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9/3/2009
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Assessment of Coastal Vulnerability to Sea Level Rise in Southeast Asia:
Some Management Considerations
LOICZ SEAsia REGIONAL NODE
Beverly Goh
“INTEGRATED VULNERABILITY ASSESSMENT OF COASTAL AREAS IN THE SOUTHEAST ASIA AND EAST ASIAN REGION”
INTERNATIONAL SECRETARIAT
NSSE, National Institute of Education, NTU
Coastal Vulnerability Assessment
June 2005 LOICZ 16th SSC and Inaugural OSM
DIVA
http://diva.demis.nl
DIVA is a program developed by DINAS-COAST project.
The program aids in making a dynamic and interactive assessment of the vulnerability of coastal zones to climate change and sea-level rise at the national, regional and global scales.
It uses inputs from biophysical and socioeconomic data, which can be defined/specified by the user to create various scenarios.
The IPCC Special Report on Emission Scenarios Storylines(4th IPCC Report). Highlighted in red - scenarios with the highest predicted carbon production from fossil combustion.
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High Loss of Doing Nothing!
e.g. Migration due to land loss
A1HRtype of mitigation-NO NOURISHMENT
annual average 1-3 thousand
NO. 1 of the IPCC SRES storylines
HIGH Sea Level Rise
REGIONALIZED analysis
1 2 3 5
economic
1,2,3 5
environmental
regional
global
4 6
IPCC SRES storylines
exponential increase
“Sea Walls/Dikes” are good options
• people actually flooded• land loss due to submergence• sea flood costs
no nourishment
e.g. people actually flooded
10 yr protection mode
e.g. sea flood costs
Effectiveness of “Sea Walls/Dikes” depends onadministrative unit level
min 10-yr protection
min 100-yr protection
min 1000-yr protection
min 10000-yr protection
In SEAsia Full Beach Nourishment is better
no nourishment
• preservation of• wetland area• coastal forest• mangrove
• minimize • net land loss due to
erosion• sand loss total• migration due to land loss
e g net land loss due to erosion
full nourishment
e.g. net land loss due to erosion
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Full Beach Nourishment option also wins in cost and benefit analysis
total adaptation COST BENEFIT – total wetland area
full nourishment
“full” protection mode
No effective mitigating measures for salinity intrusion
HIGH
Sea Level Rise affect magnitude of loss and costs e.g. Net Loss of Wetland
SEAsia Indonesia
MEDIUM
LOW
Country-specific response toadaptive strategy
2500
3000
3500
4000
4000
5000
6000
7000
e.g. Net Land Loss due to erosion e.g. mitigation measure “dikes”
PHILIPPINES, VIETNAM & THAILAND
0
500
1000
1500
2000
1 2 3 4 5 60
1000
2000
3000
1 2 3 4 5 6
MALAYSIA
35000350
400
INDONESIA
0
5000
10000
15000
20000
25000
30000
1 2 3 4 5 6
0
50
100
150
200
250
300
350
1 2 3 4 5 6
CAMBODIA & SINGAPORE
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4
250
300
350
400
2
2.5
3
0
50
100
150
200
250
1 2 3 4 5 6
CAMBODIA SINGAPORE
0
0.5
1
1.5
1 2 3 4 5 6
existing situation
Length of the coast
Coastal floodplain area
Coastal floodplain population
Total wetland area
Coastal forest area
Low unvegetated wetlands area
Mangrove area
Saltmarsh area
DISCO
http://fangorn.colby.edu/disco-devel/main.php
DISCO is an on-line data analysis tool for performing cluster analysis and
l t d ti
relative sea level rise
Total residual damage costs
Land loss costs
Mi ti (d t l d l ) t
cost of doing nothing
2000 2040 2080
2010 2050 2090
2020 2060 2100
2030 2070 x
related operations.
