*2.8. Integrated Flooding–Electric System Model*

This model analyzed the potential effects of pluvial floods on the electrical system of the city of Barcelona, with special emphasis on critical infrastructures such as high and medium-voltage substations, as well as distribution centers, taking into account the possible effects of climate change.

The model was designed for the hazard, risk and cost assessment of the electrical assets, as shown in Figure 10.

**Figure 10.** Integration of GIS spatial analysis for flood assessment on the electrical model.

In particular, the flooding hazard level of each electrical infrastructure was assessed on the basis on flood influence areas of 5 m, 25 m and 30 m in radius with respect to their location depending on the asset type (distribution center (DC), medium-voltage (MV) and high-voltage (HV) substation respectively), as well as considering the flow depths values every 2 m in order to avoid local errors and potential uncertainties of the electrical asset location and of the source data provided by the 1D/2D USW model. In addition, a 10 cm threshold was used to consider significant local flooding. Using these parameters, the flood affections were classified as complete, partial or null, quantifying the percentage of flooded surface in each area of influence of each electric infrastructure according to the methodology proposed by Sánchez et al. [28,40].

One of the most important uncertainties of this model was the lack of knowledge about the specific location of critical electrical infrastructures (sometimes located on surfaces and at other times underground or with self-protection elements which were not always known).

For the impacts analysis, a vulnerability curve (known as a fragility curve in the energy sector) of the electrical infrastructure proposed by the Federal Emergency Management Agency [41] was used. The curve relates the probability of failure of an electrical infrastructure to the flood depth. Furthermore, this curve was partially modified to carry out a sensitivity analysis of the final results regarding this input [40]. The results obtained from the analysis of the percentage of flooding surface in each area and from the fragility curve were computed to obtain a probability of failure, later categorized into four different risk categories as shown in Table 3.


**Table 3.** Failure probabilities for electrical assets.

The cost assessment was based on estimations based on GIS computing; furthermore, we established the supply area of each electrical location using Thiessen polygons and obtained the power supplied through an estimation of the consumers per area based on the census of the city.

Based on these estimations, it was possible to extract the number of consumers affected and the time needed to repair the substation as well as the cost of the energy not supplied, the cost incurred by businesses, auxiliary generation and the damage received by the location [40].
