Innovations™ Magazine VII NO.3 2015 - ChineseT.D. Williamson
Welcome to the summer issue of Innovations™ Magazine, where industry experts from across the globe explore many of the pressing challenges — and successes — of pressurized piping operators.
OVER STORY: The Pervasive Menace
Helping the public be – and feel – safe, the pipeline industry develops, employs, and shares best practice corrosion detection and control methods.
FUTURE THINKING: More Stringent Safety Regulations
Preparing for NTSB compliance, U.S. transmission operators proactively seek safe and cost-effective options.
FEATURE STORY: Containing Catastrophe
Mitigating offshore oil and gas pipeline incidents, from dropped objects to pipe laying, through advancements in non-intrusive isolation technologies.
HIGHLIGHTS
TECHNOLOGY FOCUS
Turning Impossible into Piggable
Changing how we think about the integrity of low flow, low pressure lines with new low drag inspection tools.
SAFETY MATTERS
It Can Happen Here
Learning to cultivate “safety imagination” and benefit from “chronic unease” with Dr. Jan Hayes.
MARKET REPORT
Local Sourcing in the Eagle Ford
Supporting shale play profitability in a low price environment through localized pipeline services model.
BY THE NUMBERS
Four Steps to Battling Pipeline Integrity Threats
Detecting, characterizing, reporting, and prioritizing/mitigating threats to pipeline integrity with multiple dataset (MDS) inspection platforms.
Innovations™ Magazine VII NO.3 2015 - ChineseT.D. Williamson
Welcome to the summer issue of Innovations™ Magazine, where industry experts from across the globe explore many of the pressing challenges — and successes — of pressurized piping operators.
OVER STORY: The Pervasive Menace
Helping the public be – and feel – safe, the pipeline industry develops, employs, and shares best practice corrosion detection and control methods.
FUTURE THINKING: More Stringent Safety Regulations
Preparing for NTSB compliance, U.S. transmission operators proactively seek safe and cost-effective options.
FEATURE STORY: Containing Catastrophe
Mitigating offshore oil and gas pipeline incidents, from dropped objects to pipe laying, through advancements in non-intrusive isolation technologies.
HIGHLIGHTS
TECHNOLOGY FOCUS
Turning Impossible into Piggable
Changing how we think about the integrity of low flow, low pressure lines with new low drag inspection tools.
SAFETY MATTERS
It Can Happen Here
Learning to cultivate “safety imagination” and benefit from “chronic unease” with Dr. Jan Hayes.
MARKET REPORT
Local Sourcing in the Eagle Ford
Supporting shale play profitability in a low price environment through localized pipeline services model.
BY THE NUMBERS
Four Steps to Battling Pipeline Integrity Threats
Detecting, characterizing, reporting, and prioritizing/mitigating threats to pipeline integrity with multiple dataset (MDS) inspection platforms.
37. 3737
芬蘭:論文發表
the Second Nordic International Conference on Climate Change Adaptation,
Helsinki, Finland, 29-31; http://www.nordicadaptation2012.net/
德國:知識平台
Climate Service Center, Hamburg; http://www.climate-service-center.de/
德國:科技法律
Center for Environmental Research - UFZ;
http://www.ufz.de/index.php?en=11382
荷蘭:示範計畫
Delft University of Technology, Department of Urbanism;
http://www.bk.tudelft.nl/en/about-faculty/departments/urbanism/
日本:論文發表
International Conference on Science and Technology for Sustainability;
http://www.scj.go.jp/ja/int/kaisai/jizoku2011/program.html
英國:論文發表
Planet Under Pressure 2012; http://www.planetunderpressure2012.net/
美國:論文發表
ISA ANNUAL CONVENTION 2012; http://www.isanet.org/blog/2011/04/cfp-
isa-annual-convention-2012.html
荷蘭:洪水治理
UNESCO-IHE Institute for Water Education; http://www.unesco-ihe.org/
台灣:國際會議
International Symposium on Climate Change Adaptation Technology, 15
September 2012, Taiwan; http://taiccat2012.blogspot.tw/
菲律賓:糧食安全
International Rice Research; http://www.irri.org/
歐盟:評量系統
CLIMSAVE - climate change integrated assessment methodology for cross-
sectoral adaptation and vulnerability in Europe; http://www.climsave.eu
美國:論文發表
24th Annual Conference International Society for Environmental Epidemiology;
http://saeu.sc.edu/reg/isee2012/
38.