Cluster analysis is an important tool for discovering structure in complex data sets.
effect on coast by 2100
Land loss (submergence)
Net land loss (erosion)
Migration (due to land loss)
Net loss of wetland area
People actually flooded
Sand loss total
Migration (due to land loss) costs
Results of cluster analyses
VIETNAM HIGH coastal floodplain population
0. 9
1
A HIGH INCREASE in relative sea level change at 2040 for the low SLR scenario& at 2100 for the med and high
A HIGH total residual damage cost at 2010 & 2040 and a MEDIUM migration (due to land
2000 2010 20202030 2040 2050
2060 20702080 2090
2100
LOW
HIGH
0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0. 8 LOW
MEDI UM
HIGH
a MEDIUM migration (due to land lost) at 2040 & 2100
A HIGH land loss (due to submergence), HIGH net loss of wetland area, & HIGH people actually flooded by 2100
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MALAYSIA & THAILAND
MEDIUM coastal floodplain population
A HIGH INCREASE in relative sea level change at 2030 & 2040 for the low scenario& A MEDIUM INCREASE at 2100 for the med and high
A MEDIUM total residual damage (TRD) cost and land loss (LL) cost 0.9
1
( ) ( )at 2010 and a HIGH TRD and LL costs at 2040 A LOW land loss (due to submergence), MED net loss of wetland area, & MED people actually flooded by 2100
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
LOW
HIGH
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8 LOW
MEDIUM
HIGH
PHILIPPINES
MEDIUM coastal floodplain population
A HIGH INCREASE in relative SLC at 2030 & 2040 for the low,A MEDIUM at 2100 for the med, & A HIGH at 2100 for the high
A LOW total residual damage (TRD) cost at 2010 and a MEDIUM l d l d i ti
0.9
1
LOW MEDIUM land loss and migration costs at 2040 & 2100
A LOW land loss (due to submergence), MED net loss of wetland area, & MED people actually flooded by 2100
LOW
HIGH
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
LOW
MEDIUM
HIGH
MEDIUM coastal floodplain population
CAMBODIA & SINGAPORE
A LOW INCREASE in relative sea level change 2040 &2100 for all the scenarios
A LOW total residual damage (TRD) cost at 2010 & 2040 and a MEDIUM land loss and migration
NO Land Loss Cost for Singapore
costs at 2040 & 2100
A LOW land loss (due to submergence), MED net loss of wetland area, & MED people actually flooded by 2100
LOW
HIGH
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
LOW
MEDIUM
HIGH
HIGH coastal forest and mangrove area
INDONESIA
A LOW INCREASE in relative sea level change 2040 &2100 for the low & a MEDIUM INCREASE at 2100 for the medium and high scenarios
A HIGH land loss costs through the years, a MEDIUM–HIGH total residual damage (TRD) cost from 0.9
1
2010 to 2040 and a MEDIUM- HIGH migration costs from 2040 to 2100
A HIGH land loss (due to submergence) and net loss of wetland area by 2100 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
LOW
HIGH
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8LOW
MEDIUM
HIGH
c
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Total residual damage cost prediction for the year 2100 using a high sea level rise scenario
12000
14000
nourishmentno adaptive measure
0
2000
4000
6000
8000
10000
12000
Thai
land
Indo
nesi
a
Viet
Nam
Mal
aysi
a
Sin
gapo
re
Phili
ppin
es
Cam
bodi
a
100 year CBA-dike10 year CBA-dike
nourishment0
CO2 concentration and populationaffect adaptive strategy effectiveness
economic
global
decline pop after 2050
decline pop after 2050
1
2
35
1 (A1F1) 2 (A1B) A2 B2
VietNam
less land lost and cost of loss; best total wetland and coastal forest value
most expensive
less land lost and cost of loss; best salt marsh most expensive less land lost
environmental
regional
4 6
IPCC SRES storylines
inc global pop
inc global pop
scenario 1 & 4 having the highest predicted CO2 emission
Malaysia cost of loss value cost of loss and cost of loss
Thailand
less land lost and cost of loss; best total wetland (incl unvegetated wetland) value
good total wetland (incl unvegetated wetland) value
