## 4 Results and Discussion
### Manning's \(n\) Value Calibration  
The Manning's \(n\) value calibration process was carried out first for the 500-year return period peak flow, and it was done in two steps. First, focusing on a cost-saving approach that would allow its application in places with very different socio-economic development, the calibration was carried out based on the results obtained in a series of cross-sections of the Douro River. At the location of each cross-section, a hydrodynamic model was generated and a best fit Manning's \(n\) value model was defined (Figure 1D). A non-homogeneous Manning's \(n\) value for each cross-section was found, which pointed towards the assumed hydrodynamic simplification when we use a homogeneous surface roughness coefficient for the whole river reach. This point is discussed later.  
From the different best fit Manning's \(n\) values of each cross-section, a mean value of \(n=0.015\) was obtained. However, given the non-homogeneous results obtained in the previous step, a second calibration phase was carried out.  
In this second phase, the hydrodynamic model was extended throughout the study area. The latter aspect favored the achievement of multiple objectives, such as the rapid comparison of results in the location of the river cross-sections that were used in the first calibration phase. However, it also allowed for statistical and geostatistical analyses of the results to be carried out to achieve a better understanding of them in such a way that one could finally obtain a selection, based on scientific criteria, of the hydrodynamic model based on the \"LiDAR scenario\" topography and the best value (or range of values) of Manning's n coefficient.  
As a complement to the above, the results obtained from two other models were analyzed. On the one hand, use was made of a model that presented a variable spatial distribution in the value of the roughness coefficient in the channel (obtained from the roughness values that offered a better adjustment relative to the control model, i.e., the \"real scenario\", for each point in the channel). On the other hand, a model with a roughness coefficient value of 0.027 was considered (similar to the control model), albeit with a reduced peak flow value (from 2274 to 2114 m\({}^{3}\) s\({}^{-1}\)) depending on the measured flow rate at the date of acquisition of the LiDAR data.  
The calibration, optimization and validation of the parameters in the models require having observational elements of calibration, such as the existence of a gauging station with its available stage-discharge curve in the case of the hydraulic models [54,55]; the existence of stage water plaques of historical floods with a known peak flow value; or other types of high-water marks, such as paleo-hydrological evidence (slackwater deposits or dendro-geomorphological floods [56]). In addition, it is not sufficient to have a single element for calibration because different combinations of parameters can give convergent results at one point; rather, multiple points are needed to adjust them, and these are not always available [28]. In fact, as pointed out by [PERSON] et al. [43], the availability of observational elements of calibration is not possible in many cases.  
However, the readjustment of compensation between parameters, which is the strategy followed in this work, made it possible to compensate for the deficiencies in bathymetry by readjusting the roughness in a relatively simple way that was applicable to any section or situation, whether or not there were calibration elements.  
In short, the methodological approach adopted, although it can be complemented with other approaches, is an innovative strategy that can substantially improve hydrodynamic models, hazard analyses, risk assessments and, finally, the effectiveness of flood risk mitigation measures. Evidently, this was all done in places where there was no bathymetric information and where such information could not be obtained, and only for the floodplain, not for the river channel.