**5.1.1 Extreme rainfall events**

For extreme rainfall events, four different inundation maps are used. For these different inundation maps, potential damages were calculated with the use of the model. Data showed that most of the damage occurs in agricultural area and infrastructure, and the most damage occurs in areas with wheat, potato and pastures. This is due to the fact that these simply have the largest area. The reason why mostly agricultural areas have large amount of damages reflects the fact that crops are severely damaged with only small amount of inundations.

If we take a closer look at the flood risk for the different probabilities, we will look at the annual expected damage. The annual expected damage is calculated by multiplying the probability times the total damage. In Table 5 we see an overview of total damage and the different flood risk per probability for extreme rainfall events.


Table 5. Overview of the estimated total damage and flood risk (in terms of Expected Annual Damage) per probability for extreme rainfall events

In the table above, we see that higher return periods are associated with higher total damage but not higher flood risk (measured in annual expected damage). This is mainly due to the fact that when the probability of specific events becomes lower, the annual expected damage is also lower because you will multiply the total damage with a much lower factor. Interestingly, the highest total damage occurs for the return period of 1/25 and that all the return periods have almost the same flood risk in terms of EAD (about 100,000 euro per year), even though the total damage varies considerably.

It is also interesting to see where the damage exactly occurs. Figure 3 shows that even with a very low inundation probability (1/10), there is already a relative large amount of damage

Comparing Extreme Rainfall and Large-Scale Flooding

inundation depth is lower.

Induced Inundation Risk – Evidence from a Dutch Case-Study 17

from 22.3 million euro to 1.7 million euro in the sub scenario without the RTC-module. When looking at Figure 5, we see that the main reason for the higher damages is that there is a much larger area that inundates in the sub scenario with the RTC-module even though the

Fig. 4. Damage maps for the four different sub scenarios with the 'North Sea breach'

Fig. 5. Damage maps for the two different sub scenarios with the 'Oosterschelde breach'

Finally, the flood risk per sub scenario was calculated (Table 6). At first, we see the highest total damages in the 'Oosterschelde sub scenario 1/4000 with RTC' and the 'North Sea sub scenario 1/40000 with RTC'. This is mainly due to the fact that, as described above, a much larger area inundates with a lot more urban area in both these sub scenarios and a lot more infrastructural areas in the first sub scenario. If we closer examine the flood risk values, we see the highest flood risk in the 'North Sea' sub scenario 1/400 with RTC and the 'Oosterschelde' sub scenario 1/4000 with RTC. The reason why the first sub scenario has a much higher flood risk is because it has a much higher probability of occurrence. The reason why the latter has a high flood risk is simply because there are very high total damages.

in the northwestern part of the area. This is mainly due to the fact that there are higher inundation levels in these areas and agricultural land uses that undergo damage at even low inundation levels. If we compare this with the land use map of the region (Figure 1), we see that these are all agricultural crops (wheat, beet, and grass).

Fig. 3. Damage maps for the four return periods for extreme rainfall events
