International Seminar on Global Metropolitan Delta’s 2017. Flood risk assessment in the Sids. Creating an adequate model with a minimum of input data.

1. FLOOD RISK ASSESSMENT IN THE SIDS
CREATING AN ADEQUATE MODEL WITH A MINIMUM OF INPUT DATA
Hanne GLAS
PhD student at Ghent University, Department of Civil Engineering

2. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

3. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

4. INTRODUCTION
FLOOD RISK ASSESSMENT
Natural hazards cause an economic loss of 314 billion USD worldwide.
Riverine flooding is responsible for 1/3 of that cost.
Flooding affects more people worldwide than any other hazard.
The number of affected people is estimated at 21 million people per year.
In an effort to minimize the cost of flooding, decision makers have invested in water defense
structures such as dikes and levees.
These interventions do not assure full protection.
These interventions give a false sense of safety.
Risk increases due to high-value property and inhabitants close to dikes.
Economic and human losses are higher in case of a dike break.
To minimize consequences, an integrated risk-based approach is necessary.
A risk assessment tool should identify high-risk areas as well as overflow zones.

5. INTRODUCTION
FRAMEWORK FOR RISK MAPPING
Risk = Hazard x Vulnerability

6. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

7. STUDY AREA
SMALL ISLAND DEVELOPING STATES
Each of the SIDS is characterized by:
- low-lying, densely populated coastal areas
- development challenges due to an unstable economy and political situation.
- high vulnerability and a low resilience towards natural hazards.high vulnerability and a low resilience towards natural hazards.

8. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

9. CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
Annotto Bay is a small, low-lying coastal town in the north-east of Jamaica. The presence
of four main rivers, as well as the town’s topographic location, downhill from the Blue
Mountains, attributes to an extreme vulnerability to riverine flooding, flash floods in
particular.
Mountains, attributes to an extreme vulnerability to riverine flooding, flash floods in

10. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

11. Historic rainfall data, hydraulic and hydrological data were inexistent.
The risk analysis was limited to a damage assessment, based on the inundations due to
Tropical Storm Michelle in 2001.
CASE STUDY: ANNOTTO BAY, JAMAICA
DAMAGE ASSESSMENT
Three types of damage were taken into
account: building, road and crop damage.
The damage cost is first calculated for every
damage type separately. Then, all damage
costs are added up to create the final
damage map.
Final damage map for Annotto Bay, Jamaica, based
on the 2001 flood

12. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

13. One of the major challenges for Annotto Bay was the input data availability.
In order to develop a risk assessment tool, applicable in all SIDS, a minimum set of input
data must be determined. This minimum set contains the input data that is absolutely
indispensable to generate an adequate result.
A sensitivity analysis performed to determine the set of indispensable input data.
11 scenarios were created, each testing the influence of certain input data on the result
by evaluating the sensitivity of the three damage types (building, road or crop damages). This
was done by eliminating or simplifying input data.
CASE STUDY: ANNOTTO BAY, JAMAICA
SENSITIVITY ANALYSIS (1)

14. S1 Detailed approach
Building damage calculations sensitivity
S2 Building materials and number of floors unknown
S3 Building locations, materials and number of floors unknown
S4 Building density is calculated based on population density (3 people per building)
Population density is used to determine number of buildings in statistical sectors
S5 Building density is calculated based on number of people in study area (3 people
per building)
Number of people in the study area is used to determine number of buildings
CASE STUDY: ANNOTTO BAY, JAMAICA
SENSITIVITY ANALYSIS (2)

15. S1 Detailed approach
Road damage calculations sensitivity
S6 Road classes are unknown
Average values for the width and the cost of the roads are used
S7 All roads are unknown and not taken into account
No roads data is used
S8 All roads are unknown but taken into account as a percentage of land use
(5% in urban areas, 2% in rural areas)
No roads data is used, but the damage is calculated based on a percentage of
land use
S9 Roads are only used to divide land use polygons – no road damage
Roads are used as a division tool, not to calculate damage
CASE STUDY: ANNOTTO BAY, JAMAICA
SENSITIVITY ANALYSIS (3)

