assessing local vulnerability to climate change and its...
TRANSCRIPT
Assessing Local Vulnerability to Climate Change and its
Implications: the Case of Gyeonggi-Do
Jaekyung Koh
(Gyeonggi Research Institute)
Resilient Cities 2010
The concept of vulnerability
• Vulnerability refers to the degree to which a system
cannot cope with negative impact of climate change,
encompassing physical, social and economic aspects
• IPCC characterizes vulnerability as a function of three
componentsexposure
sensitivity
Potential impact
Adaptive capacity
Vulnerability
1. The concept of vulnerability
Vulnerability(V) =
f { exposure(E),
sensitivity(S),
adaptive
capacity(AC) {
Components of vulnerability
• Exposure relates to the degree of climate stress upon a
particular unit analysis; it may be represented as either
long-term changes in climate conditions, or by changes
in climate variability, including the magnitude and
frequency of extreme events(IPCC, 2001)
• Sensitivity is the degree to which a system will be
affected by, or responsive to climate stimuli , either
positively or negatively
• Adaptive capacity refers to the potential or capability of
a system to adjust to climate change, including climate
variability and extremes, so as to moderate potential
damages, to take advantage of opportunities, or to
cope with consequences
1. The concept of vulnerability
Vulnerability types by impact-adaptive capacity axis
• The greater the exposure or sensitivity, the greater is the vulnerability, while the greater the adaptive capacity, the lesser is the vulnerability.
• Reducing vulnerability would involve reducing impact, or increasing adaptive capacity
most vulnerable
resilient
Impact
Adaptive
Capacity
1. The concept of vulnerability
<Figure > Administrative Map
• Located in the central western part of Korea
• 11,549,091 residents
(23.3% of total
national population)
• 10.2% of gross
national area(17 times
larger than Seoul)
• 31 Municipalities
• 20.3% of Korea’s
total GDP
• More than 40% of
knowledge- based
industry
manufacturing and
50% of related R&D
spending in Korea
A Glance at Gyeonggi-Do
2. Climate trends in Gyeonggi-Do
Temperature
• Temperature Increase at the rate of
0.55℃/10years on average
SuwonYang pyung
Icheon Gyeonggi-Do(average)
2. Climate trends in Gyeonggi-Do
Average precipitation in July (1971-2000)
• High in Pocheon, Yeoncheon, Gapyung,
Dongducheon
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546mm
199mm
2. Climate trends in Gyeonggi-Do
Precipitation intensity
• Precipitation intensity increase at the rate of
1.3/10 years on average
Precipitation intensity
2. Climate trends in Gyeonggi-Do
3. Methodology
Objectives of vulnerability assessment
• Vulnerability assessment needs different information,
methodology, and spatial and temporal scale
depending its objective
• Objectives of vulnerability assessment
- Climate impact assessment to reduce greenhouse gas
emissions
- Identify vulnerable sectors and areas to allocate resources for
adaptation
- Analyze adaptation options to develop adaptation strategies
Determining vulnerability indicators and their weightings
• Vulnerability indicators were elicited by feedbacks from
two expert meetings and interviews with public officials
• Standardize data and measure skewness
• Analytic Hierachy Process was utilized to determine
weightings of the indicators
• Calculate sectoral indices(exposure, sensitivity, adaptive
capacity) by summation of weighted standardized scores
of indicators
• Vulnerability Index is the average of three sectoral indices
3. Methodology
sectors Indicators Proxy variables
Function of
vulnerabilit
y
Precipitatio
n
Heavy
Precipi-
tation
Heavy precipitation frequency
Number of Days with precipitation ≥ 80mm/day
+
Maximum one day precipitation
Maximum one day precipitation +
Precipitation intensityAnnual total precipitation/ no. of days with precipitation ≥1mm
+
Drought
Average consecutive dry days
Average of consecutive dry days +
Maximum consecutive dry days
Maximum no. of consecutive dry days +
Temperature
Tropical nightsNo of days with daily minimum temperature ≥ 25℃
+
Heat waveDays with daily maximum temperature ≥33℃
+
Heat wave duration index
Maximum period > 5 consecutive days with Tmax > 5℃ above the past 30 years daily Tmax normal
+
Sea level rise Sea level rise Presume 1m of sea level rise +
Exposure indicators
3. Methodology
Sensitivity indicators
sectors indicators Proxy variables
Function
of
Vulnerabilit
y
Geography
/land use
Ecologically sensitive area
Habitat of Endangered species +Tidal wetland areas
Drought vulnerable area
Agricultural land area/total land area+
Flood risk areaFlood risk area/total land area
+Utilized river bed area/total land area
Low-lying coastal area
Proportion of areas at altitude below 1m+
