Flood damage assessment and estimation of flood resilience indexes

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1 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

2 Outline Objectives Barcelona case study Damage assessment methodology Data CBA methodology Results Conclusions

3 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)

4 Barcelona case study Collserola mountain Besós River Llobregat River High gradients Runoff preferred direction Low gradients and critical points FLOODS Mediterranean sea

5 Barcelona case study Location: Mediterranean Area, NE Spain Inhabitants/Area/People Density: 1,621,000 inhab. within an area of Km 2 with a density of 15,980 inhab./ Km 2 (19,200 inhab./ Km 2 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./km 2. Spot susceptible to flooding as demonstrated by historical data. Traditional 1D sewer models do not detect flooding problems as demonstrated by historic data

6 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

7 Damages types Damage assessment methodology Direct Indirect Tangible Physical damage to assets Loss of production, traffic disruption Intangible Fatalities, injuries Psychological trauma, increased vulnerability of survivors

8 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

9 Damage ( /m 2 ) Barcelona methodology Damage 0 0 0,5 1 1,5 2 2,5 3 Water depth (m) 2 1. Assign DDC to land-use type 2. Introduce the depth to obtain relative damage 3. Multiply the relative damage by the corresponding surface

10 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

11 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

12 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

13 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 Future calibration of the curves should focus on average values Oversestimation can be explained by: Non-reported damages Protection measures applied

14 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

15 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

16 CBA methodology Following a DPSIR approach, adaptation strategies are implemented Drivers Economic growth Urban growth Climate change Adaptation measures Mitigation measures Responses Pressures Urbanisation Drainage networks Precipitation Damage values Resilience level Impacts States 2D hydraulic models Damage models

17 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 Pessimistic Medium Low Adaptation 2 Pessimistic Medium Medium Adaptation 3 Pessimistic Medium High Business as usual 2 Optimistic Medium None Adaptation 4 Optimistic Medium Low Adaptation 5 Optimistic Medium Medium Adaptation 6 Optimistic Medium High

18 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

19 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

20 Results Flood maps With return periods of 1 year, 10 years and 100 years, for the baseline, BAU1 and Adaptation 3 scenarios

21 Results Flood maps With return periods of 1 year, 10 years and 100 years, for the baseline, BAU1 and Adaptation 3 scenarios

22 Results Flood maps With return periods of 1 year, 10 years and 100 years, for the baseline, BAU1 and Adaptation 3 scenarios

23 Results Damage maps For the baseline and BAU1 and adaptaion 3 scenarios

24 Results Damage maps For the baseline and BAU1 and adaptaion 3 scenarios

25 Results Damage maps For the baseline and BAU1 and adaptaion 3 scenarios

26 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

27 Results Expected Anual Damage Return period (years) Probability EAD 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, ,258 10,478, ,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, ,427

28 Results Expected Anual Damage

29 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, 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, 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

30 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

31 Flood Resilience Index In order to include other intangible indexes, an index called Flood Resilience Index has been created Dimension Dimension index FRI Natural 3.50 Social 2.14 Economic 3.11 Institutional Physical 3.40 Physical Natural Social Institutional Economic

32 Flood Resilience Index In the Barcelona case study, the FRI includes impacts to assets, pedestrians and vehicular circulation Conversion from damages to Risk buildings Risk buildings = K damage Human vulnerability level Formulation *,** Low (D+C+F)/3 < 1.5 Medium 1.5 < (D+C+F)/3 < 2.5 High (D+C+F)/3 > 2.5 *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 Vehicular flow intensity (VFI) (vehicles in 24h) Low VFI < 5000 Medium 5000 VFI High VFI > RI = (Risk buildings + Risk pedestrians + Risk vehicles )/3

33 Flood Resilience Index In the Barcelona case study, the FRI includes impacts to assets, pedestrians and vehicular circulation RI = (Risk buildings + Risk pedestrians + Risk vehicles )/3 Risk Index T1 T10 T100 RI < 3 < 3 < 3 0 Very low < 3 < Very low < Low Medium High Very high Very high Scenario RI Difference Weight Value BAU1 4 Adaptation Adaptation Adaptation FRI 2.1 Weight = f (cost of the strategy, environmental impact) W A1 + W A2 + W A3 = 1 W A1 = (1/Cost A1 ) + EI low W A2 = (1/Cost A2 ) + EI medium W A3 = (1/Cost A3 ) + EI high

34 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

35 Marc Velasco Beniamino Russo

36 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

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