16. S1 Detailed approach
Crop damage calculations sensitivity
S10Difference between banana plantains and other crops is unknown
In the damage calculations, the same damage factors and maximum costs are
used to determine the cost of the crops and the banana plantains
CASE STUDY: ANNOTTO BAY, JAMAICA
SENSITIVITY ANALYSIS (4)

17. S1 Detailed approach
Data type sensitivity
S11Raster approach (10mx10m) based on population density
All input data (vector) is converted to raster data with a resolution of 10 meters
S12Raster approach (30mx30m) based on population density
All input data (vector) is converted to raster data with a resolution of 30 meters
CASE STUDY: ANNOTTO BAY, JAMAICA
SENSITIVITY ANALYSIS (5)

18. Important conclusions sensitivity analysis
- Roads are very important for an adequate visual result of the damage spread, even
though the road damage cost has only a very small influence on the overall damage cost.
- The combination of population density with an average number of people per
household is a good replacement for building data with the exact building locations.
- Since the share of crop damage in the total damage is almost negligible, it is impossible
to decide on the accuracy of the crop calculations.
CASE STUDY: ANNOTTO BAY, JAMAICA
SENSITIVITY ANALYSIS (6)

19. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

20. A building must be accessible.
Most buildings are located close to a road.
Two buffer distances are taken into account.
In the case study of Annotto Bay, 90% of all buildings is located within a distance of 25
meters from any road. The other 10% is located in a buffer distance of 60 meters from
any road.
The Annotto Bay area has an average of 3 people per household.
Combined with the population density per statistical sector to calculate the number of
buildings per landuse polygon.
It is extremely important that all roads, even small dirt roads, are part of the input road
dataset.
CASE STUDY: ANNOTTO BAY, JAMAICA
MINIMUM INPUT DATA DAMAGE ASSESSMENT (1)

21. CASE STUDY: ANNOTTO BAY, JAMAICA
MINIMUM INPUT DATA DAMAGE ASSESSMENT (2)
Final damage map for Annotto Bay,
Jamaica, based on the 2001 flood
Final damage map based on the
minimum set of input data

22. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

23. COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
G E
D G E
D D
A G M PE

24. COMPARISON
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
Final building damage map for Annotto Bay,
Jamaica, based on the 2001 flood
Final building damage map based on the
minimum set of input data

25. CONTENT
INTRODUCTION
FLOOD RISK ASSESSMENT
FRAMEWORK FOR RISK MAPPING
STUDY AREA
SMALL ISLAND DEVELOPING STATES
CASE STUDY: ANNOTTO BAY, JAMAICA
SITUATION MAP
DAMAGE ASSESSMENT
SENSITIVITY ANALYSIS
MINIMUM INPUT DATA DAMAGE ASSESSMENT
COMPARISON
QUANTITATIVE RESULTS OF THE TWO DAMAGE MODELS
VISUAL RESULT OF THE BUILDING DAMAGE CALCULATIONS
CONCLUSIONS

26. - The damage map based on the minimum set of input data offers an excellent view on the
damage spread and the areas with the highest damage.
- A new case study must be carried out in a rural area, where building damage will take
up a smaller part in the total damage cost, to enable the verification of the results of the
crop damage calculations.
- Roads have almost no influence on the overall damage cost. However, before
eliminating these calculations from the model, this conclusion must be verified in other
case studies, especially in rural areas.
- The presence of the roads has proven to be extremely important for a correct visual result
on the damage spread. Therefore, a complete road dataset, including all dirt roads as
well, is indispensable from the flood damage model.
CONCLUSIONS (1)

27. - Since many areas in the SIDS are dangerous, remote or inaccessible, different data
acquisition possibilities will be investigated in further research.
- The focus will be on open source data, such as satellite imagery and aerial photography,
but the available vector data will also be assessed on its accuracy.
- The goal of the use of these new data types is to eliminate the need of an on-site
mission and making it possible to perform an adequate flood damage assessment with a
minimum set of accurate open source data, without using any ground truth, in all SIDS.
CONCLUSIONS (2)