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The Feasibility of Developing a Physical Hazard Index Model for Climate
Change Adaptation and Disaster Risk Management (CCA-DRM) Using a
System Dynamics Approach: the Case of Metro Manila
Jairus Carmela Josol1, Charlotte Kendra Gotangco1,2, Abigail Favis1, Severino Salmo III1, May Celine Thelma Vicente2, Gemma Narisma2
1Department of Environmental Science, Ateneo de Manila University
2Manila Observatory
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2
Background
n 
Disasters due to climate and weather related events continue
to increase
n 
Forensic investigation (FORIN) of disasters developed to
better understand why disasters persist
Risk =
Hazard x Exposure x Vulnerability
Adaptive Capacity
+
Climate &
Weather
related
hazards
Physical Hazard
Components and their
Interaction
Envi quality
Urban
Morphology
+
Auxiliary
Stock
Flow
System dynamics
q 
A study of system structure
understand system behavior
q 
Salient feature: feedback
processes
+
5
Objectives
n 
Develop a physical hazard index model of Metro Manila
using system dynamics
n 
Explore the potential of the model as a decision support tool
for CCA-DRM
+
6
Method
+
7
Urban
Development in
Metro Manila
No
comprehensive
land use plan
70
Share of Total Land Area (%)
60
50
Residential
Commercial
40
Industrial
Institutional
30
Utilities
Agricultural
20
Open Space
Forestland/Parks
10
0
1938
1980
1990
Year
+
Change in Land Cover
Urban Development in Metro Manila
1994
8
Flooding has
expanded into
upland areas in
the recent
decades
+
Flooding
Urban development in Metro Manila
9
Cleanup
(0.1%)
Recycled
(2%)
Waste
generated
Uncollected
(36%)
Disposed
(98%)
To Disposal
Sites (64%)
+
Municipal Solid Waste
Urban Development in Metro Manila
Streams &
Waterways
Others
Sanitary
Landfills
Controlled
Disposal
Low collection 10
efficiency,
uncollected
waste ends up in
waterways
94% of
population has
access to
sanitation
facilities
0.12
0.10
0.08
0.06
0.04
0.02
0.00
1996
1998
2000
2002
2004
to sewerage
+
2006
desludged
Sanitation and sewerage
Urban Development in Metro Manila
2008
2010
2012
11
Year
Paranaque
San Juan
NMTT*
DO
BOD
DO
BOD
DO
2000
4.9
19.6
3.3
16.6
2.88
2001
1.6
13.3
2002
3.1
25.6
3.0
34.8
2.8
2003
3.1
18.2
2.4
54.8
2004
2.0
45.7
2.9
46.8
2005
1.3
29.5
2006
1.6
41.0
1.1
2007
1.4
39.9
2008
1.6
38.2
0.3
38.0
BOD
Marikina
Pasig
DO
BOD
DO
BOD
4.6
7.4
3.3
6.0
3.6
8.8
3.6
7.1
25.2
5.0
12.1
3.7
11.5
3.6
22.3
3.1
18.2
3.1
17.1
3.34
28.2
3.6
19.3
1.6
17.4
1.92
24.5
3.4
12.1
2.1
24.2
33.4
1.59
17.8
2.2
15.0
2.5
13.6
1.6
40.4
1.99
27.7
2.2
25.4
2.4
15.5
1.9
44.2
1.41
40.6
2.6
18.2
3.2
20.5
3.19
31.0
3.2
31.0
30.2
2009
2010
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Surface water quality & availability
Urban development in Metro Manila
10.7
Major rivers in 12
Metro Manila are
heavily polluted
39-65% of total
production is
non-revenue
water
2000
Volume of Water (MCM)
1600
Total Prod
1200
E Supply
Total Demand
800
400
1980
1985
1990
1995
2000
2005
2010
Year
+
Water supply and accessibility
Urban Development in Metro Manila
13
10000
500.0
9000
450.0
8000
400.0
7000
350.0
6000
300.0
5000
250.0
4000
200.0
3000
150.0
2000
100.0
1000
50.0
0
1980
1985
1990
Stock
+
1995
Withdrawal
2000
2005
Recharge, JICA 1992
Groundwater quality & availability
Urban Development in Metro Manila
0.0
2010
Groundwater 14
mining occurs at
a rate of 100 to
200 MCM/y
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15
Model Development
WATER
ACCESSIBILITY
SANITATION &
SEWERAGE
MUNICIPAL
SOLID WASTE
FLOODING
WATER
AVAILABILITY
WATER
BALANCE
URBAN GROWTH
+
influent
effluent
SANITATION & SEWERAGE
(management of human waste)
commercial & industrial effluent
PHYSICAL
SERVICES INDEX
WATER ACCESSIBILITY
(demand vs. consumption)
supply-production
PHYSICAL
SERVICES
INDEX
WATER QUALITY &
POLLUTION LOAD
(LONG TERM COMPONENT)
WATER AVAILABILITY
(production efficiency)
MUNICIPAL SOLID WASTE
(management)
demand
raw water
available
waste
generation
surfaces for
infiltration
WATER BALANCE
(long-term availability of
groundwater)
URBAN GROWTH
(population & surface
characteristics)
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FLOOD HAZARD
INDEX
(SHORT TERM COMPONENT)
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18
Model Translation:
Causal Loop Diagram
solid waste
+ generation
unused collection
capacity
+ disposed to +
uncollected
disposed to
waste collected
SLFs
waste
unmanaged SWDS
-
availability of
SFs
demand for
pollutant load in + unconnected
connected to +
sanitation facilities
to SFs
SFs
+ surface water
+
channel
capacity
withdrawal
other uses
-
evapotran+
spiration
rain
built-up spaces
+
population
+
growth rate
+
+
withdrawal for
-- surface water MWSS
water
stored
overflow
available
for
use
+
+
+
conveyanceinflow to dams
away from land+
+
+
water on land
+
water in dams
unused MWSS
service capacity
+
infiltration &
percolation
-
+
available
groundwater
expansion of
water sources
wastewater
generated
+
-
-
unconnected to connected to
MWSS
- MWSS
+
groundwater +
withdrawal
net growth
surface water
withdrawal
(external)
+
+
alternative
water source
+
water demand
+
water
+consumed
+
19
Model Translation: SD Model
+
20
Model Translation: SD Components
FLOOD EVENT
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21
Model Translation: SD Components
URBANIZATION
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22
Model Translation: SD Components
SEWERAGE & SANITATION
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23
Model Translation: SD Components
WATER BALANCE
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Model Translation: SD Components
WATER ACCESSIBILITY
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Model Translation: SD Components
POLLUTION LOADING/WATER QUALITY
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Model Translation: SD Components
PHYSICAL SERVICES INDEX
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Water&Availability&Index&
1.1$
1$
0.9$
0.8$
Zero$Builtup$Inc$
0.7$
Builtup$Inc$
0.6$
0.5$
0.4$
1980$ 1990$ 2000$ 2010$ 2020$ 2030$ 2040$ 2050$
Year&
Sample Scenario
Analyses (long-term)
Population growth rates
q 
Changes in built-up spaces
Scenario
!
