CORFU Presentation Template

Flood damage assessment and
estimation of flood resilience indexes
Barcelona case study
Marc Velasco
CETaqua
Workshop CORFU Barcelona
“Flood resilience in urban areas – the CORFU project”
Cornellà de Llobregat, Monday 19th of May 2014
Outline
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Objectives
Barcelona case study
Damage assessment methodology
Data
CBA methodology
Results
Conclusions
Objectives
• Establish a framework to accurately assess flood
damages in urban areas
• Assess damages for the current state and future
scenarios
• Implement adaptation strategies to cope with future
impacts
• Prioritize the strategies via a cost-benefit analysis (CBA)
• Include the intangible benefits of the strategies by using
the Flood Resilience Index (FRI)
Barcelona case study
Besós River
Collserola mountain
High gradients
Llobregat River
Runoff preferred direction
Low gradients and critical
points  FLOODS
Mediterranean sea
Barcelona case study
 Location: Mediterranean Area, NE Spain
 Inhabitants/Area/People Density: 1,621,000
inhab. within an area of 101.4 Km2 with a
density of 15,980 inhab./ Km2 (19,200 inhab./
Km2 not considering Collserola mountain).
 Morphology and land use: high slopes in the
upper part of the city and flat and impervious
areas near the cost.
 Climatology/Rainfall patterns: Average annual
precipitations: 600 mm. Heavy rainfall with
high intensities (Maximum intensity in 5 min is
205 mm/h for a 10 yr return period and 50% of
annual precipitation can occur in only 2 or 3
events causing flash flood events).
 Raval District: Very vulnerable district with a
people density of 44,000 inhab./Km2 . Spot
susceptible to flooding as demonstrated by
historical data.
Traditional 1D sewer models do not detect flooding
problems as demonstrated by historic data
Damage assessment
methodology
Risk = Hazard · Exposure · Vulnerability
Risk
Hazard
Vulnerability is defined as the susceptibility of the exposed structures/people
at contact with the damaging natural event. This factor measures the extent to
which the subject matter could be affected by the hazard
Damage assessment
methodology
• Damages types
Tangible
Intangible
Direct
Physical damage to
assets
Fatalities, injuries…
Indirect
Loss of production,
traffic disruption…
Psychological trauma,
increased vulnerability
of survivors…
Damage assessment
methodology
• To obtain direct tangible damages the following are needed:
– depth damage curves
– flood depth maps
– land use maps
• The methodology proposed follows these steps:
– Simulation of three flood events to obtain the flood depths in the area
– Assign a water depth to each building
– Interpolate this value in the depth damage curve to obtain the relative
cost
– Multiply the relative cost by the area, obtaining the total damage value
per each block
– Sum of all the blocks damages’ to obtain the total damages of each
event
– Calculation of the EAD by weighting the damages of each event with
its probability
Barcelona methodology
90
80
1
3
Damage (€/m2)
70
60
50
40
Damage
30
20
10
0
0
0,5
1
1,5
2
2,5
3
Water depth (m)
2
1.
2.
3.
