**4.2 Land-use and inundation data**

10 Studies on Water Management Issues

Of final importance are the differences in policy. Whilst for extreme events the Regional Water Boards are responsible for policy making, is 'Rijkswaterstaat' responsible for the policy making with large-scale floods. Due to this difference, other criteria or other

Since it is now clear what the conditions are that need to be taken into account and what the dissimilarities are between the flood risk of extreme events and large-scale flooding, it is possible to continue with the actual integrated flood risk model. Even though both types of risk are normally estimated using different models that differ in several aspects, both models are based on the same underlying concepts, namely: depth-damage curves and maximum damages. It should therefore be possible to integrate both approaches into a single integrated flood risk model. This is possible since the integrated flood risk model – like the models it is based on – is mainly focused on direct damage and most of the differences described in the previous section (e.g. human casualties, costs of preventing floods) do not have a direct influence on that. Several studies note that the most important factor that determines direct damage in both extreme rainfall events and large-scale floods is the flood depth (Merz et al., 2007; Penning-Rowsell et al., 1995; Wild et al., 1999). Therefore, the integrated flood risk model will be built around this parameter. In this section, a general description of the methodology will first be explained, then the input will be described and

The integrated flood risk model uses the same approach as the Damage Scanner and the HIS-SSM model. In this approach, a land use map and inundation map are used, which are combined using damage curves and maximum damages per land use. Every land-use class has a different maximum amount of possible damage and uses a different damage function, whereby the possible amount of damage is in millions of euro per hectare. Every damage function shows a curve where the possible inundation is on the x-axis and the damage factor on the y-axis (Figure 2). To determine the amount of damage in the area, a number of steps

1. Inundation depth: Inundation maps determine the maximum inundation depth for each

3. Damage factor: a damage factor is derived from the damage functions and represents the percentage of the maximum total damage. The damage function used is defined by the land-use class. Then, the inundation depth defines the damage factor, which is measured in percentage terms. These damage curves and maximum damages per land

4. Damage calculation: the final step is to determine the amount of damage for a specific cell by multiplying the damage factor with the maximum amount of damage. This

Once the calculations are done, the outcome will be a map and a table for every inundation map with the different amount of damage respectively per pixel and per land use in euro. In the table, not only the different amount of damage is described, but also the average

2. Land-use class: Land-use maps determine the land-use for individual cells.

processes are seen as important for flood policies.

finally the damage factors and maximum damages.

cell, which varies depending on the scenario.

use will further be described in section 4.3.

quantifies the damage that occurs in each cell.

**4.1 General outline of the flood risk model** 

have to be taken:

**4. Methodology of the integrated flood risk model** 

The key inputs to this model come from two different maps. One is the land use map and the other is the inundation map. For the land use map, a new land use map is made which is a combination of the land use map from Land Use Scanner (described in Riedijk et al., 2007 and used in the Damage Scanner) and the 'Landgebruikskaart Nederland' (LGN4, used in the model of Hoes, 2007). The former are derived from a land use model that is applied to simulate land use changes and that is mainly focused on urban areas (see, for example, Koomen et al., 2008 and Koomen and Borsboom-van Beurden, 2011). The latter dataset is more focused on agriculture and distinguishes more classes in these categories (de Wit and Clevers 2004; de Wit 2003; van Oort et al. 2004). Since extreme rainfall events mainly damage agriculture but large-scale floods also damage urban areas and infrastructure, we combine those two to cover enough land-uses for both types of flood risk. The other map we use is the inundation map, which shows us the maximum inundation in a specific area for the different flood probabilities.

The combined land use map contains 25 different land-use classes which can be aggregated into four major land-uses: urban land-uses, agriculture, nature and infrastructure. The urban land-uses consist of five classes: Urban - high density, Urban - low-density, Urban - rural, Commerce and Building lot. Where 'Urban - high-density' are the main cities and towns (like Amsterdam or The Hague), 'Urban - low density' are suburbs and villages (like Egmond aan Zee) and 'Urban – rural' are farms and large houses between pastures and along rural roads. Commerce is all the commercial areas within the Netherlands. The agricultural land-uses consist of nine classes: Greenhouses, pastures, corn, potato, beet, wheat, orchard, bulbs and other agriculture. The nature land-uses consist of seven classes: fen meadow, forest, sand/dune, heath, peat/swamp, water and other nature. Finally, the infrastructure land-uses consist of three classes: Airport, seaport and infrastructure, where the 'infrastructure' class are all the roads, railways and other infrastructure that is not included in airport and seaport.

The inundation maps depict the inundation of extreme rainfall events or large-scale floods. These maps show the inundation in a specific area for different return periods, varying from a probability of 1/10 to a probability of 1/40000. The inundation maps used in this study for large-scale floods, which are calculated for different scenarios, are obtained from the province of Zeeland. The inundation maps can be subdivided into four scenarios: 1/4000 with RTC, 1/4000 without RTC, 1/400 with RTC and 1/40000 with RTC. "RTC (Real Time Control) is a module in the SOBEK model which allows the system to react optimally to actual water levels and weirs, sluices and pumps'' (Deltares, 2010). Important to note is that for the 'North Sea-side' of Noord-Beveland all four scenarios are used, while for the 'Oosterschelde-side' only the first two scenarios are used. This is due to the fact that with high water levels the 'Delta Works' will close.

