## 3 Hydrodynamic/Hydraulic Modeling  
To assess the quality of 3D spatial data, the 1-D hydrodynamic model HEC-RAS was directly selected. Hydrodynamic model was created with using software product HEC-RAS (version HEC-RAS 5.0.7). The hydrodynamic model was established from a set of files presenting the topographic data of the watercourse, the berm, and the zones behind the shore line, raster data presenting DMR and hydrological data presenting hydrological conditions in the given area, which were prepared in the program ArcGIS (HEC-GeoRAS extension). The process of hydrodynamic modeling demonstrates the sensitivity to input data. The entire group of spatial data entering this process affects the expected result through the standard of its qualitative level. Interpretation of the hydraulic results is based on a geodetic survey and passportization of the watercourse, DMR, and other parameters such as surface roughness values and boundary conditions. The roughness values (Manning's roughness) were determined according to the applicable roughness coefficients based on valid methodologies [PERSON] (2016) and [PERSON] (2016). Roughness values determined according to the characteristic parameters of the given flow: material, surface, cross-section, obstacles, vegetation, meanders were received separately for each trough profile. 1D hydrodynamic models of the steady and unsteady flow use these values to calculate the hydraulic characteristics of individual profiles ([PERSON] _et al._, 2017). Given the fact that in the period under review (year 2010) were not directly mapped roughness, we proceeded to the modeling of constant determination of [PERSON]'s roughness values for the trough of the watercourse, berm, and the zone behind the shore line. The roughness values for the trough were in the range (\(n\) min = 0.03, \(n\) normal = 0.04, \(n\) max = 0.05), and based on the recommendations of water managers, the roughness value for the trough \(n\) = 0.04 entered the hydrodynamic calculation. The berm and the zones behind the shore line had a roughness value of \(n\) = 0.05 (Figure 8). The constant selection of the roughness coefficient for all profiles also reflected the fact that the watercourse channel was under-maintained in the monitored time. The model was calibrated by adjusting the Manning Roughness coefficient based on available records of previous floods. We achieved a match of modeled and critical flow from the course of flood activity in the given territory in 2010. The model was validated based on the extent of the flood in 2010 and the extent of the inundation area according to the flood hazard maps. The values of observed flows Q\({}_{10}\), Q\({}_{20}\), Q\({}_{50}\), Q\({}_{100}\) were determined as the result of long-term observation of the state of the stream-gauging station located within the area of interest. The values of the observed N-year levels of flows have a variable character in the modeling process. These were measured values. This data is exclusively provided by SHMI, which also guarantees their accuracy. It should be stressed that the determination of N-year flow rates in individual profiles can in many cases be a problematic aspect, mainly due to the long-term observation of these flow rates. Boundary conditions describe the interaction between the simulated system and its surroundings. For our simulation steady flow data was necessary to enter conditions on the upper edge of the river network. We chose the condition normal Depht \(4\times 10^{-4}\).