Demographi
c
Characteristi
cs
Population density population/total land area +Old age population Proportion of population aged over 65years +
Socially vulnerable groups
Proportion of elderly living alone+Proportion of people in poverty
Climate related disease patients
Proportion of patients with respiratory diseases
+Proportion of patients with vector-borne diseases
Infrastructur
e
/industry
InfrastructureProportion of transportation and supply facilities area +
Industrial park Proportion of industrial park area +
buildingProportion of housing units older than 30 years +
3. Methodology
Adaptive capacity indicators
sectors indicators Proxy variables
Function
of
vulnerabili
ty
Economic
capability
GRDP GRDP -Economic growth GRDP growth rate for five years -
Fiscal independence
Local tax+non tax revenue/general account budget
-
Physical
infrastructure
Open space Park area per capita -River
improvementRiver improvement length(km)/improvement needed(km) -
Medical facility
Population/hospital beds
-Medical employees/total populationPublic health center employees/total populationNumber of general hospitals
Access to clean water
Drinking water supply -Sewage treatment systems -Use of groundwater/available groundwater +
telecommunications
Cellular phones per household-Ratio of PC supply and use
Internet subscription rate
3. Methodology
Adaptive capacity indicators
sectors indicators Proxy vairables
Function
of
vulnerabili
ty
Social
capital
Public-private partnership Climate change related partnership -
Citizen’s capacity on climate change
Citizen’s actions on climate change
-Education and campaign for disaster management Proportion of people took health education
Sense of communityProportion of volunteers
-Local voluntary commitment for disaster management
Institution
al capacity
Political leadershipPolitical leader’s concern in disaster management -Political leader’s concern in climate change
Prevention systemDelivery system for disaster relief
-Warning system managementDisaster prevention system management
Staff for adaptation measures
Public officials per capita -Convalescence care +
Policy levelLevel of Climate change policyClimate change policy systemLevel of disastem management policy
-
3. Methodology
Data collection
• Temperature and precipitation data during 1999~2008
• Statistical data and survey data were utilized together
3. Methodology
Weather observations Precipitation observations
Meteorological Observatory
Meteorological AWS
Agricultural AWS
Meteorological Observatory
Meteorological AWS
Agricultural AWS
Precipitation Observatory
Results of AHP
exposure
sensitivityAdaptivecapacity
geography/land use
populationcharacteristics
infrastructure/industry
sea level rise drought
rainfall/flood
heatwave
economy
institutionalcapacity
physicalinfrastructure
social capital
3. Methodology
Top 10 Indicators by priority of AHP
rank indicators priority category
1 Prevention system against disasters 0.06326 Adaptive capacity
2 flood risk area 0.05868 Sensitivity
3 Political leadership 0.05384 Adaptive capacity
4 Local fiscal independence 0.04708 Adaptive capacity
5 GRDP 0.04708 Adaptive capacity
6 Infrastructure 0.04083 sensitivity
7 Access to clean water 0.03828 Adaptive capacity
8 Policy responses to climate change 0.03826 Adaptive capacity
9 Citizen engagement and action 0.03662 Adaptive capacity
10 Public-private partnership 0.03662 Adaptive capacity
10 Community solidarity 0.03662 Adaptive capacity
3. Methodology
4. Results
Mapping Vulnerability to Climate Change
Exposure Map Sensitivity Map
P a ju - si
S e o u l- s i
P o c h e o n - s i
Yo n g in - s i
Ya n g p y e o n g - g u n
A n se o n g - s i
Ye o ju - g u n
G ap y e o n g - g u n
H w a se o n g - s iIc h e o n - s i
Ye o n c h e o n - g u n
G w a n g ju - s i
P y e o n g ta e k- s i
Ya n g ju - si
N a m y a n g ju - s iG im p o - s i
In c h e o n - s i
G o y a n g - s i
S u w o n - s i
S ih e u n g - s i
A n sa n - si
S e o n g n a m - s i
H a n a m - s i
U ije o n g b u - s i
A n y a n g - s i
D o n g d u c h e o n - s i
O sa n - s i
U iw a n g - si
G u r i- s i
B u c h e o n - si
G w a ch e o n - s i
High
Paju-si
Seoul-si
Pocheon-si
Yongin-si
Yangpyeong-gun
Anseong-si
Yeoju-gun
Gapyeong-gun
Hwaseong-siIcheon-si
Yeoncheon-gun
Gwangju-si
Pyeongtaek-si
Yangju-si
Namyangju-siGimpo-si
Incheon-si
Goyang-si
Suwon-si
Siheung-si
Ansan-si
Seongnam-si
Hanam-si
Uijeongbu-si
Anyang-si
Dongducheon-si
Osan-si
Uiwang-si
Guri-si
Bucheon-si
Gwacheon-si
Paju-si
Seoul- si
Pocheon-si
Yongin-si
Yangpyeong-gun
Anseong-si
Yeo ju-gun
Gapyeong-gun
H waseong-siIcheon-si
Yeoncheon-gun
Gwangju-si
Pyeongtaek-si
Yangju-si
N am yangju-siGim po-si
Incheon-si
Goyang-si
Suwon-si
Siheung-si
Ansan-si
Seongnam -si
Hanam -si
Uijeongbu-si
Anyang-si
D ongducheon-si
O san-si
U iwang-si
