saved wealth saved health 2013.pdf
TRANSCRIPT
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Published by:
Saved health, saved wealth:an approach to quantiying
the benefts o climate change
adaptationPractical application in coastal protection projects in Viet Nam
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Abbreviations
Figure and Table List
1. Executive Summary
2. Background and Introduction
3. The concept o quantiying adaptation benets
3.1. Explanation: Saved Wealth indicator
3.2. Explanation: Saved Health indicator
3.3. Explanation: Environmental benets
4. Methodology
4.1. Applicability and boundary
4.2. Derive baseline
4.3. Calculation o wealth and health benets due to an adaptation project scenario
4.4. Sensitivity analysis
4.5. Assessment o environmental impacts
5. Case study Viet Nam
5.1. Vulnerability situation o Viet Nams coastline
5.2. Presentation o the baseline adaptation options and benets
5.2.1. Baseline scenario
5.2.2. Adaptation measure: Dyke upgrade
5.2.2.1. Application o the methodology5.2.3. Adaptation measure: Mangrove plantation
5.2.3.1. Application o the methodology
5.3. Comparison o project scenarios
6. Conclusions regarding the quantication ramework and application
in the context o the Vietnamese case study
7. Reerences
8. Appendix: Methodology or estimating wealth and health benets o
climate change adaptation projects: Adapting coastal zones to rising sea levels
C O N T E N T S
2
3
4
6
9
10
11
11
12
13
13
13
14
15
16
17
18
20
22
2223
25
26
28
30
33
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AF Adaptation Fund
AFB Adaptation Fund Board
CBA Cost-Benet Analysis
COP17 Seventeenth session o the
Conerence o the Parties to the
United Nations Framework
Convention on Climate Change
DALY Disability-Adjusted Lie Years
FAO Food and Agriculture Organization
o the United Nations
GBD Global Burden o Disease
GDP Gross Domestic Product
GEF Global Environment Facility
GIZ Deutsche Gesellschat r
Internationale Zusammenarbeit
IFRC International Federation o
Red Cross and Red Crescent Societies
IPCC Intergovernmental Panel on
Climate Change
M&E Monitoring and evaluation
MISW Mixed index or Saved Wealth
MNRCZ Management o Natural Resources
in the Coastal Zone o Soc Trang
MONRE Ministry o Natural Resources
and the Environment (Viet Nam)
MRV Measurement, reporting and
verication
NGO Non-governmental organisation
RBM Results-based management
RWS Relative wealth savings
SD Sustained development
SDC Swiss Agency or Development
and Cooperation
SH Saved Health
SW Saved Wealth
UN United Nations
UNFCCC United Nations Framework Convention
on Climate Change
USD United States Dollar
WHO World Health Organization
WRI World Resources Institute
YLD Years lived with disability
YLL Years o lie lost (due to
premature mortality).
A B B R E V I A T I O N S
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Figure 1: P. 5
Steps in assessing an adaptation project
according to the indicator ramework and a
related methodology
Figure 2: P. 7
Uncertainties when predicting and evaluat-
ing results o a climate change adaptation
project
Figure 3: P. 12
Steps in assessing an adaptation project
according to a suitable methodology
Figure 4: P. 14
Example o the damage-requency unction
o food events
Figure 5: P. 17
Geographic distribution o primary climate
exposure hazards in Viet Nam
Figure 6: P. 19
Salinity boundary in Mekong river delta in
2000 and projection or 1 m sea level rise
Figure 7: P. 19
Satellite image o Au Tho B village with a
co-managed zoning plan
Figure 8: P. 26
Sensitivity analysis o critical parameters or
calculating Saved Wealth
Table 1: P. 18
Projected average sea level rise (in cm)
in Viet Nam, relative to average o the
1980-99 period
Table 2: P. 20
General baseline parameters
Table 3: P. 21
Expected annual wealth losses (in
million USD/yr).
Table 4: P. 21
Expected annual health losses (in
DALYs/yr).
Table 5: P. 22
Wealth and health losses in baseline
Table 6: P. 23
Main results o Saved Wealth calcula-
tion or the dyke scenario
Table 7: P. 24
Main results o Saved Wealth calcula-
tion or the mangrove scenario
Table 8: P. 25
Main results o Saved Health calcula-
tion or the mangrove scenario
L I S T O F F I G U R E S A N D T A B L E S
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E X E C U T I V E S U M M A R Y
1.
4
Global greenhouse gas emissions are increasingcontinuously despite two decades o climate
policy. By 2012, the average global temperature
increase since the late 19th century had already
reached 0.7C. At the same time, the international
climate community has realised that eective
and ecient adaptation to the adverse eects o
climate change is vital.
