## 3 Results
### NDVI and Autocorrelation Analysis of Flooding Patterns  
We first performed a _NDVI_ analysis of the DANA days in 2016, 2018, and 2019 (Figure 9). The obtained spatial floodplain was then visually compared with the theoretical watershed model established by the criterion used in official flooding regulations in order to evaluate the extent to which the behavior of the theoretical watershed corresponds to the real situation of the watershed observed in the last DANAs (Table 3). The level of autocorrelation of the spatial distribution of the effects of the last rains was measured. The values obtained from this analysis, evaluated through the global Moran's I statistic, allow for the verification of whether the phenomenon of flooding in the study area follows significant behavior patterns (Table 4). This ensures that it is not a random phenomenon at the statistical-spatial level.  
The values obtained in the spatial distribution of the _NDVI_ analysis clearly show two issues. The first one is that the spatial distribution of the phenomenon has a significant statistical autocorrelation level. The level of clustering of the three DANAs analyzed shows a pattern of behavior that identifies a clearly nonrandom phenomenon. It is therefore an issue that requires detailed study in order for us to understand its behavior, whose physical derivatives can be parameterized using GIS spatial patterns.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**GIS Indicators** & \(I_{\text{FSD}}\) & \(LID\) & \(SA\) & \(ATO\) \\ \hline Global Moran’s Index & 0.37 & 0.87 & 0.72 & 0.48 \\ z-score & 17.5 & 78.2 & 62.7 & 27.3 \\ \(p\)-value & 0.01 & 0.01 & 0.01 & 0.01 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Evaluation of the global Moran’s I statistic for the different GIS indicators.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Rate HS/NDVI** & **2016** & **2018** & **2019** \\ \hline T = 50 years & 36.1\% & 55.0\% & 28.2\% \\ T = 100 years & 64.6\% & 76.2\% & 43.5\% \\ T = 500 years & 94.5\% & 100\% & 77.4\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Coverage ratio of the _NDVI_ analysis for different return periods for the last three DANAs of 2016, 2018, and 2019 and the resulting simulation from national regulations with the current Horton–Strahler theoretical model of the watershed.  
The second issue is that there is an important spatial discrepancy between the flow network observed through the _NDVI_ analysis in these DANAs and the expected theoretical flow network. The theoretical results of the Horton-Strahler suggest a strong downward divergence from the actual results observed in this watershed if we assimilate them to the return periods for the available statistical series assigned to the rainfall observed in the three DANAs studied (Figure 10). As can be seen, the current existing theoretical model, based on the data provided by the competent administrations in the area, clearly underestimates the effects of the floodplain, even for very high return periods (T = 500 years).  
The territorial transformation of an anthropic nature in the region therefore plays a relevant role in this mismatch between reality and the theoretical models. However, the phenomenon of territorial anthropization is a very wide and heterogeneous concept. Therefore, we explore which of its main guiding parameters at a spatial level present a higher level of statistical correlation with the existence of damage derived from the DANAs.  
Figure 9: _NDVI_ representation of flooding distribution in the study area associated to the DANA episode of 2019. Source of data: Sentinel 2 satellite (consulted for 13 September 2019).