Population Growth
Physical Urbanization
1
Zero Population Growth (2010)
Increase in built-up areas
2
Increase in Population (NSCB)
Zero increase in built-up areas
3
Increases in Population (NSCB)
Increase in built-up areas
0.55%
Physical)Services)Index)
q 
0.54%
0.53%
ZeroPop_BuiltupInc%
0.52%
PopInc_ZeroBuiltup%
0.51%
PopInc_BuiltupInc%
0.5%
0.49%
2010%
2020%
2030%
Year)
2040%
2050%
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900"
Discharge*(m3/s)*
800"
700"
600"
CN_60"
500"
CN_70"
400"
CN_80"
300"
CN_90"
200"
CN_100"
100"
0"
0"
10"
20"
Sample Scenario
Analyses (short-term)
q 
State of urban services
represented by the Physical
Services Index (PSI)
Surface characteristics expressed
as Curve Numbers (CN)
40"
50"
Time*(h)*
1.2"
Flood%event%hazard%index%
q 
30"
1"
0.8"
Physical"[email protected]"
0.6"
Physical"[email protected]"
0.4"
Physical"services@1"
0.2"
0"
0"
10"
20"
30"
Time%(h)%
40"
50"
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solid waste
+ generation
unused collection
capacity
uncollected
waste
+ disposed to +
disposed to
waste collected
SLFs
unmanaged SWDS
-
+
channel
capacity
Model Utility and Application
As a hazard assessment tool:
Can account for both short-term and long-term factors
Can test different development configurations
Can identify data gaps
evapotran+
spiration
rain
built-up spaces
+
+
conveyancewater stored
inflow to dams
overflow
away from land+
+
+
+
+
water on land
+
water in dams
-
+
infiltration &
percolation
+
available
groundwater
groundwater +
withdrawal
+
30
solid waste
+ generation
unused collection
capacity
uncollected
waste
+ disposed to +
disposed to
waste collected
SLFs
unmanaged SWDS
-
+
channel
capacity
Model Utility and Application
As a tool for decision-making
Can explore different policy/management options through
scenario analyses
Graphical interface makes the model tractable (structure,
biases, weighting, assumptions) – potential for
participatory modeling
Index lends ease of comparability and communication
evapotran+
spiration
rain
built-up spaces
+
+
conveyancewater stored
inflow to dams
overflow
away from land+
+
+
+
+
water on land
+
water in dams
-
+
infiltration &
percolation
+
available
groundwater
groundwater +
withdrawal
+
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solid waste
+ generation
unused collection
capacity
uncollected
waste
+ disposed to +
disposed to
waste collected
SLFs
unmanaged SWDS
-
+
channel
capacity
Limitations
Cannot accurately predict hazards
No spatial representation
Short-term and long-term models are not coupled
evapotran+
spiration
rain
built-up spaces
+
+
conveyancewater stored
inflow to dams
overflow
away from land+
+
+
+
+
water on land
+
water in dams
-
+
infiltration &
percolation
+
available
groundwater
groundwater +
withdrawal
+
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Future work
n 
Refine the model by gathering more information
(characteristics of river basins, state of urban services,
environmental quality)
n 
Expand model to include other hazards (geophysical, other
continuous slow-onset hazards)
n 
Dynamically couple short-term and long-term models
n 
Combine model with existing assessment tools to enhance its
utility
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This research was supported by the project, Harmonizing FORIN
for Climate Change Adaptation and Disaster Risk Management
(CCA-DRM) implemented by the Manila Observatory through a
grant to conduct follow-on research from the 2012 Advanced
Institute on Forensic Investigations of Disasters (FORIN). Funding
for participant follow-on research and this project was provided by
ICSU and the US National Science Foundation, Grant Number:
0627839. The International START Secretariat is the implementing
agency.
The 2012 Advanced Institute on FORIN was organized by START
and the IRDR International Center of Excellence (CoE) in Taipei,
together with IRDR International, ICSU and Taiwan’s National
Science and Technology Center for Disaster Reduction (NCDR).
Funding for the Institute was provided form ICSU.
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