less land lost and cost of loss
Philippines
best coastal forest and wetland value
less land lost and cost of loss; best total
tl d (i lSUMMARYCambodia
most expensive cost of loss
wetland (incl unvegetated wetland) value
most expensive cost of loss
less land lost and cost of loss
Singapore
best total wetland (incl unvegetated wetland) value
good total wetland (incl unvegetated wetland) value
Indonesiamost expensive cost of loss
best resource value; less land lost and cost of loss
most expensive cost of loss
less land lost and cost of loss
SUMMARY
• balanced source of energy technologies
• reduction of pop growth
• inc equity
• convergence among regions
Summary of results
• Adaptation to impacts of sea level rise requiresengineering measures to limit damage to humanengineering measures to limit damage to human populations and coastal resources;
• Country-specific and target-specific application of cost-benefit relation between beach nourishment and sea walls / dikes;
• Extent of impact dependent on underlying IPCC SRES storyline;
• Global effort should be exerted towards a target of B1 or A1T scenarios
Use of Conceptual Diagrams:
Identification of vulnerable coastal areas on a smaller refined scale in individual
countries for targeted case studies
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• Urbanization
VIETNAM (Red River Delta) PHILIPPINES (Batangas Bay)• Salt water intrusion• Storm surge• Land reclamation
• Aquaculture expansion• Storm frequency
Proposed case studies for coastal vulnerability in SE Asia to sea level rise
Urbanization
MALAYSIA (Darvel Bay)• Salt water intrusion• Sedimentation
CAMBODIA
• Land subsidence• Coastal inundation• Storm frequency
Coastal Vulnerability Assessment Map
INDONESIA (Jakarta Bay)• Flooding
• Pollution• Saltwater intrusion
THAILAND (Andaman coast)
• Flooding • Erosion• Land cover change
SINGAPORE• Flooding• Erosion
Andaman Coast, Thailand
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Singapore
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Management and Policy Considerations
• Management and policy decisions can be enhanced with the proper scientific inputs;
I thi j t d li t l h b d t• In this project, a modeling tool has been used to give a preliminary regional perspective, with several options for adaptation to sea level rise;
• On a more refined scale, conceptual diagrams are useful for identifying specific issues and highlight sensitive areas for further study;
• The final phase of this regional project will focus on policy ad cost-benefit analysis specifically relevant to the management and governance of coastal areas at risk to global environmental change.
TEAM:Beverly Goh, Ph.D. National Institute of Education, Nanyang Technol. U., Singapore, [email protected] T David, Ph .D. U. Philippines Marine Science Institute, Philippines, [email protected] Maneja, U. Philippines Marine Science Institute, Philippines, [email protected] Lansigan, Ph.D. U. Philippines Los Banos, Philippines, [email protected] Sereywath, Department of Fisheries, Cambodia, [email protected] M. Radjawane, Ph.D., Bandung Inst. of Tech., Indonesia, [email protected] M. Manjaji Matsumoto, Ph.D., U. Malaysia Sabah, Malaysia, [email protected],Ejria Saleh, Ph.D., Ph.D., U. Malaysia Sabah, , MalaysiaBen S. Malayang III, Silliman University, Philippines, [email protected] S. Malayang III, Silliman University, Philippines, [email protected] Pitiwong Tantichodok, Ph.D., Walailak University, Thailand, [email protected] Snidvong, Ph.D., Chulalongkorn University, Thailand, [email protected] Hoang Tri, Ph.D. Center for Environmental Res & Education, Vietnam, [email protected] Anh Thi Nguyen, Ph.D. Nha Trang University of Fisheries, Vietnam, [email protected] Saito, Ph.D., Geological Survey of Japan, Japan, [email protected] Hinkel, Ph.D. Potsdam Institute for Climate Impact Research, Germany, [email protected]
SEA-START Regional Centre, ThailandLOICZ-IPO, Germany; LOICZ-SEAsia Regional Node, Singapore
INTERNATIONAL SECRETARIAT
