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Disaster Risk AssessmeDisaster Risk AssessmeApplications
Manzul Kumar Haz
With contrib
Gabriel BernaFrancis Ghesquiere, T
ent and Management and ent and Management and s of CAPRA
arika, AIT, Thailand
butions from
l, UPC, SpainThe World Bank, USA
Defining ‘Disaster Risk’
Potential Hazard
Hazard cause dand theiHazard• Hazar• It is re• It is va
V l bl
• The ev
Vulnerable
Risk ~ Hazard → StruRisk Hazard → StruRisk ~ Hazard x Vulnerability → QuaRisk ~ Hazard x Vulnerability/Capacity → Qua
(H) is a phenomenon or situation, which has the potential to isruption or damage to people, their property, their services r environment.
rd is a probabilityestricted for a given period of timealid for a specified area
A
vent has a certain intensity – or magnitude
e Area Elements at Risk
uctural Measuresuctural Measuresantitative Risk Assessmentalitative Risk Assessment, CBDRM
Risk is Also a Spatial Pro
Hazard: How big is the flood (10 yr 50 yr 100 yrHazard: How big is the flood (10 yr., 50 yr. 100 yrVulnerability: What is the depth of water in elemeElements at risk: Which elements are getting aff
oblem
r )?r.)?ents at risk?fected?
How to Assess Risk Spatially
Risk = Hazard x Physical Vu(Probability of occurrence) (Degree of losses
ge (%
)
VulnerHazard
Flood Depth
Dam
ag5 1025 1005 1025 100
Type of hazardIntensityDurationS ti l E t t ExposureSpatial Extent
Overlay of hazard
Exposure
y?
ulnerability x Amount/Numbers to elements at risk) (Quantification of exposed elements)
rability Elements at risk
T f l t t or Intensity
Type of elements at riskNumbersEconomic valueL tiLocation
d & element at risk
Importance of Disaster Risk
Disaster risk assessment important for deveRisk assessment provides a good platform fEvidence provided by risk assessments helpRisk assessment along with cost-benefit anaRi k A t b i i i dRisk Assessments are being commissioned
ChallengesSignificant increase in scientifically-based abut without much convergence;Limited collaborations among the various plLimited collaborations among the various plRisk assessment need variety of data, but d
5
k Assessment
elopment and risk reduction decision making;for advocacy with the policy or decision maker;ps to get political support and mobilize resources;alysis can help in prioritizing DRR investments; i iti (D lhi A Dh k t )in many cities (Delhi, Amman, Dhaka etc.).
nd community-based (VCA) risk assessments,
ayers involved in risk assessments;ayers involved in risk assessments;data sharing/inter-operability remains a challenge.
Disaster Risk is Increasing
Main driver of disaster risk is the rapidly incrPoorer countries have disproportionately hig
Rank
FloodAbsolute Relative Absolute
Absolute and Relative Exposure of Top Asi
R (Million) (%) (Million)1 Bangladesh1 (19.2) Cambodia1 (12.2) Japan1 (30.9
2 India2 (15.8) Bangladesh2 (12.1) Philippines2(20.7
3 China3 (3.9) Vietnam3 (3.9) China3(11.1
4 Vietnam4 (3.4) Bhutan4 (1.7) India4(10.7
5 Cambodia5 (1.7) India5 (1.4) Bangladesh6(7.5
6
reasing exposure;gher mortality/GDP risk.