This report deals with one o the key challenges
adaptation project developers are acing: how to
consistently estimate, monitor and evaluate the
actual outcomes o their adaptation activities. So
ar many dierent approaches or various adapta-
tion project types and sectors have been applied,
but a standardised set o indicators covering most
activities is still missing. It would allow project
proposals to be compared beore implementation
in order to identiy the most promising activitiesin a transparent manner (ex-ante). The standard-
ised criteria would also enable lessons to be drawn
rom project implementation (ex-post).
We propose a ramework consisting o two key
indicators that allows the total value o an adapta-
tion project to be assessed. Saved wealth (SW) cov-
ers the monetary value o public inrastructure,
private property and income loss. Saved health
(SH) assesses avoided disease, disability and lie
loss. Moreover, environmental impacts that are
dicult to measure in terms o monetary wealth
such as biodiversity can be taken into accountqualitatively.
We apply this indicator set to the GIZ project Man-
agement o Natural Resources in the Coastal Zone
o Soc Trang (MNRCZ) in Viet Nam as a case study.
The main ocus o this GIZ project is coastal pro-
tection. The rst step o this report has been the
development o a Methodology or estimating
the wealth and health benets o climate changeadaptation projects: Adapting coastal zones to ris-
ing sea levels, which includes the steps described
in gure 1.
The methodology also includes two comprehen-
sive spreadsheets* that perorm the calculations
and consist o pre-dened ormulas, sensitivity
analyses and databases.
When applying the methodology in the context
o Soc Trang, we have assessed two adapta-
tion options: the real mangrove rehabilitation
programme and a hypothetical dyke upgrade.
This allows or the evaluation o two dierent
adaptation projects at the same location and a
comparison o the expected benets. The nal
* The spreadsheets can be downloaded at
www.AdaptationCommunity.net
under Knowledge -> Monitoring and Evaluation. ->
Tools and Training Material
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1Data gathering at the local level
Coverage o combined extreme events
Uncertainty o climate projections
The complexity o the applied tool could be
reduced through pre-dened methodologies and
simplied versions o calculation tools. External
guidance and capacity building help make the
tool usable by local project managers. The ap-
plication o the methodologies and tools by users
with dierent education levels and o dierent
cultural backgrounds, ideally through hands-
on workshops, would be crucial to allow or the
generalisation o this approach.
The harmonization as well as other internation-
ally available data sources would be helpul and
should be supported. Methodologies or other
types o adaptation activity would need to be
developed and tested. This would allow or cross-
sector comparisons o dierent adaptation project
types (e.g. coastal zone interventions vs. drought
adaptation activity).
result shows that the wealth benets or the
local population are almost ve times higher or
the mangrove option than or the dyke upgrade.
Additionally, the mangroves also lead to signi-
cant health and ecological benets whereas the
dyke cannot provide such advantages: the dyke
upgrade would not even justiy its investment.
We conclude that the quantication ramework
can be successully applied or measuring project
impacts ex-post (monitoring and evaluation
(M&E) or the historical mangrove benets) and
predicted impacts ex-ante (or the hypothetical
dyke upgrade and the uture mangrove benets)
o coastal zone interventions. Furthermore the
assessment provided clear guidance or an invest-
ment decision as it was able to directly compare
the adaptive benets o two competing projects
due to an identical set o applied indicators. The
methodology can be replicated or coastal zone
interventions in other countries due to large
databases providing parameters or developing
countries around the globe.
We have identied challenges in the ollowing elds:
Dening the applicability and boundaries o the methodology
Deriving a baseline scenario
Description o project scenarios
Assessment o saved wealth, saved health and environmental benets/impacts
Denition o monitoring parameters
1
2
3
4
5
Figure 1:
Steps in assess-
ing an adaptation
project according to
the indicator rame-
work and a related
methodology
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2.
6
B A C K G R O U N D A N D I N T R O D U C T I O N
The need or adaptation to mitigate existing and
upcoming impacts o climate change is widely
recognised in the international climate com-
munity. For 2030, the United Nations Framework
Convention on Climate Change (UNFCCC) (2007)
estimates annual global adaptation costs at
USD 49 to 171 billion, with USD 27 to 66 billion
accruing in developing countries (see also Parry et
al. 2009). Adaptation eorts have evolved signi-cantly in recent years and more experience has
been gained. However, the adaptation resources
available are many times less than the adaptation
needs calculated by Parry et al. (2009). From an
economic point o view, it would be desirable to
maximise the adaptive benet achieved with the
global investments in adaptation. Against this
background there is a strong need or eective-
ness criteria to assess ex ante where adaptation
measures can bring about the largest benets or
the least cost, and to assess ex post whether or not
an adaptation intervention has been successul.
