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Page 1
FLOODRESILIENCE
FLOODRESILIENCEGROUP
FLOODRESILIENCEGROUP
FLOOD DAMAGE ANALYSIS
William Veerbeek, Flood Resilience Group, Unesco-IHE, Delft, Netherlands
URBAN FLOOD MANAGEMENT DORDRECHTHSRR02: FLOOD DAMAGE ASSESSMENT ROTTERDAM-RIJNMOND
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UFM DORDRECHT: Knowledge development by DESIGN
WORK PACKAGES: -Risk and Vulnerability assessment-Resilient Planning and Building-Urban Design-Communication and Emergency Response-Policy and Governance
STAKEHOLDERS: -Governement (federal, regional, local)-Research Institutes-Water-board-Housing corporation-Developers, Building industry-Insurance Companies-Citizens
Flood modelling,Vulnerability assessment Flood proofi ng technologies
Vulnerability assessmentDamage assessment
GuidelinesCommunicationFLOOD RESILIENT DESIGN
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UFM DORDRECHT: LEARNING by DOING, Iterative Process (Slow Prototyping)
Flood modelling,Vulnerability assessment
Flood proofi ng technologies
Vulnerability assessmentDamage assessment
GuidelinesCommunicationDESIGN PROTOTYPES
PRACTISE: TREMENDOUS AMOUNT OF INFORMATION EXCHANGE
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INTERGRATED UFM: Incorporate fl ood impact reduction into the city
YET: CITIES ARE COMPLEX AND HIGHLY DIFFERENTIATEDNEED FOR A HIGHLY EXPRESSIVE VULNERABILITY/IMPACT MODEL
1. WHAT? Need for broad set of impact evaluation tools, climate scenarios2. WHERE? Need for detailled impact assessment3. WHEN? Need for incorporation of renewal strategies
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FLOOD DAMAGE ASSESSMENT
TERMINOLOGY
Tangible damages• : expressed in money (direct, indirect)Intangible damages• : Cannot be expressed in money (culture, health, etc.)
Direct damages: • cleaning, repair, replacement, etc.Indirect damages: • business interruption, ‘ripple eff ects’, etc.
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FLOOD DAMAGE ASSESSMENT
TERMINOLOGY
Cummulative frequency• : fi nd frequency of occurence of some value (e.g. dis-charge, water stage)-> from historical recordsReturn period• : period in which the event occursExceedance probability• = return period-1 -> Probability that a given value (e.g. discharge, water stage) is exceeded
COMMON MISCONCEPTIONS:
A 100 year fl ood doesn’t happen every 100 years• A 10000 year fl ood is based on fl ood records•
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FLOOD RISK ASSESSMENT: Only from the ‘driver’ perspective
2D FLOOD SIMULATIONS: 4000-1 EPHigh resolution (max 10x10m grid), including sewerInundation, Velocity for a multitude of design fl oods events
limited inundation depth (<1m) limited fl ow velocities (<0.75m3/s)
FLOOD RISK FOCUSSED ON FLOOD EXTENT AND INUNDATION DEPTH-Little knowledge about impact assessment
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0
5000
10000
15000
20000
25000
30000
35000
40000
0 0,3 0,6 0,9 1,2 1,5 1,8 2,1 2,4 2,9
water stage [m]
dam
ag
e [
€]
Cleaning Floors & Walls Doors Kitchen Installation
CALCULATING DAMAGE FOR INDIVIDUAL FEATURES
1. STAGE-DAMAGE FUNCTIONRelates inundation depth to damage level• Diff ers per feature type, region• Can be composed of diff erent damage contributors• Can be multi-modal (inundation depth, velocity, duration)•
Stage damage curve for detached housing
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CALCULATING DAMAGE FOR INDIVIDUAL FEATURES
2. 2D OR 1D-2D FLOOD SIMULATIONGenerates maximum inundation depth per grid-cell• Apply diff erent fl ood scenarios (i.e. EPs associated to a water stage)•
