not directly measured and could contribute to differences between simulated and observed flood extents. The calibration of hydraulic parameters, such as Manning's roughness  
Figure 4: Interactive map of flood dynamics (MIKE model). (**a**) Initial stage of flood wave propagation; (**b**) intermediate stage showing wave crest movement; (**c**) phase of maximum flood zone expansion; (**d**) final stage illustrating flood attenuation and recession.