Such eectiveness criteria will also be o help or
development cooperation and its eorts in moni-
toring adaptation projects (see also Spearman and
McGray 2011, p.5 and GIZ (2012)).
In contrast to mitigation, where the eectivenesso policy action can be measured through the
metric tonnes o CO2
equivalent reduced, no
universally accepted metric or assessing adapta-
tion eectiveness exists to date. The lack o such
a metric is a barrier in planning, monitoring and
evaluating o adaptation eorts. The rst experi-
ences with allocating adaptation unding show a
tendency to use intermediate outcome indicators
(e.g. or adaptive capacity and adaptation action
taken) but no nal impact metrics (e.g. or sus-
tained development despite climate change).
This report introduces indicators or nal adapta-
tion impacts that can be used or two purposes.
First, the indicators provide inormation or the
ex-post monitoring and evaluation (M&E) o
adaptation benets. Second, the indicators can be
used to identiy promising and ecient adapta-
tion projects ex-ante. Given the long time horizon
o adaptation projects, some overlap betweenM&E and planning is inevitable. In order to assess
uture benets o climate change adaptation, it is
necessary to think in alternatives (counteractu-
als) even when the adaptation project has already
been running or a considerable period o time.
This is why our approach or M&E uses a type o
cost-benet analysis (CBA) that is usually applied
in project planning and has been suggested or
appraising adaptation projects ex-ante (GIZ 2013).The approach developed by Perspectives Climate
Change builds on results-based monitoring sys-
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2
available yet, and there are ew decision support
tools. Moench et al. (2009) were among the rst
to discuss CBA as a tool or evaluating adaptation
projects. The idea evolved to make use o CBA
indicators or planning and prioritisation beore
project implementation as well as or M&E. How-
ever, a detailed description o appropriate metrics
or such a systematic assessment o adaptation
benets is lacking.
Development agencies like the Deutsche Ge-
sellschat r Internationale Zusammenarbeit
(GIZ) have traditionally applied a broad range
o process and outcome indicators or evaluat-
ing their adaptation projects. An assessment o
natural resource management projects conducted
by Michaelowa and Khler in 2010/2011 revealed
that most o these indicators address lower
tems ollowing the concept o results chains lead-
ing rom outputs to outcomes and indirect results/
impacts (see GTZ 2008, p.5). With each level o the
results chain, the level o uncertainty regarding
the attribution o a result to the evaluated project
increases. In the complex eld o climate change,
this uncertainty has two main components
uncertainty relating to uture climate change
impacts and uncertainty regarding non-climatic
drivers that infuence project impacts. Figure 2
demonstrates how uncertainties infuence the
assessment o adaptation results in a classic results
chain and identies attribution gaps.
Several studies have shown that estimating
adaptation benets rom dierent project types in
dierent sectors and geographies is challenging.
A comprehensive and systematic approach is not
Inputs Outputs Outcomes Impact
Project-external uncertainties (e.g. climate change impacts, baselineadaptation measures)
Project-internal uncertainties (e.g. project management, support rom
stakeholders, ailure and diusion rates o technologies)
e. g. dollars e. g. trained e. g. coastal e. g. prevention
people protection o foods, saved
in place assets
Attribution? Attribution?
Figure 2:
Uncertainties when
predicting and
evaluating results
o a climate change
adaptation project
Source:
Modied ater
Binnendijk 2001,
UNFCCC 2010,
example o coastal
adaptation project
in italics
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Document the conclusions drawn rom its
application as the basis or uture applica-
tions.
The concept o quantiying adaptation benets
will be introduced in chapter 3. Based on the
concept a methodology to assess benets o
coastal adaptation projects is described in chapter
4. Chapter 5 outlines the application o the meth-
odology in the context o the Vietnamese case
study. At rst, the baseline scenario is described,
ollowed by two potential project scenarios: dykeconstruction and the rehabilitation o mangroves.
The results o both projects are compared to the
baseline, which allows or the interpretation o
outcomes and identication o lessons learned or
similar project types. Identied strengths, chal-
lenges and recommendations or improvements
are presented in chapter 6. Finally, Annex I docu-
ments the ull methodology.
levels o the results chain and rarely take into
account the indirect long-term impacts (see also
Michaelowa and Khler 2011, p. 15).
