Flood Risk Assessment for Emergency Preparedness and Response

Flood Risk Assessment for Emergency Preparedness and

Response. Paolo Reggiani & Nathalie Asselman

WL | Delft Hydraulics

Symposium on Multihazard Early Warning Systems for Integrated Disaster Risk Management

WMO- Geneva 23-24 May 2006

Definition of Flood Risk:

Risk = damage x probabilityRisk = damage x probability

Damage

Damage is function of:• type and number of buildings• land use• infrastructure• flooding characteristics….

Important flooding characteristics:• time of inundation (winter / summer)• rate of rise• duration of inundation• water depths• flow velocities

Flooding characteristics

Damage andcasualties

model developed at

Delft Hydraulics for

the Dutch situation

General

• Development of a standard method to compute costs and casualties caused by flooding.

• Implemented in a Hydrological Information System (HIS).

• Initiated by Road and Hydraulic Engineering Division, Directorate-General of Public Works and Water Managementm, The Netherlands.

• The method is applicable for situations world-wide.

Aim and applicability

• Modelling system to estimate/predict damage caused by low-frequency floods.

• Floods and inundations originating from “larger” water bodies.

YES: dike breaks.

NO: local inundation from sewage systems.• No difference between salt and fresh water.

What is modelled?

• Casualties

• Damage

• loss of capital goods (houses, infrastructure, etc.)

• reduced productivity

• loss of income (businesses, shops, restaurants, etc.)

Procedure

Model•damage functions

Data•land use type•nr of inhabitants•etc.

Flooding scenario

damagedamage function

water depth

land use

Total damage estimation:

with: i = damage-factor for category i (e.g. houses, roads, etc.)

ni = number of units in category i

Di = max. damage per unit in category i

1

n

i i ii

D n D

Damage factor i

Varies from 0 to 1

Function of:

• depth of inundation

• (critical) flow velocity

• storm(waves)

• rate of rise (important for number of casualties)

Problems:

• Number of casualties depends on water depth and flow velocities after dike break, but also on possible warning and evacuation beforehand

• Damage relations for other categories mainly based on theory as little ‘experimental’ data are available form previous flood experience

• Use of experimental data still poses problems

Utrecht

Amsterdam

Den Haag

Rotterdam

NorthSea

Rhine

Meu

se

December 1993 - January 1995

3700

3800

3900

4000

4100

4200

4300

4400

4500

4600

0 200 400 600 800 1000 1200 1400 1600 1800

tijd (uren)

wat

er le

vel (

m +

msl

)

h-dec93 h-jan95

Damage claims

Cathegory (aggregated)

1993 (million guilders)

1995 (million guilders)

Private properties

96 48

Agricultural companies

39 42

Other companies

71 62

Government 61 39

Total ca. 270 ca. 190

Damage data private properties: houses

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

0 0.5 1 1.5 2 2.5 3

water depth (m)

da

ma

ge

(fl

)

HD-95 HD-93 FD-theory

Damage data private properties: furniture

0

10000

20000

30000

40000

50000

60000

0 0.5 1 1.5 2 2.5 3

water depth (m)

da

ma

ge

(fl

)

FD-95 FD_93 FD-theory

Why are the costs for the second flood lower ?

• People take measures to reduce the damage:• tiled floor instead of parquet floor• put furniture on first floor when probability for

flooding increases

--> difficult to include in damage model !!

Improvement of the damage models: current research

• adjust damage functions• economic – loss of income (TU Twente)• houses and roads (TNO)

• environmental risks (Alterra, TNO, GeoDelft, CSO, WL)

• casualties / victims (WL, DWW)

Case study area ‘Zuid-Holland’

Flooding characteristics: water depth

Flooding characteristics: flow velocities

Isochrones of inundation (in hours after dike break)

Is it possible to escape ?• based on evacuation model for different area

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

time (hours after dike break)

perc

enta

ge o

f pe

ople

tha

t ha

ve e

scap

ed

empirical relationships established for different areas

Percentage of inhabitants that are able to escape (based on data on road network)

Estimated number of casualties (based on 1953 flood data, Zeeland province)

The Problem – time to escape

First estimate

City (suburb) Rotterdam-Hilligersberg

available time (hours) 60

route A20 Gouda

distance (km) 27

driving speed (km/h) 20

driving time needed (hours) 1,5

time elapsed before departure (hours)

4

total time (hours) 5,5

risk ? very low

Second estimate

City (suburb) Rotterdam-Hilligersberg

bottleneck road to highway, highway

available time (hours) 1

distance to bottleneck (km) 1,5

total time needed (hours) 4,1

risk ? very large !

Main lesson learned?

• A traffic / transport model is needed to obtain the most realistic estimate of potential number of casualties

• Good instructions beforehand may reduce the risk of wrong decisions with respect to choice of route