Cyclone EarthquakeRelative Absolute Relative
ian Countries:
(%) (Million) (%)9) North Marina Isl.2 (58.2) Japan1(13.4) Vanuatu1 (60.4)
7) Niue9 (25.4) Philippines2(12.1) Solomon Isl.2 (36.3)
) Japan10 (24.2) Indonesia3 (11.0) Tonga6 (21.1)
7) Philippines11 (23.6) China4 (8.1) Papua New G..9 (17.5)
5) Fiji12 (23.1) India8 (3.3) Philippines12 (13.8)
Source: Asia Pacific Disaster Report, 2010
HFA and Disaster Risk Asses
HFA Priority Actions ActivitiesAction 1: Ensure that – Legislation to DRR is a priority support DRRAction 2: Identify, assess, and monitor
– Risk assessmen– Early warning,
disaster risksy g
Action 3: Knowledge & education to build a
– Research in mulhazard riskeducation to build a
culture of safetyhazard risk
– Public awarenesAction 4: Reduce
d l i i k f t– Land-use plannin
B ildi l tiunderlying risk factors – Building regulatioAction 5: Preparedness for effective Response
– Review/exercisepreparedness anp p pcontingency plan
7
ssment/Disaster Management
Challenges Reported– Political inertia in approving legislations
nts – Lack of technical/financial capacities– Difficulty in early warning at very local levely y g y
ti- – Multi-hazard risk ass. remains a weak areaGap in risk communication for public
ss– Gap in risk communication for public
awarenessng – Weak enforcement of land-use planning
Diffi lti i i l ti b ildi don – Difficulties in implementing building codese nd
– Eighty percent countries have contingency plans to deal with major disasters
nsp j
Framework for Disaster Risk AManagement
Hazard ITriggering Factors Environmental Factors
GeologySoilLand-use
RainfallVolcanic EruptionEarthquake
LandslidFloodDrought
TopographyHydrology
qCycloneEarthqua
Spatial-Temporal Probability
Risk = Hazard
Quantitative Risk Assessment (Absolute Risk)
Disaster Ma
Disaster PrDisaster Mitigation (Disaster Risk Management)
8
Assessment and Disaster Disinventar
nventory Elements at Risk
de BuildingsInfrastructuresPopulation
Socio-Economic Factors
LivelihoodsLiteracyGender
akeCritical FacilitiesLifelines
PovertyCulture
Community Approach
S l C l d
x Vulnerability
Damage-intensity Relationships Seasonal CalendarTransect Walk
Qualitative Risk Assessment (Relative Risk)
anagement
reparedness Disaster Response Disaster Recovery
Hazard Assessment by Mo
Historical river discharge record was analyzed to find th f it d
4000
5000
6000
umec
s)
the frequency-magnituderelationship for flood
0
1000
2000
3000
Disc
harg
e (cu
01.00
20 Year
Flood hazard maps obta9
odeling
Discharge vs Return Period
Modeling10.00 100.00
Return period (years)
50 Year 100 Year
ined from a flood model (Kalu-Ganga Basin, Sri Lanka)
Hazard Assessment by ParApproach
Flood Haz20 years 20 years 50 years
100 years 10
rticipatory/Community
zard Assessmentflood - Depth up to 90 cmflood Depth up to 90 cmflood - Depth up to 250 cmflood - Depth up to 400 cm
Vulnerability Assessment
Types of Vulnerability
1) Physical – e.g., types and locations of buildings
2) Economic – e.g., non-diversified livelihoods, pove
3) E i t l/ t l 3) Environmental/natural – e.g., destruction of natural barriers e
4) Individual 4) Individual – e.g., age, gender, skill etc.)
5) Social l d hi t )– e.g., poor leadership etc.)
11
Qualitative Vulnerability
Quantitative Vulnerability
Detail Survey
(S i tifi )
erty etc.)
(Scientific)
etc.)Questionnaire Survey
(Traditional VCA)
Quantitative Vulnerability
12
Assessment
Qualitative Vulnerability Ass
Sensitivity Demogr
Major CoContributing Factors
Sensitivity g
LVULNERABILITY
Rural
Adaptive CapacityAdaptive CapacityExposure
Flood Depth
Duration of Flood Events
Exposure: Intensity and duration of flood eventsAd ti C it C it ’d bilit t ith t d Adaptive Capacity: Community’d ability to withstand orSensitivity: Degree to which the community is affected
13
sessment for Flood
raphic Standing Gender
omponents Sub-Components
p g
Land
Gender
Age Groups
Health ConditionStanding
Water
Health Conditiong
Income
LivelihoodMajor Components
Sub-Components
Assets
f fl d t
j p
Contributing Factorsr recover from flood events by flood events.