Perspectives has elaborated a ramework or
quantiying the results o adaptation projects
and programmes through standardised indica-
tors1. The method quanties long-lasting impacts
while taking into account uncertainties. Perspec-
tives has so ar tested the practical application o
the method in one setting, a project or Kenyas
agricultural sector. GIZs Climate Protection Pro-
gramme or Developing Countries commissioned
urther testing o the concept or the GIZ project
Management o Natural Resources in the Coastal
Zone o Soc Trang (MNRCZ).
The study aims to:
Communicate the concept o quantiying
adaptation benets to GIZ project developers
and related stakeholders and policy-makers.
Eventually, the concept could be applied
widely or all types o adaptation. The spe-
cic aim is to present an innovative indicator
approach or ex post M&E o adaptation
benets. At the same time these indicators
might also be useable or ex ante planning in
the context o CBAs;
Provide a methodology or quantiying
adaptation benets o coastal adaptation
projects, including a spreadsheet and related
instructions to operationalise the metho-
dology;
Apply the methodology and tool to the case
study in Viet Nam, illustrating the underly-
ing concept and presenting the benets o
mangrove restoration;1 This was done on behal o the Swiss Agency or Develop-
ment and Cooperation (SDC).
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3.
9
3
Conceptually, estimating adaptation benets o
projects has always been plagued by the chal-
lenge to give a monetary value to human lie and
biodiversity. Attempts to use lie insurance data
to value human lie have been heavily criticised
because they value human lives according to their
economic potential expressed in monetary terms
such as Gross Domestic Product (GDP) per capita
which diers greatly between industrialised
and developing countries. We avoid this ethical
challenge by dierentiating between monetary
and human lie/health-related benets. In order
to cover the existence value*o biodiversity, the
concept also includes a procedure to take such
environmental benets into account.
Based on these general principles, indicators or
each o the ollowing three key dimensions re-
lated to the adverse eects o climate change are
proposed: economic value at risk health o people
at risk, and environmental benets. The aim is
to apply a consistent methodology that helps to
quantiy the benets or each o the categories
and which may help decision-makers to track
and compare project impacts as well as allocate
available resources systematically. A quantative
approach has been developed or economic and
health benets. The downside o purely quantita-
tive approaches is that they provide only a very
coarse picture o the reality and that such indica-
tors are dicult to measure. Furthermore, there
are uncertainties and value judgments such as
the impacts o climate change on extreme events.
However, quantitative indicators allow compar-
ing two situations consistently between space and
time.
It is proposed to determine the total value o an
adaptation project (TVAdapt) as the Saved Wealth
(SW), covering the monetary value o public
inrastructure, private property and income loss,
plus Saved Health (SH), covering avoided disease,
disability and lie loss. Besides this, environmen-
tal impacts that are dicult to measure in terms
o monetary wealth such as biodiversity are taken
into account qualitatively. In the ollowing, each
indicator is explained in detail.
T H E C O N C E P T O F Q U A N T I F Y I N G
A D A P T A T I O N B E N E F I T S
* The existence value refects the benets people expe-
rience rom knowing that a particular environmental
resource, such as a orest, endangered species or any other
organism or thing exists.
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Saved Wealth (MISW), which is calculated in two
steps: At rst the absolute wealth saved, includ-
ing private and public property, is assessed (e.g.
USD 0.2 million or a community as described
above). As a second step the relative wealth saved
is calculated. Here, the absolute wealth saved is
divided by the total wealth o the community
and nally multiplied by the population. In
the example, this would be e.g. USD 0.2 million
absolute savings divided by USD 1 million total
wealth = 20% relative wealth savings (RWS) within
the community. Finally the approach combines
both outcomes by multiplying the two values. Inthe example, the village would have a total aver-
age Saved Wealth o USD 0.2 million * 20% (RWS)
= USD 40,000 (RWS). The concept has the advan-
tage that poor, vulnerable communities that lack
assets to be protected are not excluded (covered
by relative wealth), while concentrations o assets
in more developed regions are not neglected
(covered by absolute wealth). The ormula or the
Saved Wealth index is:
SW = MISW = AWS. RWS
where;
MISW: mixed index or Saved Wealth (MISW)
AWS: absolute wealth saved by a project (in USD)
RWS: relative wealth saved by a project (in relative
wealth savings (RWS))
The MISW may be applied to the wealth categories
o public inrastructure - which can include natu-
ral resources and services - and private property.
3 . 1 .
