- UNDP-ALM

advertisement
Conserving Mangroves for
Storm Protection Services
Saudamini Das, Assoc Prof. Institute of
Economic Growth, Delhi, and SANDEE Fellow
Economics of Climate Change Adaptation Workshop, USAID, UNDP, ADAPT AsiaPacific, 24-26 Oct 2012, Bangkok
The views expressed are those of the presenter and should not be attributed to either UNDP or USAID.
Furthermore, it is strongly recommended that both the PowerPoint slides and the videos of the presentation of
1 are
content included herein are viewed in conjunction in order that statements appearing in the PowerPoint slides
not interpreted out of context.
Approach to Storm Hazard
• Emphasis on scientific & engineering approach to storm risk
management by policy
• Better prediction
• Early warning
• Evacuation
• Storm shelters, storm resistant houses, dikes
•There are limitations & uncertainty
• Accurate prediction of intensity, landfall with sufficient time gap
• Limited compliance of community to State warning: (wait & watch,
faith on GOD, less faith on Govt)
• All investments limited to protection of movable properties
• Uncertainty from Climate change
• Bay of Bengal, South China Sea and North Pacific Ocean are core
area of Cyclogenesis (IPCC 1997)
Natural buffers are important - need to examine
their role
• Do mangroves provide storm protection ?
- historical context,
- concerns, knowledge gap
- careful examination of this service
• How do they fare vis-à-vis the other approaches like
early warning, storm shelter, dikes, etc?
• Is mangrove preservation an economically viable
adaptation strategy to climate change?
3
Mangroves break, stop and
channelise the storm surge
Storm protection by Mangroves - Background
• Debated since the Bhola Cyclone (Nov 1970) in
East Pakistan (Bio.Conserv, 1971)
• Much focus due to prominent natural disasters like
2004 tsunami, Katrina, Sidr, Nargis, Aila etc.
• Accepted as a prominent ecosystem service
(Barbier et al, Science 2008; Day et al, Science 2007;
Gedan et al, Climate Change 2010).
• Most of the empirical works are questioned.
Present Study
• Quantifies Mangrove Protection during 1999 Super Cyclone
• Examines mangrove protection for movable as well as
immovable properties (house damages)
• Large sample and maximum possible control to separate
Mangrove impact on Cyclone Damage
• Use Scientific, GIS and Socio-Economic data
• Robust finding that mangroves reduced cyclone damages
and support for mangrove conservation to get storm
protection
Mangrove Forest cover before 1950 (30,766 hectares)
Bhadrakh
Kendrapada
LEGENDS
Jagatsinghpur
District Boundary
River
Mangrove
Super Cyclone Path
Bay of Bengal
Puri
7
Mangrove Forest cover in 1999 (17,900 hectares)
Bhadrakh
Kendrapada
LEGENDS
District Boundary
River
Jagatsinghpur
Casurina Dense
Casurina Open
Mangrove
Super Cyclone path
Mix Jungle(Kaju)
Bay of Bengal
Puri
8
B
A
9
Human death in Kendrapada
Description of Deaths
Area
No of
Mean
Villages death
Mini
mum
Maxi
mum
Entire District
1180
0.39
0
21
Villages with no or little
mangrove protection (M ≤ 0.5)
722
0.54
0
21
Villages with high mangrove
protection (M > 0.5)
458
0.14
0
10
Villages inside mangrove habitat
( established by cutting
mangroves)
96
1.11
0
13
Villages outside mangrove
habitat
1084
0.32
0
21
11
How do I identify Mangrove Impact during
Cyclone?
• Estimate Cyclone Damage Function using multiple control
variables along with mangroves
• Use variables to control for:
- Physical features of mangrove habitat
- Cyclone Impact
- Topography
- Hydrology
- Infrastructure
- Socio-Economic Well-being
- Governmental Institution
• Calculate avoided damages from marginal effect
12
Confounding effect of mangrove
with effect of distance from coast
Village B
●
Village A
Mangrove
●
Sea
---- with effect of Mangrove Habitat
• Exclude village A, include village C
• Test that protection at B is due to vegetation, not habitat
A●
C●
B●
Mangrove habitat
Mangrove
Sea
Marginal effect - death
(villages within 10km from coast)
Variables
Marginal Effect
Variables
Marginal Effect
Mahakalpada
Tahasil
0.22 ***
Droad
0.0006
Patamundai
Tahasil
-0.06
Roadumy
0.04
Surge
0.02
Pop99
0.00005 ***
Dcoast
0.02**
Literate