Comparing Extreme Rainfall and Large-Scale Flooding

are shown.

Induced Inundation Risk – Evidence from a Dutch Case-Study 13

the curves to our specific land-use classes. The damage maps of the HIS-SSM were used to calculate the amount of damage for different inundation depths. By dividing the damage of a certain water depth by the total possible damage (at ten meters of inundation), the damage factor for that inundation depth can be determined. In Figure 2, the different damage curves

**Land use Million euro per hectare** 

A close look at Figure 2 reveals that damage curves for the agriculture classes reach the maximum amount of possible damage relatively quickly. This is consistent with the Damage

1 - Urban - high density 9.9 2 - Urban - low density 5.3 3 - Rural area 1.2 4 – Commerce 7.9 5 – Seaport 5.5 6 – Airport 11 7 – Infrastructure 1.4 8 - Building lot 0.8 9 - Holiday accomodation 0.4 10 - Green houses 0.65 11 – Pastures 0.015 12 – Corn 0.025 13 – Potato 0.025 14 – Beet 0.025 15 – Wheat 0.025 16 - Other agriculture 0.025 17 – Orchard 0.140 18 – Bulbs 0.050 19 - Fen meadow 0.015 20 – Forest 0 21 - Sand/dune 0 22 – Heath 0 23 - Peat/swamp 0 24 - Other Nature 0 25 – Water 0 Table 4. Maximum damage per land use in millions of euro

The inundation maps used in this study for extreme rainfall events are obtained from the water board. These maps, which have been calculated with the use of SOBEK RR and Channel Flow, are made for the water boards in response to the 2003 'Nationaal Bestuursakkoord Water'. For the study, the inundation maps with return periods of 1/10, 1/25, 1/50 and 1/100 are used, whereas the higher return periods have the lowest inundation depths and the lowest return periods the highest inundation depths.

Finally, two additional maps were used for a closer examination of the damage that can occur with respect to the safety norms. For large-scale floods, the Risk Map for the Netherlands (www.risicokaart.nl) has been used and for extreme rainfall, an inundation map has been made with an overall inundation of 0.165 meter, which is the average inundation level above zero of the four different inundation maps for extreme rainfall events.

To be able to use all the maps properly in the model, the land use map and the different inundation maps are modified with ArcGIS to match the same study area. Several adjustments must be made to be able to fit the different inundation maps in the same model. Since the maps for inundation from large-scale floods start at inundation above 0, all the zero values in the map mean no water. But with extreme rainfall events, a value of zero means that there is water up to the ground level. Therefore, the inundation maps of largescale floods need to be adjusted to have no damage in areas where there is no inundation.

#### **4.3 Maximum damage values and damage curves**

Maximum damages and damage curves were created using various sources. The maximum damage for most of the land-use classes is derived from their mean damage per hectare in the damage maps of the HIS-SSM for ten meters of inundation, above which hardly any extra damage occurs. A few land use classes were new and thus not able to have their correct maximum damage derived via the HIS-SSM damage maps. These maximum damages were therefore derived by comparing the specific land use class to damages given in various other studies (Brienne et al., 2002; de Bruijn, 2006; Hoes, 2007; Klijn et al., 2007; Vanneuville et al., 2006). Urban – high density is calculated by first determining the amount of dwellings in high density residential areas (Jacobs et al., 2011) and then multiplied with the amount of damage per dwelling as described in studies of Briene et al. (2002). The maximum damage for rural area is not only derived from the maximum damage per farm, as described in studies of Briene et al. (2002), but also derived after determining the average amount of rural area in the land-use map. Once the maximum damage has been calculated, a simple calculation allows us to estimate the damage per hectare for rural areas. Finally, the maximum damages for the different types of natural land use (e.g. forest, heathland) are set to zero, since no economic valuea can be attached to these areas. This is consistent with studies of Briene et al. (2002), Hoes (2007) and Vanneuville et al. (2006). In Table 4 is an overview of the different maximum damages per hectare.

