Risk Awareness and Perceptions after Typhoon Morakot: Community-based Survey on Residents’
Response and Preparedness for Future Climate Chang in Tainan City
Dr. Ya-Pin Lyu
Project Assistant Researcher
APEC Research Center for Typhoon and SocietyTaiwan Typhoon and Flood Research Center
National Applied Research Laboratory
Outline Introduction Community-Based Survey Research
Tainan as the Research Target City Survey Structure Sampling Areas Survey Results Factors Motivating Household Mitigation Actions Logistic Regression of Household Mitigation Actions Could Community Supports Motivate Household Actions? What do We Learn?
The Promotion of Weather Forecast in Household Decisions Benefits Revelation for Advanced Weather Forecast Technology
Concluding Remarks Future Works
Introduction
Background• The history record has shown that Taiwan
is a disaster-prone island hit mainly by typhoons and floods. – According to government statistics, an average
of 4.9 typhoons hit Taiwan every year during the period 1958~2007, 3.5 of which caused damages.
– Even though there is a slightly increasing trend of typhoon frequency, we are not sure about the whether we will experience more typhoon in the future.
1972-1976
1977-1981
1982-1986
1987-1991
1992-1996
1997-2001
2002-2006
2007-2011
0
1
2
3
4
5-Year Average
Table 2: Natural Disaster Losses and Insurance Reimbursement
Year Natural Disaster
Economic Losses (USD
million)
Insurance Reimbursement
(USD million)
ReimbursementRate+
( %)
1999 Chi Chi Earthquake 11,894 486 4.03%
2001 Tropical Storm Toraji 256 17 6.51%
2004 Typhoon Mindulle 447 10 2.23%
2009 Typhoon Morakot 6,661 76 1.24%
Data Sources: Chi-Chi Earthquake Post-Disaster Reconstruction Committee, Typhoon Morakot Post Disaster Reconstruction Committee, the Non-Life Insurance Association of the R.O.C., Munich Reinsurance Company, and Willis Re
Background
Damage Losses During Typhoon MorakotLosses Items Dollar Amount
( billion NTD)1. Monetary Losses 199.83(1) Direct Losses 189.68
a. Household Damage 5.31b. Household Construction and Equipment Damage Losses
4.34
c. Industrial Direct Losses
27.35
① Agriculture 19.40② Industrial 2.33③ Business 1.18④ Traveling 2.18⑤ Aborigine 2.26
d. Public Infrastructure 152.68(2) Indirect Losses 10.15
① Agriculture 8.16② Industrial 0.59③ Business 1.40
2. Nonmonetary Losses: Death and Missing Toll
699
Damage Losses in Typhoon Morakot( billion NTD)
Household Damage Household Construction and Equipment Damage Losses
Industrial Direct Losses Public Infrastructure Indirect Losses
The Total Damage Losses are around 6.6 billion USD
A Long Way Toward Recovery and Reconstruction for households and local Industries
Could we reduce damage losses and speed up recovery via encouragement of household preparation works? And how?
Bottom up or Top down:Could we encourage actions at community scale ?
Research Objectives According to United Nations Office for Disaster Risk Reduction (UNISDR), preparedness works
before catastrophes determine recovery speed of a society thereafter.
Buttom-up or top-down risk management? The responsibility of top-down and bottom-up risk management strategies should be
clarified. They should be coordinated with each other. Top-down risk management might suffer a lack of local viewpoints and thereby
emergency responses could not be as instant as we expected. Local strategies should be initiated via bottom-up approach by integrating stakeholders’
viewpoints in decision process.
This research tries to start with a community-based survey and based on which we could figure out several cures for the increasing trend of future damage losses compounded by climate change.
The inventory survey on capacity and mitigation/adaptive needs Do high risk perceptions encourage residents’ autonomous mitigation actions? Are they sufficient in capacity to prepare for future hazards? What residents need in preparedness work?