Flood extent for diff erent EPs
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0,3 0,6 0,9 1,2 1,5 1,8 2,1
water stage [m]
0,3 0,6 0,9 1,2 1,5 1,8 2,1
water stage [m]
0,3 0,6 0,9 1,2 1,5 1,8 2,1
water stage [m]
H1 H2 Hn
.... Classify feature
Attributes feature Fi (e.g. house)type• area• location• etc.•
Flood characteristics at location (Xi, Yi)depth• velocity• duration• etc.•
CALCULATING DAMAGE FOR INDIVIDUAL FEATURES
3. APPLICATION OF STAGE-DAMAGE FUNCTION AND 2D INUNDATION MAPClassifi cation of individual features•
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y = 4E-08x5.8845
0
20
40
60
80
100
120
140
160
180
225 250 275 300 325 350 375 400 425 450
water stage [cm +NAP]
exp
ect
ed
Dam
ag
e [
m€
]
CALCULATING DAMAGE FOR INDIVIDUAL FEATURES
4. RESULTING AGGREGATE DAMAGE LEVELSWater stage - Expected damage•
Return periods - Expected damage•
Current
0
5
10
15
20
25
30
35
40
10 100 1000 10000return period [Y]
exp
ect
ed
Dam
ag
e [
m€
]
Current
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STAGE-DAMAGE CURVES: ATTRIBUTES
MEAN ANNUAL DAMAGE (MAD)Average contribution of each damage level per year•
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
20000
10000
4000
2000
1000
500
250
100
50
25
10
Exceedance probability-1 [-](Water stage [m +NAP])
Dam
ag
e [
x m
ln €
]
2100 Total
MAD
i
I
i
iiP
P
pddpdpDMAD
1
1
2 )(
max
0
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STAGE-DAMAGE CURVES: ATTRIBUTES
SENSITIVITYMaximum value for the derative of the stage-damage curve.•
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
20000
10000
4000
2000
1000
500
250
100
50
25
10
Exceedance probability-1 [-](Water stage [m +NAP])
Dam
ag
e [
x m
ln €
]
2100 Total
SENSITIVITY
max11
11maxYSENSITIVIT dPPdd
ii
ii
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STAGE-DAMAGE CURVES: ATTRIBUTES
GRADUALITYIdentify discontinuities in the derivates of the stage-damage curve•
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
20000
10000
4000
2000
1000
500
250
100
50
25
10
Exceedance probability-1 [-](Water stage [m +NAP])
Dam
ag
e [
x m
ln €
]
2100 Total
Strong infl ection point
N
p
ii DPGRADUALITY
1 21
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RESILIENT PLANNING AND BUILDING: Damage model (where?)
HIGH LEVEL OF DETAIL: High precision but low usability
Dordrecht outer marches: Damage Distribution
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WP3 RESILIENT PLANNING AND BUILDING: Damage model (where?)
Dordrecht outer marches: Damage Clustering
GEOGRAPHICAL DISTRIBUTION(CLUSTERING): High usability(where)
€17.545.537 (71%)
€147.886 (1%)
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WP3 RESILIENT PLANNING AND BUILDING: Damage model (where?)
Example from Rotterdam-Rijnmond(where)
Rotterdm-Rijnmond: Damage Clustering EP = 10000-1
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Roze
nbur
g
Maa
sslu
is
Vlaa
rdin
gen
Schi
edam
Spijk
enis
se
Kore
ndijk
Oud
-Bei
jerla
nd
Bare
ndre
cht
Cape
lle a
an d
en IJ
ssel
Krim
pen
aan
den
IJss
el
Ned
erle
k
Nie
uw-L
ekke
rland
Hen
drik
-Ido-
Am
bach
tA
lbla
sser
dam
Pape
ndre
cht
Berg
amba
cht
Lies
veld
Scho
onho
ven
Lopi
k
Slie
drec
ht
Har
dinx
veld
-Gie
ssen
dam
Gor
inch
em
Wou
dric
hem
Zaltb
omm
el
Dor
drec
ht
Wer
kend
am
Drim
mel
en
Moe
rdijk
Zwijn
drec
ht
Strij
en
Moe
rdijk
Goe
dere
ede
Hel
levo
etsl
uis
Bern
isse
Mid
delh
arni
s
Dirk
slan
d
Brie
lle
Cro
mst
rijen
Oos
tflak
kee
Gee
rtru
iden
berg
Ling
ewaa
l
Rott
erda
m
WP3 RESILIENT PLANNING AND BUILDING: Damage model (where?)
