## 3 Results and Discussion
### Flood Vulnerability Index for Flood-Prone Areas  
The five classes of the flood vulnerability index were obtained by applying the AHP-GDM weights to the characteristics of the flood-prone sites at the neighbourhood level. For each of the 23 flood-prone sites in mainland Portugal, the percentage of each vulnerability class is shown in Figure 7a. The most vulnerable sites are as follows: Ponte de Lima in the North; Coimbra and Pombal in the Centre; Loures in the Tagus and West Region; Setibal and Alcacer do Sal in the Alentejo Region; and Monchique in the Algarve Region. Sites of high or very high vulnerability have been identified in all areas. For example, the city of Agueda, in the central region, is frequently flooded and there is considerable damage in the urban area. Nevertheless, a large area is classified as low vulnerability. This is because the flooded area consists mainly of agricultural land. This index, in addition to the final vulnerability class, allows stakeholders to assess which criterion is the main contributor to the final vulnerability (Figure 7b-e). For all 23 flood-prone areas, Figure 7c shows that the socio-economic criterion is generally the one that contributes the least to the flood vulnerability index, and the exposed elements are the criteria that contribute the most. This is mainly because these areas are usually urban centres where urban land use predominates. As the flood vulnerability index is supported in GIS, it is possible to spatially display the index for each flood-prone area studied. As an example, five flood-prone sites have been selected to illustrate the spatial distribution of the flood vulnerability index categories at the neighbourhood scale (Figure 8). As we can see, the 100-year return period flood area of the Agueda site (Figure 8d) includes a large area of agricultural land that is not considered to be highly vulnerable. However, in the city centre, the vulnerability is very high; several small commercial businesses are severely affected by flooding almost every year. In Coimbra (Figure 8c), the area considered to be very highly vulnerable also includes a national monument (Santa Clara-a-Velha Monastery). This area is frequently flooded, even after several major economic investments in flood defences. This approach makes it possible to validate the results for some areas with prior knowledge. The results seem to be in line with what is already known from past events, and since the analysis is very detailed (small territorial units), the authorities can make better decisions in terms of preparedness or intervention when a flood occurs. These maps can be used by the authorities only with the final vulnerability (Figure 8), but the spatial representability of the flood vulnerability index calculated in this work can be extended to each criterion and, as an example, Figure 9 shows the spatial representation of the four criteria for the flood-prone area of Coimbra: Population, Socioeconomic, Buildings, and Exposed elements. This information at the second level is important for decision-makers to take supported actions to reduce vulnerability in the hotspots of the most vulnerable criterion. If needed by the decision makers, it is also possible to zoom in to the third-level maps. The socio-economic criterion (Figure 9b) is the one that contributes less to the vulnerability. In addition, it is a criterion for which the authorities can apply very few measures to reduce vulnerability. The criterion that contributes most to the vulnerability to flooding is the Exposed Elements (Figure 9d). The city centre of Coimbra is a highly urbanised area, so the authorities need to be aware of flood events to take the necessary operational measures to deal with frequent flooding. For the population criterion (Figure 9a) and buildings (Figure 9c), the proposed methodology was able to identify the areas with more elderly people and older buildings within traditional narrow streets.