## 6 Conclusions  
Probabilistic flood maps arise as a valuable option to improve flood hazard and risk assessment and management, as they include the uncertainty associated to all of those analyses. In Zamora city (Spain), probabilistic maps were developed with the aim of considering the uncertainty linked to flood frequency analysis, which were calculated from the Monte Carlo method and quantified at around 40% (similar to the previously quantified value in Navalutenga in central Spain, but derived from a different approach).  
The flood frequency analysis result uncertainty will be propagated through the hydrodynamic model to the flood-prone area extension and the spatial distribution of flow parameters (depth and velocity), as well as the flood hazard of human loss of stability and vehicle damage.  
The results of Zamora city point towards some key points. First, how the terrain surface shape (mainly slope distribution) may increase or reduce the effect (flood-prone area extension) of peak flow uncertainty, so this uncertainty produces few changes in the flooded areas on the right bank of the Duero River, while such changes are much more noticeable on the left bank, with its gentle slope and extensive development of the floodplain.  
Furthermore, the changes in flood-prone areas and flood hazard levels of human loss of stability and vehicle damage are not uniform, and they are not equally distributed for all hazard levels. From our results in Zamora, we conclude that changes produce a noticeable increase in the extension and spatial distribution of higher flood hazard areas (which increase around 20% when we compare the results for the quantile and 99% confidence interval), whereas all other hazard levels show a downward trend.  
Finally, all the results for Zamora city draw different probability scenarios about flood hazard, which allow flood risk managers to improve urban-use planning from a flood risk point of view. So, managers could define the spatial distribution and restriction of vehicle parking from the probability that one street shows high hazard for vehicle instability (and the probability that those conditions occur), or improve the evacuation paths for the population living in areas where hazard to human loss of stability is higher too. The making of all these decisions by risk managers (who may be politicians who do not have a deep knowledge of flood dynamics) will be facilitated by the availability of this type of probabilistic mapping in which, in a simple way (from a colour scale), one can observe the distribution of the hazard in the urban city environment.  
All authors have a significant contribution to final version of the paper. Conceptualisation, J.G.; probabilistic flood maps analysis, J.G. and E.P.; writing--original draft, J.G. and A.D.-H.; writing--review and editing, all authors. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the project DRAINAAGE, CGL2017-83546-C3-R (MINECO/AEI/FEDER, UE), and it is specifically part of the assessments carried out under the coverage of the sub-project DRAINAAGE-3-R (CGL2017-83546-C3-3-R).  
The authors would like to thank [PERSON] (MNCN, CSIC) and the Duero River Water Authority (CHD), who provided us with the bathymetric data from Zamora city and its surroundings.  
The authors declare no conflict of interest.