## 4 Results and Discussion
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Integrity** & \\ \hline
**Product** & **Advantage** & **Disadvantage** \\ \hline DMR 3.5 & coverage of complete territory & high purchase costs \\ DMR 5.0 & coverage of part of territory & high purchase costs \\ Classic surveying & detailed local measurement & high purchase costs \\ (GNSS-RTK) & & \\ \hline \hline \multicolumn{3}{c}{**Logical Continuity**} \\ \hline
**Product** & **Advantage** & **Disadvantage** \\ \hline DMR 3.5 & coverage of complete territory & insufficient linking objects with attribute \\ DMR 5.0 & linking objects with attribute database & database; \\ Classic surveying & addressing/targeting for specific study & absence of descriptive information on monitored \\ (GNSS-RTK) & addressing/targeting for specific study & group of objects; \\  & & problems with interoperability \\ \hline \hline \multicolumn{3}{c}{**Positional Accuracy**} \\ \hline
**Product** & **Advantage** & **Disadvantage** \\ \hline DMR 3.5 & any & not homogeneous accuracy over the entire \\ DMR 5.0 & high accuracy & territory of the country \\ Classic surveying & high accuracy & poor quality classification of cloud points \\ (GNSS-RTK) & high accuracy & time-consuming measurement in the large \\  & & territories \\ \hline \hline \multicolumn{3}{c}{**Temporal Accuracy**} \\ \hline
**Product** & **Advantage** & **Disadvantage** \\ \hline DMR 3.5 & documentation of spatial data in real time & use of outdated map documents \\ DMR 5.0 & current data with possibility of regular updating & restriction of period for spatial data collection \\ Classic surveying & (e.g., vegetation, clouds) \\ (GNSS-RTK) & fast response times for local measurement & unsuitability for global measurement \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The assessment of qualitative parameters of DMR according to their significance. Figure 12: Cross-section of selected part of area for a comparison of height differences. (a) river km 60.4; (b) river km 57.9. The following results were arrived at by means of the evaluation of these parameters (Table 4). The majority of DMR quality parameters could be assessed only based on practical experience in the area concerned. The legislation in the Slovak Republic does not specify them in detail. For the assessment of the qualitative aspect of input data in the hydrodynamic model is in many scientific studies suggested the importance given to the hydrological and hydraulic part [68]. We noticed that the authors such as [69; 70] present a consensus view that the input parameters and their uncertainties affect modeling results mainly in the extent of inundation area and water depth. As in scientific work [68], our study uses a 1D-hydraulic model to monitor and map the extent of inundation areas. The diversity of land-use patterns in inundation areas means that the roughness in the hydrodynamic modeling process is one of the important parameters that have a significant impact on the outcome [67]. Among the basic types of uncertainty, the work [70] mentions the shape, width, and roughness of the canal and the watercourse. Given the overall assessment of the situation, we can state that the roughness coefficients recommended in [61; 62] are underestimated for the current state of watercourses in Slovakia. This is confirmed by the results of professional work [71] and the practical experience of water managers. The data used as N annual flow rates create a high degree of uncertainty in hydrodynamic models. N-year flow rates used by us belong to the 4 th class of reliability of hydrodynamic data by the STN 75 1400: 2008 ([[https://www.sutn.sk/eshop/public/standard_detail.aspx?id=104840](https://www.sutn.sk/eshop/public/standard_detail.aspx?id=104840)]([https://www.sutn.sk/eshop/public/standard_detail.aspx?id=104840](https://www.sutn.sk/eshop/public/standard_detail.aspx?id=104840))). As mentioned in [72], flow parameters of higher reliability are inevitable for hydrodynamic modeling.