## 5 Discussion  
Conceptually, all flood hazard and risk maps are probabilistic, although classical maps are sometimes referred to as \"Deterministic Flood Maps\" [47]. As these are not representations of tangible objects or strictly deterministic variables (as they are in a topographical, geological or vegetation map), the elements and immaterial variables represented (hazard or risk) are of a potential future nature and, therefore, stochastic. This stochastic component can be derived both from the hydro-meteorological methods of estimating flood discharges \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Damage Model** & **Hazard Level** & **Quantile** & **50\% CI** & **80\% CI** & **90\% CI** & **99\% CI** \\ \hline \multirow{4}{*}{[PERSON] et al. (2012)} & Level 1 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\  & Level 2 & 45.45 & 42.35 & 41.14 & 40.51 & 35.38 \\  & Level 3 & 2.95 & 3.35 & 3.09 & 2.63 & 2.16 \\  & Level 4 & 51.59 & 54.30 & 55.78 & 56.86 & 62.46 \\ \hline \multirow{4}{*}{[PERSON] et al. (2013)} & Level 1 & 34.85 & 33.37 & 33.24 & 30.99 & 27.29 \\  & Level 2 & 1.90 & 1.12 & 1.00 & 0.87 & 0.39 \\  & Level 3 & 0.61 & 0.68 & 0.57 & 0.48 & 0.25 \\  & Level 4 & 0.80 & 0.72 & 0.55 & 0.60 & 0.33 \\  & Level 5 & 61.85 & 64.11 & 64.63 & 67.05 & 71.73 \\ \hline \multirow{4}{*}{USACE (2003)} & \(<\) 5\% & 0.00 & 0.00 & 0.01 & 0.01 & 0.02 \\  & 5-10\% & 0.86 & 0.51 & 0.68 & 0.33 & 0.40 \\  & 10-25\% & 26.30 & 24.24 & 22.76 & 21.89 & 19.17 \\  & 25-50\% & 58.48 & 56.07 & 50.18 & 49.03 & 44.11 \\  & 50–75\% & 14.36 & 19.19 & 26.37 & 28.74 & 36.29 \\  & 75–100\% & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\ \hline \multirow{4}{*}{JRC—[PERSON] et al. (2017)} & \(<\) 5\% & 1.19 & 0.85 & 1.11 & 0.55 & 0.66 \\  & 5-10\% & 3.01 & 3.21 & 2.94 & 2.60 & 1.96 \\  & 10-25\% & 13.56 & 11.80 & 11.08 & 11.29 & 9.59 \\  & 25–50\% & 29.36 & 28.47 & 28.01 & 27.72 & 23.97 \\  & 50–75\% & 43.44 & 43.78 & 42.90 & 39.25 & 36.90 \\  & 75–100\% & 9.45 & 11.90 & 13.95 & 18.59 & 26.92 \\ \hline \multirow{4}{*}{USACE (2009)} & \(<\) 10\% & 3.75 & 3.62 & 3.65 & 2.74 & 2.34 \\  & 10-25\% & 3.00 & 3.63 & 3.13 & 3.16 & 2.33 \\ \cline{1-1}  & 25–50\% & 13.44 & 10.58 & 10.57 & 10.78 & 9.77 \\ \cline{1-1}  & 50–75\% & 18.85 & 18.90 & 18.76 & 17.00 & 14.82 \\ \cline{1-1}  & 75–100\% & 60.97 & 63.27 & 63.90 & 66.32 & 70.74 \\ \hline \multirow{4}{*}{USACE (2009)} & \(<\) 10\% & 6.35 & 6.75 & 6.38 & 5.45 & 4.33 \\ \cline{1-1}  & 10-25\% & 7.40 & 6.44 & 5.85 & 6.53 & 5.29 \\ \cline{1-1}  & 25–50\% & 18.42 & 17.33 & 16.31 & 15.10 & 14.14 \\ \cline{1-1}  & 50–75\% & 21.47 & 18.91 & 19.04 & 19.34 & 17.78 \\ \cline{1-1}  & 75–100\% & 46.36 & 50.57 & 52.43 & 53.58 & 58.46 \\ \hline \end{tabular}
\end{table} 
Table 2: Flood hazard areas (%) in the consolidated urban areas at Zamora city; for the damage models (human loss of stability; housing economic losses; damage to vehicles) considered, and their hazard levels. and from the flood frequency analysis, which use probability distribution functions and parameters such as the return period or the probability of exceedance. However, it can also come from the spatial-temporal probability of the location of exposed elements (people, material goods, commercial and service flows) and their vulnerability, which do not remain constant in time and space, and therefore must also be assigned a probability of occurrence. However, \"Probabilistic Flood Maps\" (PFM; [11]) are those which, in addition to the intrinsic stochastic component of hazard and risk, have other probabilistic elements incorporated into the cartographic representation, such as the confidence intervals of the frequency distribution function of the values represented. Therefore, probabilistic mapping of hazard and flood risk is characterized by a zoning of the values (in discrete classes or continuous models), not only of the probability of the phenomenon or of the exposure and vulnerability of the elements at risk, but also of the uncertainty or error in the estimation of the variable represented.