Hanh et al., 2009
Field Data Collection for QuaAssessment
Contributing Factor Major Components Sub-C
Sensitivity (S) Demographic standing Gender, Age, HRural standing Accessibility, pWater Well, bore-welLand Ownership, siz
Adaptive Capacity (A) Income Amount sourcAdaptive Capacity (A) Income Amount, sourcAssets House types/sLivelihoods Agriculture, bu
Exposure (E) Past flood events Flood frequenc
14
alitative Vulnerability
Components
Healthproximity to marketll, tap waterze, land-usecesces
size, vehicleusiness, jobscy, flood depth
Qualitative Flood Vulnerabil
S (HH)
FVI=0.1FVI=0.5
Flood Vulnera
FVI=0.FVI=0 5FVI 0.5
FVI=0.8FVI=0.5FVI=0.8
E (HH) A (HH)
15
ity Map
4815047
ability Index Sensitivity (S) Adaptive Capacity (A) Exposure (E)
1481 0.4575 0.5749 0.2402 5047 0 4711 0 3235 0 4355 5047
84905047 0.4711 0.3235 0.4355 8490 0.6222 0.3158 0.7201
Quantitative (Absolute) Ri
Risk = Hazard x Physical Vulnerability x Amoun
Hazard (H) = Probability of occurrence Vulnerability (V) = Degree of loss to a given Amount (A) = Value of the element (s) a
US $ 50,000
US $ 200,000
V = 0.6 $ ,
V = 1
Risk = Hazard x Vulnerability x Amount= 0.1 * ((0.6*200,000) + (1 * 50,000) + (0.1*10 0.1 ((0.6 200,000) (1 50,000) (0.1 10= 0.1 * 180,000 = 16,000 $
16
sk Assessment
nt
of a hazard (0 to 1) element (s) at risk, 0 (no loss) to 1 (total loss).at risk
US $ 100,000
10 years FloodV = 0.1
00,000) ) 00,000) )
Quantitative Risk Map for
Quantitative VulnHazard
x
Flood Risk Map
17
Flood in Sri Lanka
nerability
Amount of loss for Amount of loss for various types of
buildingsx
Qualitative Risk Map for F
Hazard
x
18
Flood in Sri Lanka
Qualitative Vulnerability
COMPREHEN
CAPRA was
Consortiu
19
SIVE APPROACH FOR PROBABILISTIC RISK ASSESSMENT
s developed by,p y
um ERN-AL
CAPRA InitiativeRisk analysis methodology
PHazardD
VulnerabilityVulnerability
Exposure
20
Loss EstimationPhysical oss st at oEconomic HumanDamage
Application Application 11Application Application 11
A li ti A li ti 11
Applications
Application Application 11Application Application 11
CAPRA InitiativeObjective and scope
Development of tools forcommunication in order to:
Sensitize decision makers abonatural disasters;natural disasters;
Formulate risk management stand sub-national levels;;
Develop a common methodorisk
21
r risk assessment and
out the damaging potential of
trategies at regional, national
logy for quantifying disaster
CAPRA InitiativeObjective and scope
The CAPRA initiative aims toregional strategy versatileregional strategy, versatiledevelopment of risk assessmerelated to management of disast
22
become the focus of aand effective for theand effective, for theent and decision makingter risks.
CAPRA InitiativeFeatures
Probabilistic risk modeling
Visualization moduleVisualization module
Open architecture platform
23
Hazard modules
Exposure and vulnerability modules
Risk assessment module
Variable resolution grids
Visualization tools
Planning tools
GIS interaction
Open sourceOpen source
User oriented applications
User updatable
CAPRA InitiativeFeatures
Oriented software
W b itWebsite
Communication strategy
24
Available hazard mapsp
Some exposure databases
Vulnerability curves library
Risk and loss analysisRisk and loss analysis
Information datasets
S ft d l dSoftware download
Wiki
Open access trough internet
Regional seminars and workshops
Books and papersBooks and papers
CAPRA InitiativeWhy a probabilistic risk analy
The local intensities produced boccurrence frequencyoccurrence frequency
There is uncertainty in the estimatio
Risk must be expressed in terms of
Abili dAbility to compare and aggregateor multi-risk
Likely future scenarios (climate cha
25
ysis?