39. Regional climate
models
Agriculture and
forestry
Energy economics
Water
management
Coastal protection
Urban planning
and building
Education and
communication
Tourism
Traffic
3
9
2008 to 2014
7 joint regional projects
about 80 million €
42. 德國 UFZ:調適法規 荷蘭 Delft:空間規劃德國 CSC:氣候資訊
芬蘭 會議:成果發表荷蘭 Delft:研究交流德國 KomPass:知識平台
芬蘭 會議:IPCC-TaiCCAT交流德國 CSC:研究交流荷蘭 Delft:低地考察
IPCC
Richard Klein
TaiCCAT
江益璋
43. IPCC SREX Lead Author
Prof. Richard Klein 意見 (2012.9.28):
Judging from the information
provided (TaiCCAT poster), this is
a large and ambitious
programme.
It's good to see the emphasis on
governance, and the integration
with disaster risk reduction.
I would be interested in reading
more about the programme.
芬蘭 會議:成果發表
芬蘭 會議:IPCC-TaiCCAT交流
IPCC
Richard Klein
TaiCCAT
Yi-Chang Chiang
46. 氣象局程主任意見 (2012.9.16) (張靜貞老師提供):
CWB is trying to find partners in various
application areas to promote end-to-end
services. I believe TaiCCAT project would be a
very good partner that CWB could work with.
綜合討論
I do hope that TaiCCAT would so
like to cooperate with government
agencies and/or act as a bridge to
link government agencies
(supplier and consumer) together
for better decision making.
54. 這一年來的重要成果:
Urban heat Island
Landslide prediction model (Shihmen
Reservoir)
SST rise in Taiwan Strait
Environment & food security for mullet
fishery
Air-sea interaction for peng-hu cold
water intrusion
Land-sea interaction for sand reduce
55.
56. Urban Heat Island over Greater Taipei Region (GTR)
ISA
1990
Tb
1990
UHI
1990
ISA
1996
ISA
2005
Tb
1996
Tb
2005
UHI
1996
UHI
2005
(Landsat data used from 1990 to 2009)
57. +
Brightness temperature of test areas in different season(1999-2003)
U2
U1
U3
R1
R2
S3
R3
S1
S2
area1
area2
area3
•U1: Urban1
•U2: Urban2
•U3: Urban3
•S1: Suburban1
•S2: Suburban2
•S3: Suburban3
•R1: Rural1
•R2: Rural2
•R3: Rural3
(Size: 50x50 pixels)
•Forest
•Taipei metropolitan
spring summer winter
Taiwan 20.09 25.06 18.95
Urban 25.12 29.82 22.76
Plain 24.87 26.87 21.13
Tableland 22.4 23.87 20.71
Mountain 14.52 15.99 11.31
10
14
18
22
26
30
BrightnessTemperature(C)
Brightness temperature (Tb) in different season
58. 58
2012/2/23
Investigation of UHI and regional precipitation
2000
2100
2200
2300
2400
2500
2600
1987~19061907~19161917~19261927~19361937~19461947~19561957~19661967~19761977~19861987~19961997~20062007~2010
Year
precipitation(mm)
Urban Precipitation (1987~2010)
3
4
5
1961 1969 1977 1985 1993 2001 2009
Year
UHII(℃)
Taipei Heat Island (1972~2009)
1000
1500
2000
2500
3000
1940~1950 1950~1960 1960~1970 1970~1980 1980~1990 1990~2000 2000~2010
Precipition(mm)
4000
4500
5000
5500
Precipition(mm)
台北站 竹子湖站
Urban and Rural Precipitation
50 10 15 20 25 30 35 40 45 5050 10 15 20 25 30 35 40 45 50
120 E 122 E
MODIS/Terra
2000/07/14 03:10 UTC
25 N
23 N
℃ 50 10 15 20 25 30 35 40 45 5050 10 15 20 25 30 35 40 45 50
120 E
25 N
122 E
23 N
℃
MODIS/Terra
2008/07/24 0230 UTC
2000
38.7
36.3
31.1
36.1
36.9
28
30
32
34
36
38
40
LST(℃)
33.3
35.5
31.2
32.6
35.4
28
30
32
34
36
38
40
2000 2002 2004 2006 2008
Year
LST(℃)
