**4.2 Step 2: identifying flood risk**

In this step, the expected flood inundation area was delineated by flood inundation simulation using the rainfall-runoff-inundation model (RRI model), developed


**45**

period floods.

tion depth.

*Evidence-Based Contingency Planning to Enhance Local Resilience to Flood Disasters*

Sub-step 1: acquisition of input data for the model. Sub-step 2: acquisition of flood mark records.

Sub-step 6: frequency analysis using rainfall data.

**Figure 6** shows the inundation maps produced in this step.

by ICHARM. The RRI model is a two-dimensional model capable of simulating rainfall, runoff and flood inundation simultaneously Sayama et al. [6]. The model deals with slopes and river channels separately. It applies a 2D diffusive wave model to flows on slope grid cells and a 1D diffusive wave model to channel flows. The software of the model can be downloaded from the ICHARM website [7] for free. We used the RRI model that Shrestha et al. [8] locally customised to conduct flood simulation for the Pampanga River basin and performed hazard mapping for Calumpit Municipality, following the eight sub-step procedures [5] presented below:

Sub-step 3: flood inundation simulation during Typhoons Pedring and Quiel in

Sub-step 4: calibration of the model by comparing observed and simulated

Sub-step 5: validation of the model by comparing the simulation results with

Sub-step 7: flood inundation simulation using design rainfall assumed with 10-,

Sub-step 8: development of inundation depth maps in Calumpit with 10-, 30-

Municipal personnel pointed out that the word "return period" is too technical for residents to understand. Thus, to help them understand the flood scale easily, floods were named according to their scales as "ordinary flood" for 10-year return period floods; "high flood" for 30-year return period floods, whose scale is roughly equal to the largest recorded flood in 2011; and "extreme flood" for 100-year return

Based on the flood simulation results, maps and a chart were created for each barangay, as shown in **Figure 7**. As mentioned above, Calumpit Municipality has its own community flood warning system called "colours of safety" in which power poles are painted in three colours by every 2 ft to visualise the level of danger and help residents make decisions on evacuation. The inundation maps for each barangay (**Figure 7b**) adopted this locally familiar tricolour system to show the inunda-

In addition to inundation maps with three different return periods, inundation probability maps, time-series inundation charts and resource maps were also developed for each barangay. The inundation probability map (**Figure 7c**) was created to help people understand the most frequently inundated areas, by combining the information of three inundation maps with 10-, 30- and 100-year return periods.

The simulation used the high-resolution digital elevation model (DEM) of 5 m grid, observed by the interferometric synthetic aperture radar (IFSAR) and provided by the National Mapping and Resource Information Authority (NAMRIA) in the Philippines without a fee. Inundation simulation for the River basin was first conducted using DEM data of 200 m grid created by IFSAR. After the flood inundation simulation, a grid of Calumpit with the inundation depth of 5 m was developed by obtaining the difference between the floodwater surface level of 200 m grid and the ground-level surface level of 5 m grid by IFSAR. As a result of the flood inundation simulation, three kinds of flood inundation maps with 10-, 30- and 100-year return periods were produced for ordinary, past largest and extreme floods. From the frequency analysis using past rainfall data, a return period of the flood caused by Typhoon Pedring in 2011 was estimated to be 28.3 years. The occurrence of flood inundation with a 30-year return period means the reoccurrence of the 2011 flood.

*DOI: http://dx.doi.org/10.5772/intechopen.82312*

September 2011 (grid, 200 m).

30- and 100-year return periods.

and 100-year return periods (grid, 5 m).

discharges in sub-step 3.

flood mark records.

**Table 1.** *Conditions of houses at each inundation level.*

#### *Evidence-Based Contingency Planning to Enhance Local Resilience to Flood Disasters DOI: http://dx.doi.org/10.5772/intechopen.82312*

by ICHARM. The RRI model is a two-dimensional model capable of simulating rainfall, runoff and flood inundation simultaneously Sayama et al. [6]. The model deals with slopes and river channels separately. It applies a 2D diffusive wave model to flows on slope grid cells and a 1D diffusive wave model to channel flows. The software of the model can be downloaded from the ICHARM website [7] for free.

We used the RRI model that Shrestha et al. [8] locally customised to conduct flood simulation for the Pampanga River basin and performed hazard mapping for Calumpit Municipality, following the eight sub-step procedures [5] presented below:

Sub-step 1: acquisition of input data for the model.

Sub-step 2: acquisition of flood mark records.