Furthermore, damage curves are developed that specify the different amount of damage for different inundations. These curves allow us to calculate the different damage factors for different possible inundations. These inundations vary from elevated groundwater levels (-0.3 meters) up to high water levels (5 meters). These curves are mainly based on results of the HIS-SSM, but also other studies (Hoes, 2007; Vanneuville et al., 2006) were used to adapt

The inundation maps used in this study for extreme rainfall events are obtained from the water board. These maps, which have been calculated with the use of SOBEK RR and Channel Flow, are made for the water boards in response to the 2003 'Nationaal Bestuursakkoord Water'. For the study, the inundation maps with return periods of 1/10, 1/25, 1/50 and 1/100 are used, whereas the higher return periods have the lowest

Finally, two additional maps were used for a closer examination of the damage that can occur with respect to the safety norms. For large-scale floods, the Risk Map for the Netherlands (www.risicokaart.nl) has been used and for extreme rainfall, an inundation map has been made with an overall inundation of 0.165 meter, which is the average inundation level above zero of the four different inundation maps for extreme rainfall

To be able to use all the maps properly in the model, the land use map and the different inundation maps are modified with ArcGIS to match the same study area. Several adjustments must be made to be able to fit the different inundation maps in the same model. Since the maps for inundation from large-scale floods start at inundation above 0, all the zero values in the map mean no water. But with extreme rainfall events, a value of zero means that there is water up to the ground level. Therefore, the inundation maps of largescale floods need to be adjusted to have no damage in areas where there is no inundation.

Maximum damages and damage curves were created using various sources. The maximum damage for most of the land-use classes is derived from their mean damage per hectare in the damage maps of the HIS-SSM for ten meters of inundation, above which hardly any extra damage occurs. A few land use classes were new and thus not able to have their correct maximum damage derived via the HIS-SSM damage maps. These maximum damages were therefore derived by comparing the specific land use class to damages given in various other studies (Brienne et al., 2002; de Bruijn, 2006; Hoes, 2007; Klijn et al., 2007; Vanneuville et al., 2006). Urban – high density is calculated by first determining the amount of dwellings in high density residential areas (Jacobs et al., 2011) and then multiplied with the amount of damage per dwelling as described in studies of Briene et al. (2002). The maximum damage for rural area is not only derived from the maximum damage per farm, as described in studies of Briene et al. (2002), but also derived after determining the average amount of rural area in the land-use map. Once the maximum damage has been calculated, a simple calculation allows us to estimate the damage per hectare for rural areas. Finally, the maximum damages for the different types of natural land use (e.g. forest, heathland) are set to zero, since no economic valuea can be attached to these areas. This is consistent with studies of Briene et al. (2002), Hoes (2007) and Vanneuville et al. (2006). In Table 4 is an

Furthermore, damage curves are developed that specify the different amount of damage for different inundations. These curves allow us to calculate the different damage factors for different possible inundations. These inundations vary from elevated groundwater levels (-0.3 meters) up to high water levels (5 meters). These curves are mainly based on results of the HIS-SSM, but also other studies (Hoes, 2007; Vanneuville et al., 2006) were used to adapt

inundation depths and the lowest return periods the highest inundation depths.

**4.3 Maximum damage values and damage curves** 

overview of the different maximum damages per hectare.

events.

the curves to our specific land-use classes. The damage maps of the HIS-SSM were used to calculate the amount of damage for different inundation depths. By dividing the damage of a certain water depth by the total possible damage (at ten meters of inundation), the damage factor for that inundation depth can be determined. In Figure 2, the different damage curves are shown.


Table 4. Maximum damage per land use in millions of euro

A close look at Figure 2 reveals that damage curves for the agriculture classes reach the maximum amount of possible damage relatively quickly. This is consistent with the Damage

Comparing Extreme Rainfall and Large-Scale Flooding

amount of damage will be with respect to the safety norms.

different flood risk per probability for extreme rainfall events.

Annual Damage) per probability for extreme rainfall events

year), even though the total damage varies considerably.

**5.1 The current situation 5.1.1 Extreme rainfall events** 

inundations.

Induced Inundation Risk – Evidence from a Dutch Case-Study 15

extreme rainfall events, the return periods of 1/10, 1/25, 1/50 and 1/100 are used, while for large-scale floods the probability maps of 1/400, 1/4000 and 1/40000 are used. The other is the comparison with respect to the safety norms, which describes the amount of damage for all the land uses looking at the different safety norms (i.e. what is socially and politically acceptable). In other words, when looking to extreme rainfall events, an urban area is for example allowed to inundate once every 100 years and with a large-scale flood, the whole area is in the case of Noord-Beveland allowed to inundate once every 4000 years. This means that in the second comparison, the whole area will be inundated to see what the

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

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

**(x €100,000) (x €100,000)** 

**Return period Total damage Flood risk** 

Table 5. Overview of the estimated total damage and flood risk (in terms of Expected

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

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

1/10 9.5 0.95 1/25 33 1.3 1/50 62 1.2 1/100 99 0.99

Scanner and the HIS-SSM (Klijn et al., 2007) and studies of Hoes (2007) and Vanneuville et al. (2006). This occurs because only a small amount of inundation is sufficient to harm the crops. The damage curve for airports also shows a very steep curve at the beginning, which is due to a lot of indirect damage (e.g. cancelling of flights) that will happen if there is water on the runways. Damage to the urban and other build up areas are relatively similar. A final comment is warranted on the damage curve for 'Commerce', which starts relatively flat and then rises relatively steeply above 3 meters of inundation. Limited information and large heterogeneity makes it difficult to determine the exact damage curve for commerce (Vanneuville et al., 2006).

Fig. 2. Damage curves per land use type