by dangerous events (hazard) have an
on of hazard and vulnerability
f occurrence rates or return periods
l f diff l i h dlosses of different events– multi-hazard
nge)
25
CAPRA Players
Comprehensive Approach for Pr26 robabilistic Risk Assessment (CAPRA)
Selected CAPRA ResulManagua (Nicaragua) earthquake r
Economic loss for 6.5 Mw earthquake occurrin
27
lts isk
ng near Managua
AAL/Building
Results for NicaragBluefields hurricane risk
Relative economic loss. Probabilistic analysis f
28
gua
for Wind only
AAL/Eco. Value (Building)
Results for NicaragCorinto hurricane risk
Relative economic loss. Probabilistic analysis f
29
gua
for Wind and storm surge combined
AAL/Eco. Value (Building)
Results for NicaragCorinto hurricane risk
Human expected loss. Probabilistic analysis fo
30
gua
or Wind and storm surge combined
Results for Costa San Jose earthquake risk
Relative economic loss
31
Ricak
AAL/Eco. Value (Homogeneous zone)
Results for Costa San Jose earthquake risk
Human expected loss
32
Ricak
Results for El SalvSan Salvador multi-hazar
Annual average loss (relative). Probabilistic an
33
adorrd risk
nalysis (earthquake and hurricane)
Results for El SalvSan Salvador multi-hazar
Annual average loss (absolute). Probabilistic a
34
adorrd risk
analysis (earthquake and hurricane)
Results for BelizeBelmopan earthquake ris
Annual average loss (absolute)
[US$]0 - 31
32 - 10532 105
106 - 253
254 - 554
555 - 1,421
35
sk
Results for BelizeBelmopan hurricane (win
Annual average loss (absolute)
[US$]0 - 222
223 - 423
424 - 794
795 - 1,506
1,507 - 5,644
36
nd) risk
Results for BelizeBelize City earthquake ri
Annual average loss (absolute)
[US$]7 - 603
604 - 1,453
1,454 - 2,941
2,942 - 7,500
7,501 - 24,722
37
sk
Results for BelizeBelize City hurricane (win
Annual average loss (absolute)
38
nd and storm surge) risk
[US$]472 - 39,077
39,078 - 95,905
95,906 - 185,579
185,580 - 331,062
331,063 - 765,792
Risk Analysis AppPossible Applications of CAP
1) Visualization of hazard and )risk
3) Infrastructure design
5) Contingency and Emergency Planningg y g
7) Real time post-event damage estimation
39
licationsPRA
2) Land use and territorial )planning
4) C/B analysis and support of risk reduction measures
6) Damage scenario analysis
8) Design of financial protection instruments
CAPRA Applications in Bo
40
ogotá
• Colombia’s capital and main economic center
• 750 000 residential buildings750,000 residential buildings
• 200 hospitals and health centers
• 3 500 schools and Universities3,500 schools and Universities
• Population: Over 7,000,000 (High concentration of pop.)
• Exposed value US$40 Billion only building constructions + infrastructure
1) Visualization - Hazard
Seismic Lands
41
d Mapping
slides Floods
2) Landuse and Territor
42
ial Planning
42
43
Before…Resettlement from Nueva Esperanza Barrio
44
… afterResettlement from Nueva Esperanza Barrio
3) Infrastructure Desig
45
gn (Specifications)
Colegio Distrital Florida Blanca
46
4) Cost Benefit Analysis
47 Source: GAR, 2011
etrofitting of Critical Infrastructur
48
re in Bogota
6) Damage Scenario Anal
DAY
49
lysis
NIGHT
6) Contingency and Emer
• Location of emergency units• Functional vulnerability (emergency rou• Health services requirements• Housing requirements• Food requirementsFood requirements• Utilities requirements (water, energy, e• Debris and construction materials
50
rgency Planning
utes, etc.)
tc.)
7) Immediate Damage Es
Bogotá Accelerograph Network (RA
51
stimation
AB)
Immediate Damage Estim
DamSurface Response Spatial Distributionp
52
mation
Physical damage
Human losses
mage Distribution Calculation
8) Design of Financial Pro
Technical premiumTechnical premium(annual expected loss)
53
otection Instruments
Insurance premium calculationInsurance premium calculation
Conclusions
One risk model (CAPRA) can be used
Cost of modeling is going down- geospatial technologies- open source models- open source models
“Models remain models”
54
d for a large number of applications
Upcoming Training on CAPRA
55
A
Date: 28 Nov – 02 Dec, 2011Location: AIT, Bangkok
SParticipants: From South Asian countriesFees: Free! Travel/Accommodation: Borne by participants/ y p p s
www.ecapra.org
Th k f Thank you for yo ki d tt tiour kind attention
Generation of the Risk Cuurve
Need at least 6-7 scenarios to develop a risk curve
Area under this curve shows the average annual loss