Community-Based Survey Research
Tainan as the Research Target City
• For recent decade since 1996, Tainan city ranks top 6 counties in terms of disaster losses for 7 times across top 10 typhoon events.
• Tainan is one flood-prone city in which each year residents experienced numbers of small- and large-scaled floods for their low terrain near river basins and coastal areas.
History: Top 5 Counties Suffering Severest Damage During Typhoon Morakot
Typhoon Morakot
County Household Damage(NTD)
Damage/Monthly Income
Savings per Household
Nantou County 473,779 (5) 1.87 158,227
Chiayi County 836,424 (2) 2.99 107,954
Kaohsiung County 652,632 (3) 2.70 213,404
Pingtung County 359,403 (6) 1.61 180,197
Taitung County 956,333 (1) 4.05 183,777
Tainan City 145,370 1.33146,406
Tainan County 396,396 3.05 (2) (4)
Future: Worldwide Top Risky Cities in Storm Hazards
According to Swiss Re’s risk assessment (2013), Tainan ranks top 10 risky cities among 616 worldwide urban
areas in storm hazards .
Residents’ lives, health, properties, and physical
assets are exposed to gradually higher risks under climate change
Survey Structure: Risk Perception, Household Mitigation/Adaptive Needs and Actions
under Climate Change
Part 1. Demographic Characteristic of Sample
Part 2. Past Natural Disaster Experience
Part 3. Risk Perceptions
Part 4. Mitigation and Adaptive Actions
Part 5. Capacity Survey
Sampling Districts in
Tainan
Survey Result: Typhoon Hazards in History
16%
36%21%
10%
10%1%
3% 1% 3%
Inundation Depth
<0.5m0.5m-1.0m1.0m-1.5m1.5m-2.0m2.0m-2.5m2.5m-3.0m3.0m-3.5m
37%
32%
22%
2% 1%3% 3%
Inundation Duration
1 Day 2 Days
3 Days 4 Days
5 Days 6 Days
7 Days Missing
Survey Result: Social Impacts
Life T
hreat
Contagious D
isease
s Threa
t
Household Constr
ucture
and Eq
uipment D
amag
e Losse
s
Agricu
ltural
Damag
e Losse
s
Business
Running Losse
s
Psychologic
al Dist
ress
No Influen
ce
Inconve
neient L
ife0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
28.83%
40.99%
85.59%
22.52%16.22%
56.76%
1.35% 0.45%
Survey Result: Household Mitigation Actions Before Typhoon Hits
1%8%
51%
39%
2%
Effectiveness of Household Mitiga-tion Actions
pretty bad bad
neutral good
very good
Earth
bag pilin
g
Install w
ater r
etaining p
late
Move pro
perties
to higher
place
Clear d
rainag
e
Add height fo
r furn
iture
Tape t
he window
Install w
aterti
ght g
ate
Close window
Install I
nundation in
specti
on senso
r
Food prep
aration
Others0.00%5.00%
10.00%15.00%20.00%25.00%30.00%35.00%
22.1%
8.3%
31.7%
9.0%
20.7%
0.7%5.5%
15.2%
0.7% 0.7%5.5%
Actions to Mitigate Losses
Survey Result: The Priority of Policies to cope with Household Mitigation Actions
Pretty L
ow Priorit
y
Low Prio
rity
Neutra
l
High Prio
rity
Extre
mly High
Priorit
y
Missing
0.30% 8.20%23.80%
52.70%
12.60%2.40%
Information Platform (4)
0.30% 8.20%23.50%
44.90%
20.40%2.70%
Urban Spacial Planning
0.30% 1.70% 9.20%
43.50% 43.90%
1.40%
Resources support for Emergency Responses (2)
0.00% 2.40%14.60%
49.30%31.00%
2.70%
Household Loans in Construction to Mitigate Damage Losses (3)
Pretty L
ow Priorit