Taipei City
Kaohsiung City
2008
~1990
60. 60
Land Surface Monitoring
Work Scopes
1. Statistical models for landslide and debris flow prediction: Following Lee et al.
(2008),we develop new models for landslide and debris flow prediction, and apply to
drainage basin of the Shihmen Reservoir and the Tsengwen River basin. Prediction
under extreme rainfall condition will be discussed also.
2. Soil depth estimation: We develop empirical formula for estimation of soil depth at
hill slopes by using local data. This formula will be used in estimation of sediment
budget and calculation of sediment transport.
3. Simplified method for estimation of sediment budget: Using results from
landslide prediction and soil depth estimation, we calculate sediment budget in each
drainage basin. This result can be used to compare with the result from our drainage
basin sediment transport system.
4. Geostatistical interpolation of rainfall parameters: Topographic data are joined
with rainfall data and a regression Kriging method is used to perform interpolation for
different rainfall parameters. These will be used in landslide and debris flow
prediction models and in the drainage basin sediment transport system.
5. Developing a drainage basin sediment transport system: Surface erosion and
channel transport mechanisms will be added in to a drainage basin hydrological
model to develop a sediment trasport system.
61. 61
Topographic data, hydrological data, geological data, landslide
and debris flow data, and landuse data
DEM
Geologic Map Active Faults
Landslides
Debris Flows
Land Surface Monitoring
Data Collections
62. 62
Topographic data, hydrological data, geological data, and landuse data, etc.
are processed and further used in establishing a statistical prediction model.
Rainfall Intensity
Slope Slope Roughness Profile Curvature NDVI Lithology
Relative Height TotalSlope Height Wetness Index DistancetoFault
Land Surface Monitoring
Data Analysis for landslide prediction model
63. 63
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1
0.6403
0.007587( )
1
slP
AUC=0.856
LS sus.index,λ
LSprob.,Psl
Landslide probability curve
for Typhoon Aere
Success rate for model Aere
Landslide probability map under
Aere rainfall
Portion of area
Succes
srate
Landslide probability map for Typhoon Aeret and for 100-year return
period rainfall at drainage basin of the Shihmen Reservoir (石門水庫).
Landslide probability map under
100-year return period rainfall
Land Surface Monitoring
Landslide Prediction model
64. Figure Distribution of oceanographic station data around Taiwan (>150,000 sts).
Mapped are all available data from the World Ocean Database‐2009, updated 2011‐04‐21. Shown are
only those stations that have both temperature (T) and salinity (S). Created by Daphne Johnson,
National Oceanographic Data Center, NOAA.
66. Multi-decadal variability of oceanic climate in the Taiwan Strait was studied using sea surface temperature
(SST), which is the most conveniently measured and frequently observed variable related to maritime
climate. We used the 1 degree x 1 degree monthly climatology of SST available from the U.K. Met Office
Hadley Centre. Between 1957 and 2011, three distinct regimes were identified. The first regime of fairly
stable or slightly cooling SST lasted through 1976. The regime shift of 1976-1977 led to a super-fast warming
of 2.1°C in 22 years, from 23.2°C in 1976 up to 25.3°C in 1998. Another regime shift occurred in 1998-1999,
leading to a 1.0°C cooling from 1998 to 2011. The spatial distribution of climate trends across the Taiwan
Strait was studied for the first time, revealing a strong spatial gradient along the Strait. In the north
(southern East China Sea), the magnitude and rate of the overall SST warming between 1957 and 2011 was
about three times those in the south (northern South China Sea).
