## 5 Discussion
This uncertainty (although the approach to their magnitude is different in both studies) is similar in magnitude to that obtained in the town of Navaluenga (Spain) by [PERSON] et al. [59], which was just above 40%. This uncertainty magnitude, associated with the flow frequency law, was found to be much higher than other sources of uncertainty, such as the damage model, or the hydrodynamic model's calibration [59]. The importance of the correct estimation of the flow frequency distribution function has been recognized previously as one of the main sources of uncertainty in the damage estimation associated with floods (e.g., [6,60]). However, other authors [61] obtained different results, where the flood damage model is the greatest source of uncertainty for correct flood risk assessment and management, much more than the peak flow frequency distribution. There is no unanimity in the hierarchy of the sources of uncertainty on flood risk assessments, and thus, other studies highlight the importance of other variables, such as the calibration of hydrological-hydraulic models [62], the influence of the quality of the topography [63] and even the correct estimation of the relative height of the main floor of the buildings with respect to the public road [64]. In any case, the results obtained in the present study, similar to those obtained previously by other authors [58], show the importance of correct estimation of the peak flow frequency distribution. All these uncertainty sources could develop into a lack of confidence in flood hazard and risk maps, therefore making flood risk management tasks more difficult. As we show with our results for Zamora city, uncertainty in peak flow value for a 500-year return period produces important differences in flood-prone areas and in the spatial distribution of flood hazard levels for human loss stability, as well as in direct economic damage for buildings and vehicles. The use of an easy, feasible approach by Monte Carlo analysis allows us to delimitate the uncertainty linked to flow frequency analysis and the absence of a complete knowledge of maximum annual peak flow distribution. This uncertainty, and the variability in the spatial distribution of flood-prone areas is also conditioned by the morphology of the terrain (slope), as can also be seen in our study area (Figure 6). Thus, the right bank of the Duero River, where the urban area of the city of Zamora is mainly developed, shows a steep slope, and the effect of this uncertainty in the estimation of the peak flow is less evident. On the contrary, the left bank, with a gentler slope and a better developed flood plain, shows more clearly the effects of uncertainty in the estimation of the peak flow, which is reflected in a greater spatial variability of the distribution of flood zones and flood hazard. Probabilistic flood maps could be a powerful tool in flood risk management since they allow the development of probabilistic Expected Annual Damage (EAD) curves, which in turn would allow better sizing of flood insurance policies. In the same way, the development of probabilistic EADs could improve any further cost-benefit analysis of flood mitigation measures, including self-protection. All this uncertainty reduction could make it possible to improve the homeowner involvement in terms of both participation and financial implications. Regardless, the homeowner's involvement in flood risk management is a hard task, firstly because residents consider flood protection to be an almost exclusive government responsibility [65], and secondly because the profit margin of insurance companies may be reduced due to the increased expenditure in the analysis and control of the self-protection measures implemented and the quality of materials used [66], which may limit the interest of insurance companies in these tasks. Human loss of stability analysis in Zamora city shows that if we do not take into account the uncertainty of the results, we are probably underestimating the high-hazard areas (Figure 5).