y
Low Prio
rity
Neutra
l
High Prio
rity
Extre
mly High
Priorit
y
Missing
1.00%
15.30%
33.30% 35.70%
12.20%2.40%
Flood Insurance
Pretty L
ow Priorit
y
Low Prio
rity
Neutra
l
High Prio
rity
Extre
mly High
Priorit
y
Missing
0.00% 2.00% 4.80%
47.60% 43.90%
1.70%
Contagious Disease Control and Hygiene Condition Promotion (1)
Capacity Build-up and Community Support
Community Dev
elopmen
t Cen
ter
Real-T
ime D
amag
e Rep
orting S
ystem
Disaste
r Prev
ention Knowled
ge Diss
eminati
on
Materia
ls Prep
ared fo
r Disa
ster P
reven
tion and M
itigation
Disaste
r Emerg
ency
Responses
Post-Disa
ster R
elief
and Su
pport
Support
for Reco
very
others
76.90%
44.20%
13.30%4.10% 6.80% 6.80% 3.10%
9.20%
Community Support
The Possible Factors Motivating Household Mitigation Actions
Personal Characteristics Education, Personal Income, Household Income Risk Perception, Past Disaster Experience, Concerns, Responsibility
Hazards of Living Environment Terrain, Household Distance to River, Costal Line
Outer Resources and Supports Scientific Knowledge and Risk Communication Disaster warning Issuance (e.g. Heavy Rain and Flood Warning) Community Support Financial Support Policy Strategies
Logistic Regression-CoefficientsTook Mitigation Actions
or NotUse Early Flood Warning APP
Constant 0.00(0.00)
0.00(0.00)
Education (in log) 0.39*(0.21)
1.07(0.80)
Personal Income (in log) 2.32(2.57)
1.80(3.31)
Household Income (in log) 2.34**(1.03)
3.11*(2.50)
Past Disaster Experience 0.99(0.01)
1.68***(0.31)
Risk_Perception_Probability_River Area 0.99(0.85)
--
Risk_Perception_Probability_Costal Area 1.05(0.51)
4.78***(2.82)
Responsibility_Shared_Agree 3.59***(1.36)
0.92(0.52)
Responsibility_Share_Low 0.16*(0.20)
2.29(2.94)
Responsibility_Shared_Middle 0.31(0.39)
0.49(0.63)
Risk_Perception_Property 2.47*(1.26)
1.23(0.93)
Risk_Perception_Agriculture_Losses 1.39(0.53)
0.24** (0.15)
Risk_Perception_Psychological_Distress 0.62(0.27)
1.43(0.96)
Observation 206 177
Logistic Regression -Marginal EffectsTook Mitigation Actions
or NotUse Early Flood Warning
APPEducation (in log) -0.22*
(0.12)0.00
(0.07)Personal Income (in log) 0.19
(0.26)0.05
(0.18)Household Income (in log) 0.20**
(0.10)0.11*(0.07)
Past Disaster Experience -0.00(0.00)
0.05***(0.02)
Risk_Perception_Probability_River Area
-0.00(0.20)
--
Risk_Perception_Probability_Costal Area
0.01(0.11)
0.23**(0.12)
Responsibility_Shared_Agree 0.30***(0.08)
-0.00(0.05)
Responsibility_Share_Low -0.39*(0.23)
0.08(0.14)
Responsibility_Shared_Middle -0.27(0.28)
-0.07(0.14)
Risk_Perception_Property 0.22*(0.12)
0.02(0.08)
Risk_Perception_Agriculture_Losses 0.08(0.09)
-0.12*** (0.04)
Risk_Perception_Psychological_Distress -0.10(0.09)
0.04(0.07)
Observation 206 177
Market Failure Problem
More active mitigation actions are found for those who have higher household income, who agree more to take responsibility of preparedness work, and who perceive higher risk in properties under climate change.
Residents who feel psychological distress don’t guarantee their actions to prevent or mitigate damage losses. What’s wrong?