67. Feeding
ground
Spawning
ground
Grey mullet
Caught around
Taiwan has
spawning and
nursery grounds in
the coastal waters
of southwestern
Taiwan, and
feeding grounds of
juveniles and
adults are located
in the coastal
waters of mainland
China about
between latitude
25 and 30 N
Grey mullet
It migrates into the
coastal waters of
west Taiwan
during the winter
solstice.
68. Question: The cause of the fluctuation and decline in
catch? Overfishing or Climate change ?
Year
Catch(103number)
0
500
1000
1500
2000
2500
3000
1968 1973 1978 1983 1988 1993 1998 2003 2008
Catch Mean
Since 1958 the annual catch of grey mullet has fluctuated greatly with a peak
of 2.54 million fish in 1980 and a minimum of 0.4 million fish in 1990 and 0.2
million in 2000 to 2004. In recent years, it has rapidly declined to about 45
thousands/year in 2007~2009, causing a concern to its management agency.
2.54 million
Overfishing (Huang et al., 2005)×
69. Cross-wavelet coherence between climatic index (a) annual PDO (b)
winter WPO (c) autumn ONI and (d) sea surface temperature with
log10 (grey mullet catches).
1958-1978 6–8 yr
8 yr
1–2 yr
2–3 yr
70. Annual trends of (a) grey mullet catches (black line) and PDO (grey
line) and (b) winter SST (black dotted line) from 1958 to 2009.
The annual PDO, the time
series trends of annual catches
and PDO showed a fairly good
correspondence
A declining trend of the
fluctuation in catches and
raised trend in winter SST after
1980s
The PDO might play a role in affecting the grey mullet migrated but the increased
of SST would also an important reason caused the decreased and low catches of
grey mullet after 1980.
71. The catch percentage of grey mullet caught
by the Taiwanese fishing boats and collected
from the local fisherman associations in the
west coast of Taiwan (a) 1978–1987 (b)
1988–1997 and (c) 1998–2009.
More than 85%
of grey mullet
was caught in
the south of
23.5°N in 1978–
1987 in the
eastern Taiwan
Strait.
In 1988-1997, the fishing
grounds moved to north
and more than 30% grey
mullet was caught in the
latitude of 24.5°N where
was the low catch fishing
ground in 1978–1987,
while the parts of fishing
grounds moved to north
of 25°N after 1998–2008
72. The latitudinal variation of the 20 °C isotherm of 1958–
1967 (purple line), 1968–1977 (brown line), 1978–1987
(green line), 1988–1997 (blue line), 1998–2009 (Red
line), and the IPCC A2 scenario in SSTs of 2050 and
2075 (grey lines) in the western Taiwan in winter.
There is a consistency of
north shifted between
the grey mullet fishing
grounds and the
latitudinal variation of the
20 °C isotherm of
western Taiwan in winter,
while the 20 °C isotherm
moved to north of 25°N
of the western Taiwan
after 1998.
The scenario results shows the 20
°C isotherm of wintertime in the
west Taiwan will move to 25.5°N in
2050 and cross the 26°N in 2075.
The results suggested the climate
change caused the increased of
SST and weaken the intrusion of
the Coastal Current into the Taiwan
Strait. Moreover, the phenomena
might decreased the abundance of
mullet migrated into western Taiwan
and shifted the fishing grounds to
north part.
Environment- Food security
73. Air-Sea interaction for observation on Fisheries and Mariculture impact
by Extreme Oceanic Environmental Changes in Taiwan
The fishery resource (included cobia and grouper )
disaster with the economic fishery losses about NT$350
million (US$ 11 million) in February 2008.
It suggested that the continuous strong wind might have driven
the cold current more southeasterly to the southern TS and
resulted in the great drop in SST.
74. Sand area in 2009 is smaller
40 % than that in 2012.