*Recent Advances in Flood Risk Management*

*Threshold of inundation based on measurement results.*

inundation level 2, the two-storey houses started being inundated. At inundation level 3, at which the water depth exceeds 0.54 m, both one- and two-storey houses suffered from inundation above the first floor, which suggests that the residents had to stay somewhere above the water level or evacuate to safer places near their houses. The household interviews also found that the inundation above electric plugs caused severe damage to daily life. The height of electric plugs averaged 1.27 m and that of LP gas tanks 0.60 m. The residents usually move LP gas tanks to the second floor or to the rooftop to use them for cooking during an inundation. Inundation level 4 was set, based on the observed average height of electric plugs, as the

condition cutting local people off from power. At inundation level 5, the inundation depth exceeds 2.83 m, the height of the second floor of a house. Under this situation, they could not find an evacuation space due to the rarity of buildings having three storeys or more, which means an inundation of this scale is likely to be a

Calumpit Municipality has its own community flood warning system called "colours of safety". This system uses power poles painted in three colours (yellow, orange and red) by every 2 ft to visualise the level of danger and help residents make decisions on evacuation. At present, 193 electric poles in the municipality are tricoloured for this purpose. The residents are advised to evacuate before the water

In this step, the expected flood inundation area was delineated by flood inundation simulation using the rainfall-runoff-inundation model (RRI model), developed

potentially life-threatening crisis for the residents.

reached the red colour.

**Figure 5.**

**4.2 Step 2: identifying flood risk**

**44**

**Table 1.**

*Conditions of houses at each inundation level.*

Sub-step 3: flood inundation simulation during Typhoons Pedring and Quiel in September 2011 (grid, 200 m).

Sub-step 4: calibration of the model by comparing observed and simulated discharges in sub-step 3.

Sub-step 5: validation of the model by comparing the simulation results with flood mark records.

Sub-step 6: frequency analysis using rainfall data.

Sub-step 7: flood inundation simulation using design rainfall assumed with 10-, 30- and 100-year return periods.

Sub-step 8: development of inundation depth maps in Calumpit with 10-, 30 and 100-year return periods (grid, 5 m).

The simulation used the high-resolution digital elevation model (DEM) of 5 m grid, observed by the interferometric synthetic aperture radar (IFSAR) and provided by the National Mapping and Resource Information Authority (NAMRIA) in the Philippines without a fee. Inundation simulation for the River basin was first conducted using DEM data of 200 m grid created by IFSAR. After the flood inundation simulation, a grid of Calumpit with the inundation depth of 5 m was developed by obtaining the difference between the floodwater surface level of 200 m grid and the ground-level surface level of 5 m grid by IFSAR. As a result of the flood inundation simulation, three kinds of flood inundation maps with 10-, 30- and 100-year return periods were produced for ordinary, past largest and extreme floods. From the frequency analysis using past rainfall data, a return period of the flood caused by Typhoon Pedring in 2011 was estimated to be 28.3 years. The occurrence of flood inundation with a 30-year return period means the reoccurrence of the 2011 flood. **Figure 6** shows the inundation maps produced in this step.

Municipal personnel pointed out that the word "return period" is too technical for residents to understand. Thus, to help them understand the flood scale easily, floods were named according to their scales as "ordinary flood" for 10-year return period floods; "high flood" for 30-year return period floods, whose scale is roughly equal to the largest recorded flood in 2011; and "extreme flood" for 100-year return period floods.

Based on the flood simulation results, maps and a chart were created for each barangay, as shown in **Figure 7**. As mentioned above, Calumpit Municipality has its own community flood warning system called "colours of safety" in which power poles are painted in three colours by every 2 ft to visualise the level of danger and help residents make decisions on evacuation. The inundation maps for each barangay (**Figure 7b**) adopted this locally familiar tricolour system to show the inundation depth.

In addition to inundation maps with three different return periods, inundation probability maps, time-series inundation charts and resource maps were also developed for each barangay. The inundation probability map (**Figure 7c**) was created to help people understand the most frequently inundated areas, by combining the information of three inundation maps with 10-, 30- and 100-year return periods.

**Figure 6.** *Maximum inundation depth maps.*


**47**

**Figure 8.**

*Evidence-Based Contingency Planning to Enhance Local Resilience to Flood Disasters*

centres and electric poles for "colours of safety" were plotted.