The importance of Financial and Knowledge Capacity Build-up: Could we reinforce our capacity in terms of social resilience via better
utilization of community resources and via promotion of communities activities?
Low income residents who live in flood hotspot areas might suffer from deficient capacity such that autonomous mitigation
actions and preparedness works are inactive
Could Community Support Motivate Household Actions?
Took Mitigation Actions or NotCoefficient Marginal Effect
Education (in log) 0.32**(0.19)
-0.26(0.13)
Personal Income (in log) 3.30(3.64)
0.27(0.25)
Household Income (in log) 2.68**(1.33)
0.23**(0.11)
Past Disaster Experience 1.08(0.10)
0.01(0.02)
Responsibility_Shared_Agree 4.02***(1.67)
0.33***(0.09)
Risk_Perception_Property 1.71(0.95)
0.13(0.13)
Risk_Perception_Agriculture_Losses 0.92(0.39)
-0.01(0.10)
Community_Resources (1)Community_Development_Center
5.26***(2.67)
0.39***(0.10)
Community_Resources (2)Instant_Disaster_Notification_and_Reporting
1.31(0.49)
0.06(0.08)
Community _Resources (3)Scientific _Risk_Knowledge_Dissemination
1.55(0.93)
0.09(0.12)
Community_Resources (4)Emergency Responses and Rescue Support
13.12**(18.80)
0.35***(0.08)
Community_Resources (5) for_Preparedness_Work
6.25(8.64)
0.29**(0.12)
Observation 201 201
What Do We Learn? Community resources provided to support preparedness works could
motivate residents’ mitigation actions such as setup of community development centers, resources prepared for emergency response and rescue actions.
The functioning of dissemination of scientific knowledge, risk information, and disaster dynamics is under development so far at community scale in terms of application in catastrophe preparedness works.
The consideration of cost spent to mitigate damage losses is one important determinant in household decision whether they will take actions or not.
Strategies to against future hazards or cope with climate change at community scale should be formed to meet local needs in the future via reinforcement of risk communication, and risk education to facilitate scientific knowledge dissemination through community activities.
The Promotion of Weather Forecasts Utilized in Decisions related with Preparedness Works
According to IRI (2012), risk management should fully utilize weather and climate forecasts in disaster prevention and mitigation works. More accurate weather forecasts could
encourage prevention/mitigation activities, and thereby effectively reduce damage scale and speed up recovery works.
Several ways to promote advanced weather forecast in government agencies’ and households’ decisions, including Provide weather forecast knowledge and
more accurate forecast services Promote development of advanced weather
forecast techniques Reveal benefits of advanced weather
forecast to the public
Motivate Actions
Avoid Unnecessary
Damage Losses
More Efficient
Allocation for Resources
Advanced Typhoon Forecast
Techniques
Lower Damage Losses
Benefits Revelation for Advanced Weather Forecast Technology
According to our estimation, reduced forecast errors in typhoon track by 1 km would reduced damage by 0.14 billion NTD (4.6 million USD) in agriculture, 0.10 billion NTD (3.3 million USD) in household, 0.62 billion NTD (20.6 million USD) in industrial and
business sectors, The total direct benefits are around 0.86 billion NTD per kilometer (28.6 million USD/km)
Such revelation could help promote development of advanced weather forecast and further application in all aspects of decisions.
The Benefit of Advanced Weather Forecast
Techniques
Agriculture
Industrial/BusinessHousehold
Future WorksThe Core Works of ACTS Core Research:
to reinforce research capacity in typhoon studies
promote the application and utilization of advanced weather forecast technique via benefit assessment
Promotion and Application: to collaborate with NCDR and NCREE in build-up of evaluation indicators
Information Exchange: to hold international conferences and workshops to reinforce communication, knowledge exchange, and experience sharing
International Cooperation:to collaborate with native and international research institutes to work on social economic assessment of typhoon events
Thanks