-0.16
Mangrove
-0.111***
Schedulcaste
-0.10
Mhabitat
-0.022 ***
Cultivator
0.05
Topodumy
0.294 ***
Aglabor
0.03
Casuarinadumy
-0.045
Hhworker
0.958
Dmajriver
0.025 ***
Margworker
0.36***
Dminriver
-0.004
Otworker
-0.26
Deaths averted by Mangroves
DA 
,
ˆ y
ˆ
y
Actual death due to super cyclone
392
Predicted deaths if there were no mangroves
603
Predicted deaths if current mangroves were at
1950 level
31
Averted deaths under assumption 1
(603 – 392) = 211
211 (54%)
Averted deaths under assumption 2
(392 – 31) = 361
361 (92%)
16
Other damages averted by Mangroves (%)
DA 
Damage
type
 yˆ   yˆ 
1999
mangrove
1950
mangrove
Human
death
54
92
FC
17
100
PC
-17
-100
Cattle
15
67
Buffalo
27
52
17
Storm Protection Value of Mangroves
during super cyclone
Area /
Mangrove unit
Value of 1km
width
Value of 1
hectare
Village
Rs3,928/
Rs217/
Entire study
area
Rs33,39,166/
(USD 68, 586)
Rs1,82,080/
(USD 4335)
18
Weighted Average Storm Protection Value of km width
of Mangroves per Village (in INR)
Type of damage
Value/km of 1999
mangrove/village
Value/km of 1950
Mangrove/village
Human death
2743.95
1478.28
Fully collapsed houses 1368.55
3235.85
Partially collapsed
houses
-245.59
-580.85
Fully collapsed +
Partially collapsed
1123.36
2655
Buffaloes
8.77
4.83
Cattle
49.94
45.07
-.1
-.05
0
.05
.1
.15
Will we optimize benefit by going back to 1950
level? NO
0
1
2
3
hmangrvillage
4
X axis: km width of mangrove \ village
Y axis: averted death \ km width of mangrove \ village
Turning point: at approximately 1.5 km \ village
5
Mangroves vs. others
Damag Actu Death
e
al
without
mangrove
s
Death
without
storm
shelters
Death Death
without without
early
dikes
warning
Human 197
death
404
1602
331
257
Source: Das & Vincent ongoing (not to be quoted)
• 74% of all the Swept Away houses and 80% of all
the cattle loss in Kendrapada occurred from villages
next to dikes.
Source: Das ([email protected])
21
Should we preserve mangroves to adapt
to climate change?
Yes, on both meteorological and economic grounds.
•
•
Meteorology:
Orissa is the most cyclone prone state in east coast of India.
Frequency of high intensity cyclones increasing over years.
Period
Frequency of VSCS
& SC
Annual
Probability
1900-1920
0
0.00
1920-1940
2
0.10
1940-1960
1
0.05
1960-1980
3
0.15
1980-2000
3
0.15
Economic cost & benefit (1999 prices)
Opportunity cost of
conserving mangroves
Benefit from conserving
mangroves
• Market value of land in coastal
Kendrapada: Rs172, 970 \ ha
• Storm protection value (only for 3
damages):Rs182, 080\ha
• Annual return from land (8%):
Rs13, 837\ha\yr
•
Annual Probability of VSCS and
SC:
0.15\yr
• Annual return from land(12%):
Rs20, 756\ha\yr
•
Annual Storm Protection Value
(for 3 damages): Rs27, 312\ha\yr
Does reduction in only death risk justify
mangrove preservation?
Benefit from death risk reduction
•
•
•
•
No of lives saved:
0.01 \ ha
VSL for Orissa from Indian wage-risk study: Rs10,918,132\
Annual probability of VSCS &SC:
0.15\yr
Annual benefit from reduction of death risk : Rs17, 469\ha\yr
•
Opportunity cost of Mangrove Preservation:
Rs13, 837 – Rs20, 756\ha\yr
Benefit ≥ Cost
•
VSL for India: Rs13.7-14.2 to Rs55.5-60.6million at 2000 01prices ≈ Rs17.8-18.4 to Rs72 -78.12m at 2002-08 Per capita
income.
Conclusions
•Mangroves reduced human death, livestock loss and house
damages during the T-7 Super cyclone of October 1999.
• Human death toll would have been nearly doubled in
absence of mangroves.
•Annualized storm protection benefit of mangrove for reducing
three damages was found higher than annual return from land
justifying mangrove conservation as a viable adaptation
strategy to climate change.
25
Policy Implications
• Use of engineering approach to manage storm disaster may
not be the only option.
•Along with engineering and scientific approaches, mangrove
protection and regeneration should be undertaken to manage
storm risk more efficiently
• Along with movable properties like lives, mangroves also
protect immovable assets like houses.
26
THANKS
Download
Related flashcards

Banking

30 cards

Payment systems

59 cards

Finance ministries

62 cards

Currencies of Germany

18 cards

Create Flashcards