## 5 Conclusions  
The present manuscript shows a new approach for improving flood hazard maps where bathymetric data are not available (or they are scarce, such as a few cross-sections for the whole river reach). The proposed solution to this unavailability of bathymetric data is valid for river floodplains but not inside the river main channel. Unlike the approaches based on the generation of simplified bathymetric shapes, or the hydraulic corrections (HDCM model), the proposal of this manuscript was based on the calibration of the Manning's \(n\) value (roughness surface index). This calibration point toward the use of abnormally low values for a natural channel sought to compensate for the reduction in the channel cross-section area using an increase of the flow velocity in the channel itself. The main conclusions that can be derived from this study are as follows:  
* The results obtained show a clear improvement when compared to the direct use of LiDAR topographic information combined with a Manning's \(n\) value according to the characteristics of the river channel studied. The results from the methodological developed model (500-year return period peak flow) and the methodological testing model (100-year return period peak flow) converged toward a range of [PERSON]'s \(n\) values from 0.014 to 0.016, which is far from the 0.027 that is selected based on the Douro River reach characteristics. A slight uncertainty in the best range of the Manning's \(n\) value was seen depending on the magnitude of the peak flow rate used. The magnitude of the peak flow rate and the optimal Manning's value show an inverse relationship. * For the case of the Douro River in Zamora, the results of the hydrodynamic modelling under the \"LiDAR scenario\" and the \"natural\" Manning's \(n\) value conditions (\(n=0.027\)) caused average errors of 50-75 cm in the flow depth estimation. By calibrating the Manning's \(n\) value, these average errors could be reduced to a value close to 10 cm. * By transferring the errors in flow depth to the estimation of direct damage due to floods (based on the widely used USACE damage magnitude model), we achieved a reduction in the error in the percentage of damage from values of 25-30% to errors close to 5%. The results of the calibration of the [PERSON]'s \(n\) value for the 500-year return period peak flow showed that the best fit varied according to the distance from the riverbank such that we could select different values of n (within a range between 0.011 and 0.014) depending on whether the area of greatest interest (in the hazard assessment) was close to the channel (lower value of n) or far from it (higher value of n). In any case, this implied the use of values of approximately half those used in real conditions. In the case of the 100-year return period peak flow, the best option of Manning's value for areas far from the riverbank went up to 0.016. A uniform [PERSON]'s \(n\) value (for the river channel) was used both for the control \"real scenario\" and for each Manning's \(n\) value calibrated model. However, a spatially distributed Manning's \(n\) value was used too, and the results, although good, did not significantly improve on those obtained in the constant value models. In fact, it was observed that this model offered better results for distances up to 550 m from the riverbed, but at greater distances, the results worsen. A hydraulic approach, namely, the HDCM, was also used, but the results were far from satisfactory. In fact, the results associated with this model were among the worst of those obtained in the present study. This situation calls into question the usefulness of this approach as a solution to the absence of bathymetric data in cases where the flow rates (on the date of acquisition of the topographic data, and those associated with the study) are very different.