FS2 Image (2m)
2009/09/01
2010/09/26
2011/09/30 2012/06/28
Year 2009 2010 2011 2012
Area
(Ha) 5.59 5.15 3.43 3.40
THE TAICCAT CONFERENCE 09/15 2012
75. 未來工作之預期產品:
Urban heat island (UHI) and land use index
Landslide prediction model in Zengwun
Reservoir
Ocean warming variability and micro-climate
SST index
Dry/flooding, Coast erosion and inundation
index in Chianan Plain.
Ci-Gu wetland/Lagoon habitat biodiversity
76. 環境組整合運作方式:
就不同空間類型進行組內資料整合與變遷指標分析;例如:
- 五都之UHI and land use (大氣與陸地資料整合)
- 曾文水庫邊坡崩蹋預測模式(地質與脆弱度-河川水文資料與模
式整合)
- 澎湖離島之大氣海洋交互預警模式與漁業糧食安全及調適策
略分析
- 嘉南平原旱澇指標(大氣與海洋及TCCIP資料整合分析)
極端環境或微氣候變遷的加值資料分析;例如:
- 提供在極端氣候-颱風之影響下的流域(含水庫) 崩蹋預測模式
- 提供嘉南平原旱澇指標的週期變動加值分析
80. 與過去研究或現在其他單位計畫之差異:
CCliCS for model development & Scenario and TCCIP for
down-scaling and historical data bank. EA: Focus on Micro-
climate change and value-added data analysis.
回應部會不同面向(如多樣性與海岸帶管理)所需指標之分析
透過TCCIP, 總計畫,環境組,脆弱度及調適治理之整合,可針對極端
環境或微氣候變遷所帶來的衝擊,提出適切回應;例如:
- 颱風過後(環境面向-大氣,陸地,海洋與海岸),對養殖漁業(糧食與
衛生安全)造成衝擊,而後續的補償措施(調適治理)
- 澎湖冷水入侵(環境面向-大氣海洋)之微氣候變遷造成沿岸漁業
及養殖漁業(糧食與衛生安全)造成衝擊, ,而後續亦可有適當的
調適措施(調適治理)
81. After typhoon, the oyster
aquaculture raft was
damaged by heavy flooding.
FS2 Image (2m) of 2012/06/08
2012/06/28
Before typhoon, the oyster
aquaculture raft was
easily identified by
Formosa image.
FS2 Image (2m) of 2012/06/08
82. -40
-20
0
20
40
60
80
100
120
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Day of wind speed > 6 m/s
Distanceof20ºCisobath
referringtoPHI(km)
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
Dayofwindspeed>6m/s
Micro-climate case: Warning system of Fisheries and Mariculture
to Extreme Oceanic Environmental Changes in Taiwan
-60
-40
-20
0
20
40
60
80
100
<6 7~12 13~18 >19
Period (day)
Distanceof20isobath
referringtoPHI(km)
The fishery resource
(included cobia and
grouper ) disaster with
the economic fishery losses
about NT$350 million
(US$ 11 million) in
February 2008.
83. In 2008 In 2011
More than 1600 and 1000 tons of cage aquaculture fish
perished in 2008 and 2011.
http://blog.roodo.com/upupph/archives/15140175.html
Data Source: Central Weather Burial, Taiwan
Cobia, Black king fish
(Rachycentron canadum)
Sea Surface Temperature in PHI,
2011.
84. Flowchart of the decision-making process
for cage aquaculture adaptation.
(Marine policy, accepted in 2012)
125. Methodology
- Based on UN Definitions:
Risk = Element at Risk* Natural Hazard* Vulnerability
Element at Risk: Whether staple production meets demand
Vulnerability: Number of events, Econ loss, Population affected
Resilience: Per capita income per year
- Ranking Criteria :
(1) number of disaster per year;
(2) percentage of population affected per year;
(3) percentage of economic losses in GDP per year;
(4) per capita income per year.