Assign DDC to land-use type
Introduce the depth to obtain relative
damage
Multiply the relative damage by the
corresponding surface
Depth damage curves
• No existing curves in Spain
• Lack of actual damage data
• Few land use types in the case study area
• Synthetic relative curves
• Curves for only six different land use types
• Buildings
• Contents
Data: depth damage curves
• Synthetic relative curves
– Buildings
• In collaboration with local appraisers
• Types of buildings (classified by the map characteristics)
– Residential
– Commercial
– Hotels and leisure
– Public and cultural buildings
– Contents
• Using the FloReTo data
• Types of uses
– Residential
– Commercial
– Hotels and leisure
– Public and cultural buildings
– Warehouses and parkings
– Sites of interest
Creation of a
single curve
Data: depth damage curves
Buildings
Contents
Calibration of the curves has been
finalized, using:
• Surveys of the event occurred
in 30/07/2011 to validate some
qualitative features of the
curves
• Actual damage data from the
Spanish re-assurance (CCS) has
been collected to undertake a
spatial and quanititive
validation
Data: depth damage curves
Validation with actual damage data, from
31/07/2011
• Spatial patterns are very similar in
terms of affected area
• Total damages are in the same order
of magnitude
– Simulated: 750,002.9 €
– Actual: 340,472.9 €
• Oversestimation can be explained by:
– Non-reported damages
– Protection measures applied
Future calibration of the curves
should focus on average values
Flood maps
• Post processing of flood maps is required
• Conversion of the 1D-2D model outputs
– From depths in the streets to depths in the buildings
Land use maps
• Catastro (National land-registry)
• Geoportal (Municipal spatial
database)
– Information at a block size
– Number of floors
– Land-use
area of each type per floor
CBA methodology
• Following a DPSIR approach, adaptation strategies are
implemented
Economic growth
Urban growth
Climate change
Drivers
Adaptation measures
Mitigation measures
Responses
Urbanisation
Drainage networks
Precipitation
Impacts
Damage values
Resilience level
Pressures
States
2D hydraulic models
Damage models
CBA methodology
Scenarios
• Combinations of changes in climate and adaptive
capacity level are considered in 6 adaptation scenarios
• Socioeconomic scenario is kept constant in order to
properly assess the results of the CBA
Combined
scenario
Climate
scenario
Socioeconomic
scenario
Adaptive
capacity
Business as usual 1
Pessimistic
Medium
None
Adaptation 1
Adaptation 2
Adaptation 3
Business as usual 2
Adaptation 4
Adaptation 5
Pessimistic
Pessimistic
Pessimistic
Optimistic
Optimistic
Optimistic
Medium
Medium
Medium
Medium
Medium
Medium
Low
Medium
High
None
Low
Medium
Adaptation 6
Optimistic
Medium
High
CBA methodology
Damages for
BAU scenarios
Damages for
adaptation
scenarios
Calculation of
benefits and
costs
Cost benefit
analysis (CBA)
• Benefits are calculated as reductions of damages (EAD)
• Costs include the CAPEX and OPEX for 50 years
• A discount rate of 4% is used to work with present values
Adaptation strategies
• Adaptation strategies will be implemented to cope with
the impacts of climate change
– Adaptation 1: Non-structural
• Affecting the damage curves or land-use situation
– Adaptation 2: SUDS and green roofs
– Adaptation 3: Structural
• Affecting the drainage network
Results
Flood maps
• With return periods of 1 year, 10 years and 100 years, for the
baseline, BAU1 and Adaptation 3 scenarios
Results
Flood maps
• With return periods of 1 year, 10 years and 100 years, for the
baseline, BAU1 and Adaptation 3 scenarios
Results
Flood maps
• With return periods of 1 year, 10 years and 100 years, for the
baseline, BAU1 and Adaptation 3 scenarios
Results
Damage maps
• For the baseline and BAU1 and adaptaion 3 scenarios
Results
Damage maps
• For the baseline and BAU1 and adaptaion 3 scenarios
Results
Damage maps
• For the baseline and BAU1 and adaptaion 3 scenarios
Results
Expected Anual Damage
• EAD is an estimate of the average flood damages computed
over a number of years
• It is generally obtained by simulating several events of different
return periods and calculating the damages for each case
• EAD is the area under the probability – damage curve, and
hence a minimum of three events are needed
Results
Expected Anual Damage
Return period (years)