The map shows the probability of inundation that may exceed 2 ft. (0.61 m) or higher, the depth almost equal to the height of the first floor of a one-storey house. The area in dark purple colour indicates that one-storey houses in the area may be inundated above the first-floor level in case of a 10-year return period flood. The time-series inundation chart (**Figure 7d**) shows the chronological development of inundation in a barangay using different colours. From this chart, people can understand how many days the area may be inundated according to different flood scales. In the resource map (**Figure 7a**), the locations of barangay halls, evacuation

In order to quantify flood risk at each community, the number of affected residents was estimated based on damage levels by overlaying inundation maps on the population distribution map of each barangay. Since most of the municipal area of Calumpit is used for agricultural purposes, we considered it reasonable to assume that the population is not uniformly distributed over the municipal area but disproportionately distributed in the built-up areas. For this reason, the built-up areas were identified. The identification of the built-up areas was made using satellite images because no digital land use maps were available. If accurate land use maps are available, they can be used for the purpose. The population in each barangay was assumed to be evenly distributed in its identified built-up areas. Then, the number of affected residents in each barangay was estimated according to inundation levels (**Table 1**). As a result, the total ratio of affected residents living in the area with inundation levels 3–5 was calculated to be 55.9% for a 100-year flood, while 34.6% for the past maximum flood case, as shown in **Figure 8**. That well over 55% of the population may suffer at inundation level 3 or above in a 100-year flood means both

one- and two-storey houses are very likely to be inundated above the floor. **Figure 9** shows the estimated number of affected residents in each barangay in both flood cases. In case of a 100-year flood, more than 90% of the residents in barangays of Sapang Bayan, Corazon, Bulusan, Gugo and San Jose may suffer from an inundation of level 3 or above. They should prepare for prompt evacuation in case of such a severe flood. In this case study, only the number of affected residents was analysed due to a lack of spatial distribution data of buildings. If the data is available, the number of damaged houses and the repairing cost could be estimated. Moreover, the number of affected residents or those who need to evacuate outside their houses could be calculated more accurately based on the number of damaged houses.

The third step is flood impact analysis, in which possible problem communities may face in the event of a flood are identified. The most important thing is for

*DOI: http://dx.doi.org/10.5772/intechopen.82312*

**4.3 Step 3: analysing flood impact**

*Estimated number of affected residents in Calumpit.*

**Figure 7.** *Maps and chart for each barangay (example of Barangay Santa Lucia).*

### *Evidence-Based Contingency Planning to Enhance Local Resilience to Flood Disasters DOI: http://dx.doi.org/10.5772/intechopen.82312*

The map shows the probability of inundation that may exceed 2 ft. (0.61 m) or higher, the depth almost equal to the height of the first floor of a one-storey house. The area in dark purple colour indicates that one-storey houses in the area may be inundated above the first-floor level in case of a 10-year return period flood. The time-series inundation chart (**Figure 7d**) shows the chronological development of inundation in a barangay using different colours. From this chart, people can understand how many days the area may be inundated according to different flood scales. In the resource map (**Figure 7a**), the locations of barangay halls, evacuation centres and electric poles for "colours of safety" were plotted.

In order to quantify flood risk at each community, the number of affected residents was estimated based on damage levels by overlaying inundation maps on the population distribution map of each barangay. Since most of the municipal area of Calumpit is used for agricultural purposes, we considered it reasonable to assume that the population is not uniformly distributed over the municipal area but disproportionately distributed in the built-up areas. For this reason, the built-up areas were identified. The identification of the built-up areas was made using satellite images because no digital land use maps were available. If accurate land use maps are available, they can be used for the purpose. The population in each barangay was assumed to be evenly distributed in its identified built-up areas. Then, the number of affected residents in each barangay was estimated according to inundation levels (**Table 1**). As a result, the total ratio of affected residents living in the area with inundation levels 3–5 was calculated to be 55.9% for a 100-year flood, while 34.6% for the past maximum flood case, as shown in **Figure 8**. That well over 55% of the population may suffer at inundation level 3 or above in a 100-year flood means both one- and two-storey houses are very likely to be inundated above the floor.

**Figure 9** shows the estimated number of affected residents in each barangay in both flood cases. In case of a 100-year flood, more than 90% of the residents in barangays of Sapang Bayan, Corazon, Bulusan, Gugo and San Jose may suffer from an inundation of level 3 or above. They should prepare for prompt evacuation in case of such a severe flood. In this case study, only the number of affected residents was analysed due to a lack of spatial distribution data of buildings. If the data is available, the number of damaged houses and the repairing cost could be estimated. Moreover, the number of affected residents or those who need to evacuate outside their houses could be calculated more accurately based on the number of damaged houses.