Three rankings from different
summations, i.e.,
(1)+(2)+(4), (1)+(3)+(4), (1)+(2)+(3)+(4)
Integrated Risk Assessment: Risk Profile of Taiwan
126. Country
Number of
Disaster
per year (1)
% of
Population
Affected (2)
% of Econ
Losses in GDP
(3)
Per Capita
Income (4)
(no.) score (%) score (%) score (US$) score
Australia 4.6 1.95 0.28 1.13 0.25 1.37 52,273 1.00
Brunei 0 1.00 0.00 1.00 0.00 1.00 32,049 2.30
Canada 2 1.41 0.00 1.00 0.01 1.01 45,132 1.14
Chile 2.2 1.45 3.54 2.61 3.34 5.00 11,074 4.14
China 23 5.00 8.76 5.00 0.60 1.88 3,871 4.78
Hong Kong 1 1.21 0.04 1.02 0.00 1.00 31,208 2.37
Indonesia 13.2 3.72 0.41 1.19 0.14 1.20 2,585 4.89
Japan 4.4 1.91 0.10 1.04 0.88 2.29 40,100 1.59
Rep of Korea 1.2 1.25 0.02 1.01 0.00 1.00 20,486 3.31
Malaysia 1.6 1.33 0.15 1.07 0.10 1.15 7,785 4.43
Mexico 6.4 2.32 0.91 1.41 0.20 1.30 9,708 4.26
New Zealand 0.8 1.16 2.93 2.34 2.51 4.67 31,904 2.31
P N Guinea 3.2 1.66 0.84 1.39 0.00 1.00 1,357 5.00
Peru 3.2 1.66 1.74 1.80 0.09 1.13 4,681 4.71
The Philippines 19.4 5.00 8.00 4.65 0.25 1.37 1,962 4.95
Russia 2.6 1.54 0.01 1.01 0.05 1.08 10,599 4.19
Singapore 0 1.00 0.00 1.00 0.00 1.00 40,911 1.51
Taiwan 2.2 1.45 2.02 1.92 0.07 1.11 18,194 3.52
Thailand 4 1.82 11.71 5.00 2.74 5.00 4,529 4.72
USA 16.4 4.38 0.94 1.43 0.16 1.23 46,745 1.00
Viet Nam 6.8 2.40 2.05 1.94 0.74 2.08 1,097 5.00
Natural Disaster Risk in APEC, 2007-2011
Data Sources: EM-DAT DB, FAOSTAT, IMF (World Economic Outlook Database, September 2011)
127. Country Average score
of (1)+(2)+(4)
Ranking LEVEL
Average score of
(1)+(3)+(4)
Ranking LEVEL
Average score of
(1)+(2)+(3)+(4)
Ranking LEVEL
(1) (1) (1) (2) (2) (2) (3) (3) (3)
Australia 1.36 19 L 4.31 18 L 5.44 18 L
Brunei 1.43 18 L 4.30 19 L 5.30 19 L
Canada 1.19 20 L 3.56 20 L 4.57 20 L
Chile 2.74 6 H 10.60 4 H 13.21 4 H
China 4.93 1 H 11.66 1 H 16.66 1 H
Hong Kong 1.53 16 L 4.58 17 L 5.60 17 L
Indonesia 3.27 4 H 9.81 5 H 11.00 6 H
Japan 1.51 17 L 5.78 15 L 6.83 15 L
Rep of
Korea
1.86 15 L 5.56 16 L 6.57 16 L
Malaysia 2.28 11 L 6.91 11 M 7.98 13 M
Mexico 2.67 9 M 7.88 8 M 9.30 8 M
New
Zealand
1.94 14 M 8.14 7 H 10.48 7 H
P N Guinea 2.68 8 M 7.66 9 M 9.05 10 M
Peru 2.72 7 H 7.50 10 M 9.29 9 M
Philippines 4.87 2 H 11.32 3 H 15.97 3 H
Russia 2.24 13 M 6.80 12 M 7.81 14 M
Singapore 1.17 21 L 3.51 21 L 4.51 21 L
Taiwan 2.30 10 M 6.08 14 M 8.00 12 M
Thailand 3.85 3 H 11.55 2 H 16.55 2 H
USA 2.27 12 M 6.61 13 M 8.04 11 M
Viet Nam 3.11 5 H 9.48 6 H 11.42 5 H
Natural Disaster Ranking in APEC, 2007-2011
128. Governance and Institutional Framework
Information and Knowledge Platform
Education and Training
Integrated Risk Assessment: Capacity Building
129. Successful Adaptation requires
- Scientific knowledge of climate change
and vulnerability
- Systematic monitoring of climate,
ecosystem, and social-economic impacts
- Long-term planning for infrastructure
- Public education to encourage collective
actions
- Enforcement on proper societal
adjustment and practices
Design Analytical Framework: Key Elements
132. 132
1. Stochastic
Event Module
3. Vulnerability
Module
2. Hazard
Module
4. Financial Loss
Module
Overall Framework of
Flood Risk Engineering
Model
Case Study: Flood Risk
133. - Policy Options
Land Use Planning
Building Code
Disaster Relief
Insurance Program
- Financing
Calculate premiums under different
assumptions on take-up rate.