Guri- si
Bucheon-si
Gwacheon-si
4. Results
Mapping Vulnerability to Climate Change
Impact(Exposure-Sensitivity) Map
Adaptive Capacity Map
High
Paju-si
Seoul-si
Pocheon-si
Yongin-si
Yangpyeong-gun
Anseong-si
Yeoju-gun
Gapyeong-gun
Hwaseong-siIcheon-si
Yeoncheon-gun
Gwangju-si
Pyeongtaek-si
Yangju-si
Namyangju-siGimpo-si
Incheon-si
Goyang-si
Suwon-si
Siheung-si
Ansan-si
Seongnam-si
Hanam-si
Uijeongbu-si
Anyang-si
Dongducheon-si
Osan-si
Uiwang-si
Guri-si
Bucheon-si
Gwacheon-si
High
• High vulnerability group
- Yeoju, Yangpyung,
Gimpo, Pocheon,
Yeoncheon, Goyang
• Low vulnerability group
- Gwacheon, Suwon, Anyang,
Yongin, Sungnam, Ansan
• Nothern area is more
vulnerable than southern
area
4. Results
Overall Vulnerability Map
Higher
Mid-highMiddleLow-midLower
Relationship between vulnerability Index and disaster damage
• Positive relationship between disaster damage and
vulnerability index(VI)
4. Results
VI
Damage
VI
Damage rank
VI
Disaster index
Relationship between vulnerability Index and economic capacity
• Negative relationship between economic
capacity and vulnerability index
4. Results
VI
Economic capacity
Vulnerability types and characteristics
• Type I : High Impact,
Low AC
• Type II : Low Impact, Low
AC
• Type III : High Impact, High
AC
• Type IV : Low Impact, High
AC
5. Discussions and Implications
-3 -2 -1 0 1 2 3-3
-2
-1
0
1
2
3 Impact
Adaptive Capacity
Type I Type III
Type IV Type II
high
high
low
low
Vulnerability Types and Characteristics
• Type I : High Impact, Low AC
- most vulnerable, higher priority for adaptation measures
- differential adaption measures dependent on vulnerability
characteristics
ex) Yeoncheon and Pocheon have high exposure index and high ratio of
vulnerable population, while Gimpo and Yeoju high sensitivity
index(flood risk area)
- governance, education and non structural measures in the short term
are needed
• Type II : Low Impact, Low AC
- exposure to potential risk, little concern in climate change
- awareness raising and capacity building needed
- in common, lack of economic resources and social capital such as public-
private partnership
- physical infra and institutional capacity are uneven across
municipalities
5. Discussions and Implications
Vulnerability Types and Characteristics
• Type III : High Impact, High AC
- capacity to reduce high risk
- prevention system for effective adaptation
- differential adaptive capacity building dependent on its composing
elements
ex) Goyang : high economic resources, lack of social and institutional
capital
Gapyung : high social and institutional capital, lack of economic
resources
• Type IV : Low Impact, High AC
- high resilience to climate change, but the magnitude of impact could be
huge
- most urbanized and densely populated area, higher GRDP
- need climate friendly land use to limit development in flood risk area and
integration of climate impact into urban planning
5. Discussions and Implications
5. Discussions and Implications
Implications of vulnerability indicators
• Identify adaptation priorities
- compare relative vulnerability across cities
- identify adaptation priorities on the area with high potential impact by
climate change but low adaptive capacity
• Differential approaches by vulnerability types
- identify and decompose elements of local vulnerability
- take adaptation actions in urgent need depending on
local characteristics
• Adaptive capacity building
- AHP shows higher priority on adaptive
- develop human resources and social capital, and build
institutional capacity
- maximize synergy effect by integrating adaptation into
existing policies and long-term planning
5. Discussions and Implications
Implications of vulnerability indicators
• Tools for monitoring adaptation policies and education
- some indicators are useful for monitoring mitigation policies as well as
adaptation measures
ex) open spaces and sustainable drainage etc.
- vulnerability map as tools for awareness raising and for promoting
participation by stakeholders in vulnerability assessment
• Vulnerability assessment based on past climate
observations
- lack of a reliable climate model at the local level
- high uncertainty involved
- vulnerability assessment needed based on projections of future
changes in climate
Limitations and further study
5. Discussions and Implications
• Further study is needed to explore the relationship between quantified assessment and actual local vulnerability
- complementary qualitative assessment and case studies are necessary
• Development of sectoral vulnerability indicators linked
with adaptation policies
- develop sector-specified vulnerability indicators for monitoring
adaptation strategies
- use of integrated indicators linking adaptation with mitigation
Limitations and further study
Thank You !