## 4 Results and Discussion
### Local Results at Cultural Heritage Sites in Zamora (Spain)  
Beyond the results of the overall study area (with or without riverbank distance dependence), some control points (Figure 8) that are linked to different housing types in Zamora city were used for the result quality analysis of the [PERSON]'s-\(n\)-value-calibrated models. Four control points were selected, representing different types of buildings in the vicinity of the city of Zamora. Checkpoints 1 and 3 represented buildings in an urban environment with a high building density, checkpoint 2 corresponded to a cultural heritage site (chapel) and, finally, checkpoint 4 corresponded to a house that was isolated among agricultural fields. In all cases, the absence of bathymetric data in the peak flow hydraulic modelling implied a flow depth overestimation ranging from 50 to 75 cm, where no process of artificial modification of the [PERSON]'s \(n\) value (calibrated model with \(n=0.027\)) was carried out. These flow depth errors could be drastically reduced through the [PERSON]'s \(n\) value calibration process, as shown in Figure 8. However, as was also observed previously, the results obtained at the four control points did not show complete homogeneity. Again, the range of values between 0.010 and 0.014 seemed to show the best results overall. However, depending on the spatial location of the control point, it was observed that values lower than 0.010 could also give optimal results, but values higher than 0.014 did not. The selection of only four locations may not be representative for the whole study area, and the previously exposed results (where the best fit was obtained for the [PERSON]'s \(n\) value ranging between 0.014 to 0.016) had greater confidence, but they were illustrative of the overestimation of flow depth in the absence of bathymetric data without some kind of calibration process. By transferring these differences in flow depth to the analysis of direct economic damage caused by floods, they can lead to significant differences in damage estimates. Thus, based on a widely used magnitude-damage model [15], we found that a difference  
Figure 8: Local Manning’s \(n\) value calibration results at control points in Zamora city. The upper and lower graphs show flow depth values for each calibrated model, where the red line shows the flow depth value for the control model, i.e., the “real scenario”. in the flow depth of 50-75 cm could lead to a variation in the direct damage estimates of 25-30%. From the same model, we could estimate that, if we associated an average error of 10 cm with the calibrated model with \(n=0.014\), the error in the damage estimate would be around 6%. These percentages of economic direct damage can vary depending on the non-linearity of the distribution of flood damage associated with the flow depth value, as well as the damage model used. [PERSON] et al. [67] pointed out that the resulting uncertainties in estimated damage (due to different models) are in the order of magnitude of a factor of 2 to 5. Furthermore, from the results obtained, it can be seen that the use of a reduced or lower (relative to that which is naturally associated with the characteristics of the riverbed) Manning's \(n\) value between 0.011 and 0.016 could lead to an error in the estimation of the flow depth that was no more than 25 cm, which, transferred to the estimation of direct damage, meant an approximate damage value error of 12%. Therefore, the use of an artificially lower Manning's \(n\) value could reduce the error in estimating flood damage by half. Therefore, this can be an interesting starting point for the improvement of flood damage estimates in areas without bathymetric data availability (even taking into account the fact that obtaining bathymetric data will always be the best option to achieve the best results). Furthermore, it could serve to carry out hazard analyses and, therefore, more personalized risk analyses depending on the elements at risk to be analyzed and their distances from the riverbanks.