Government’s bottom-layer coverage are
assumed as premium subsidy.
133
135. Major Findings
- Government involvement is needed to increase
the amount of flood insurance in force
- Future Work Needed on Modeling
Predictions and detection of large-scale natural disasters
Integrate climate/hydrology/socio-econ database
Improve flood hazard maps
Collect risk mitigation/ flood exposure data
Upgrade/calibrate risk assessment model
Design of multi-peril assessment model
136. Policy Options –A Tool Box
- Farm Level:
Diversification, insurance
Add value to move away from raw product
Adopt agricultural research
- Supply Chain level:
Add value by moving up value chain
Improve food research
Invest in better infrastructure
New distribution methods (network v.s. hub and spoke)
- Policy/Market level:
Hedging options, price pooling,
Food reserves
Insurance tools
Information (monitoring, early warning)
136
Case Study: Food Security Risk
137. • APEC Food Emergency
Response Mechanism
• Purpose
• As an Insurance
Pool for large risk
• Reduces public
expenditures on
expanding food
reserves for natural
disasters.
• Risk Assessment
138. CBA for Rice under Different Options
Data Source and Per Capita Consumption Target
Calculation 3-Month 2-Month 1-Month
1. Rice
TOTAL BENEFIT (ANNUAL)
(1) Food Aid Needs in MT Table 4-6 2,662,873 1,775,098 887,624
(2) Marginal Value per MT in GDP Appendicx C-1 544.52 544.52 544.52
(3) Marginal Value per MT in Welfare Appendicx C-1 535.86 535.86 535.86
(4) Total Benefit in GDP (Mil US$) (4)= (1)*(2) 1,449.99 966.58 483.33
(5) Total Benefit in Welfare (Mil US$) (4)= (1)*(3) 1,426.94 951.21 475.65
TOTAL COST (ANNUAL)
(6) Market Price per MT Appendix C-1 333.56 333.56 333.56
(7) Total Procurement Cost in Mil US$ (7)=(1)*(6) 888.22 592.09 296.07
(8) Total Adminstration Cost in Mil US$ Table 2-1 0.18 0.18 0.18
(9) Total Logistic Cost in Mil US$ (9)=(7)*0.27 239.82 159.87 79.94
(10) Total Cost (Mil US$) (10)= (6)+(7)+(8)+(9) 1,128.22 752.14 376.19
Benefit-Cost Ratio
(11) in GDP (11)= (4)/(10) 1.285 1.285 1.285
(12) in Welfare (12)=(5)/(10) 1.265 1.265 1.264
139. • Great variety of options available to make society more
resilient to climate risks
• Many components should included
- Private actors as well as Public policy
- National effort or with International cooperation and
coordination
- Risk reducing/sharing as well as income/efficiency
enhancing measures
• Most policies require careful, critical appraisal before
being accepted
• Need analytical tools
• Need to collect information
How to deploy and use them adequately and
effectively?
Conclusions
140. 總計畫 評估組
環境組 治理組
謝謝聆聽
總計畫 評估組
環境組 治理組
氣候變遷調適科
技整合研究計畫
Taiwan integrated research program on
Climate Change Adaptation Technology