ADMINISTRATIVE DISTRIBUTION: Damage per Municipality
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€ 0.0
€ 0.5
€ 1.0
€ 1.5
€ 2.0
€ 2.5
€ 3.0
€ 3.5
€ 4.0
€ 4.5
€ 5.0
€ 5.5
€ 6.0
€ 6.5
€ 7.0
€ 7.5
€ 8.0
20000
10000
4000
2000
1000
500
250
100
50
25
10
Exceedance probability-1 [-]
Dam
ag
e [
x m
ln €
]
1e Merwedehaven en omgeving
2e Merwedehaven en omgeving
3e Merwedehaven
Achterhakkers en omgeving
Beekmanstraat en omgeving
Bleijenhoek
Boogjes en omgeving
Groenmarkt en omgeving
Grote Markt en omgeving
Handelskade en 's-Gravendeelsedijk
Julianahaven
Kalkhaven
Krabbegors
Lijnbaan
Maasstraat en omgeving
Merwelanden
Krabbepolder
Nieuwe Haven en omgeving
Noorderkwartier
Plein 1940-1945 en omgeving
Wantijpark en omgeving
Weeskinderendijk en Dokweg
Wijnstraat en omgeving
Wilhelminahaven
Dordrecht outer marches: Damage distribution per neighborhood
WP3 RESILIENT PLANNING AND BUILDING: Damage model (where?)
ADMINISTRATIVE DISTRIBUTION: Damage per Neighborhood1. DIFFERENTIATED2. ‘CEILINGS’3. HIERARCHY (4 Nhoods account for about 40% total expected damage)
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WP3 RESILIENT PLANNING AND BUILDING: Damage model (when?)
TEMPORAL DISTRIBUTION: Lifecycle management1. PROACTIVE RETROFITTING (up to 32.3% damages to historical buildings)2. REACTIVE RETROFITTING (end of lifecycle)3. RENEWAL SCHEMES (up to 67.8% damages on post-war buildings)
CHANCES FOR INTEGRATED UFM
0
1
2
3
4
5
6
7
8
till 1904
1905-1
909
1910-1
914
1915-1
919
1920-1
924
1925-1
929
1930-1
934
1935-1
939
1940-1
944
1945-1
949
1950-1
954
1955-1
959
1960-1
964
1965-1
969
1970-1
974
1975-1
979
1980-1
984
1985-1
989
1990-1
994
1995-1
999
2000-2
004
Year of construction[y]
Dam
ag
e [
x m
illi
on
€]
1/4000 1/2000 1/1000 1/500 1/250 1/100 1/50 1/25 1/10Dordrecht outer marches: Damage distribution age housing stock
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WP3 RESILIENT PLANNING AND BUILDING: Damage model (what?)
FUNCTIONAL DISTRIBUTION:-Features (e.g. businesses, housing, infrastructure, public space)-Typologies (e.g. row houses, appartments, detached houses)-Components (e.g. cleaning costs, structural damage, interior damage)
DAMAGE TO INFRASTRUCTUREDamage over Typology
0
50
100
150
200
250
300
4000
2000
1250
500
250
100
50 25 10 1 0.1
Frequency
# Dam
aged
Duplex
Appartment
Row House
Semi-Detached
Detached
DAMAGE OVER BUILDING TYPOLOGY0.053 0.039
0.023
0.049
0.087
0.750
Cleaning Floors & Walls Doors Kitchen Installations interior
DAMAGE COMPONENTS
-Especially for higher EPs, damage to infrastructure is major damage component-Interior damage contributes 75% to total damages to housing-Majority of inundated houses are row houses
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Aggregate Flood Damage for scenarios
RESILIENT PLANNING AND BUILDING: Damage model
0
25
50
75
100
125
150
175
10 100 1000 10000return period [Y]
exp
ect
ed
Dam
ag
e [
m€
]
Current 2050 G+ 2100 Veerman 2050 Lockable/Open 2100 Lockable/Open
INFLUENCE OF CLIMATE CHANGE (what?)-Impacts of climate change are substatial, yet relatively gradual in progression-Levels?-Trend shift?
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WP3: From Damage model to Decision Support
REDUCING FLOOD IMPACTS ACROSS SCALES:-Assessment of damage diff erentiation provides foundation for mixed-strategy-Bottom-up: Implementation of various dry-proof, wet-proof solutions-Top-down: Implementation of levee systems, combined with elevated infrastructure
Hamburg, Germany Dura Vermeer, (2004), Gouden Kust, Maasbommel, Netherlands. DuraVermeer, (2005), Drijvende Kas, Naaldwijk, Netherlands
Dura Vermeer, (2004), Impression Flood Resilient Neighborhood
spill-over eff ects
spill-over eff ects
Housing-level
Urban-level
Catchment-level
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WP3: From Damage model to Decision Support
WHAT ABOUT THE IMPACT OF NON-STRUCTURAL MEASURES:-Compensation measures-Flood insurance
MOTIVATION:-Diff erentiated ‘Risk Landscape’ (spatial, temporal, functional)-Overall impact relatively low-Yet, higher impact levels excpected in future-Stadwerven pilot
Artist Impression Pilot Flood Proof Building