1
10
100
Probability
1
0.1
0.01
Damages baseline (2010)
78,846
1,615,738
19,156,196
1,697,300
Damages BAU1 (2050)
211,846
8,369,323
45,642,494
6,292,058
Damages adaptation 1 (2050)
0
3,266,670
35,461,156
3,212,754
Damages adaptation 2 (2050)
56,143
6,398,101
44,402,370
5,190,431
Damages adaptation 3 (2050)
7,005
275,258
10,478,002
610,915
Damages BAU2 (2050)
131,654
2,718,048
32,400,065
2,862,681
Damages adaptation 4 (2050)
0
191,470
23,773,122
1,164,568
Damages adaptation 5 (2050)
TBC
TBC
TBC
TBC
Damages adaptation 6 (2050)
5,818
71,540
3,253,262
184,427
EAD
Results
Expected Anual Damage
Results
Cost benefit analysis
• In order to be able to compare costs and benefits of the adaptation
measures, the CBA is based on the Total Present Values (DR = 4%)
– EAD is used to express the annual benefits
– Total cost of adaptation is annualized through its useful life
Scenario
TPV of EAD (€)
Benefits (€)
Costs (€)
Net benefits (€)
BAU1
63,698,915
-
-
-
Adaptation 1
35,683,499
28,015,417
2,021,439
25,993,978
Adaptation 2
53,676,361
10,022,555
3,355,548
6,667,007
Adaptation 3
15,246,604
48,452,312
46,231,149
2,221,162
BAU2
42,538,378
-
-
-
Adaptation 4
20,975,184
21,563,195
2,021,439
19,541,755
Adaptation 5
6,187,114
36,351,264
3,355,548
32,995,716
Adaptation 6
8,529,029
34,009,350
46,231,149
-12,221,800
Results
Cost benefit analysis
• In order to be able to compare costs and benefits of the adaptation
measures, the CBA is based on the Total Present Values (DR = 4%)
– EAD is used to express the annual benefits
– Total cost of adaptation is annualized through its useful life
Flood Resilience Index
• In order to include other intangible indexes, an index
called Flood Resilience Index has been created
Dimension
Dimension index
Natural
3.50
Social
2.14
Economic
3.11
Institutional
3.30
Physical
3.40
Physical
Institutional
Natural
5
4
3
2
1
0
FRI
3.1
Social
Economic
Flood Resilience Index
• In the Barcelona case study, the FRI includes impacts to
assets, pedestrians and vehicular circulation
Conversion from damages to Riskbuildings
Riskbuildings= K · damage
Human vulnerability level
Formulation *,**
(D+C+F)/3 < 1.5
Low
Medium
1.5 < (D+C+F)/3 < 2.5
(D+C+F)/3 > 2.5
High
*In case there is a critical building is in the subdistrict area, 0.5 must
be added to the average value of (D+C+F)/3.
**When an EWS is implemented, the vulnerability of the subdistrict
will be reduced by a given factor.
Vehicular vulnerability level
Low
Medium
High
Vehicular flow intensity (VFI)
(vehicles in 24h)
VFI < 5000
5000 ≤ VFI ≤ 10000
VFI > 10000
RI = (Riskbuildings + Riskpedestrians + Riskvehicles)/3
Flood Resilience Index
• In the Barcelona case study, the FRI includes impacts to
assets, pedestrians and vehicular circulation
RI = (Riskbuildings + Riskpedestrians + Riskvehicles)/3
Risk Index
T1
<3
<3
<3
3-6
3-6
3-6
≥6
Scenario
RI
BAU1
Adaptation 1
Adaptation 2
Adaptation 3
4
2
2
1
T10
<3
<3
3-6
3-6
3-6
≥6
≥6
T100
<3
3-6
3-6
3-6
≥6
≥6
≥6
Difference Weight
2
2
3
FRI
0.6
0.3
0.1
RI
0
0.5
1
2
3
4
5
Value
1.2
0.6
0.3
2.1
Very low
Very low
Low
Medium
High
Very high
Very high
Weight = f (cost of the strategy,
environmental impact)
WA1 + WA2 + WA3 = 1
WA1 = (1/CostA1) + EIlow
WA2 = (1/CostA2) + EImedium
WA3 = (1/CostA3) + EIhigh
Conclusions
• DDC have been created for the case study area
– Calibration and validation process has lead to a set of curves that are
able to accurately represent the damages of the area
• The methodology followed is able to determine the EAD of the area
in a straightforward way
– The EAD of the several scenarios is easily obtained once these are
simulated
• The comparison of baseline and business as usual scenarios
highlights the need for the implementation of adaptation strategies
• The results of implementing the several adaptation measures have
been assessed via a cost benefit analysis
– Strategies with lower investments generally have higher net benefits
• In order to include some other intangible impacts, the FRI has been
created. Other impacts can be included in this index, being able to
prioritize strategies not only in economic terms
Marc Velasco
[email protected]
Beniamino Russo
[email protected]
http://www.corfu7.eu
CORFU Team
Research on the CORFU (Collaborative research on flood resilience in urban areas)
project was funded by the European Commission through Framework Programme 7,
Grant Number 244047.