E X P L A N A T I O N :
S A V E D W E A L T H I N D I C A T O R
When assessing the wealth benet o an adapta-
tion project, one can generally use the two di-
erent concepts: absolute wealth saved or relative
wealth saved. These two types o wealth (de-
scribed below) can be used to compare the impact
o competing investment options (or approaches)
within an adaptation project at community level.
1. Absolute wealth saved: This approach meas-
ures the absolute wealth saved by the project.
Taking the ctive example o a community
with 1,000 inhabitants and with a moderate
level o wealth (USD 1 million), an adaptation
activity is, or example, able to save USD 0.2
million. Looking only at the absolute wealth
o the community does not necessarily ad-
dress vulnerability, as absolute wealth may
be concentrated among a ew community
members who are able to cope with the loss
o part o their assets.
2. Relative wealth saved: Here, the absolute
wealth saved by the adaptation project is
divided by the total wealth o the commu-
nity. The number o average personal wealth
saved is calculated as a per cent. The relativewealth saved or the community described
above would be 20% (USD 0.2 million/1 mil-
lion). Looking only at the relative wealth o
the community may lead to high losses or
wealthy community members while spend-
ing a lot o resources to protect the limited
wealth o poor people.
To combine the advantages o both approaches
the authors decided to apply a mixed index or
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3
In the context o the assessed project activities in
chapter 4, the MISW has been balanced equally.
However the tool user makes the decision about
the weighting o relative and absolute wealth. I
both public inrastructure and private property
are assessed, then the sum o public and private
wealth saved shall be calculated or each sub-
indicator (absolute and relative wealth savings)
beore multiplying the two values to get the MISW.
In determining the potential o an adaptation
activity to save wealth, one needs to consider the
development o wealth in the relevant region over
time that would occur in the absence o climatechange during the lietime o the project. Demo-
graphic and/or economic developments will lead
to changes o property, and thereore wealth in
the baseline scenario. Furthermore, the wealth
needs to be discounted. Discounting is done to re-
fect infation as well as decrease o the economic
value o inrastructure and hardware over time
that is not related to climate change (depreciation).
3 . 2 .
E X P L A N A T I O N :
S A V E D H E A L T H I N D I C A T O R
In this section, the concept o Disability Adjusted
Lie Years (DALYs) saved is introduced to assess
avoided negative climate change impacts on
humans due to a proposed adaptation activity,
also reerred to as Saved Health (SH).
The concept o DALYs was developed by the
World Bank (1993), and has since then been
systematically utilised by inter alia the World
Health Organization (WHO) in the Global Burden
o Disease (GBD) concept, which provides a com-
prehensive and comparable assessment o mortal-
ity and loss o health due to diseases, injuries and
risk actors or all regions o the world (WHO
2010). It is a concept to quantiy the burden o
disability and death that avoids the monetisation
o human lie. Instead, adaptation benets are
expressed as the avoided number o lie years lost
due to disability and early death.
DALY = YLL + YLD
(YLL stands or years o lie lost (due to prema-
ture mortality) and YLD stands or years lived
with disability.)
3 . 3 .
E X P L A N A T I O N :
E N V I R O N M E N T A L B E N E F I T S
This section explains our method to assess
environmental adaptation benets. Contrary tonatural services and resources that are included in
Saved Wealth, the concept o natural ecosystems
ocuses on the intrinsic value o nature. Its major
criteria are the quality and quantity o biodiver-
sity. Thus, assessing the saving o endangered
species (fora and auna) in a qualitative manner
and the protecting o their natural habitat in a
quantitative manner can be main indicators. In
the context o the proposed ramework, a simpli-
ed approach ocuses on adequate incentives or
project developers to minimise and compensate
or potential negative environmental eects o
the given adaptation project. Thus, an environ-
mental assessment o the project will be applied,
based on evaluation criteria that can be ound in
chapter 8 (see Annex I). Ater introducing the gen-
eral concept o quantiying adaptation benets,
the next chapter describes a specic methodology
to apply the indicators in the context o coastal
protection projects.
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4.
12
M E T H O D O L O G Y
The concept developed by Perspectives is used in two ways. First, the health and wealth benets o
two coastal protection approaches are calculated. One approach is integrated coastal zone manage-
ment ocusing on mangrove planting/rehabilitation and the other is a more traditional approach o
concrete dyke building. Second, the benets o the two approaches are compared to the costs. Fur-
thermore, non-health/-wealth related environmental benets are taken into account in a qualitative
manner.
A Methodology or estimating wealth and health benefts o climate change adaptation projects:
Adapting coastal zones to rising sea levels has been prepared and can be ound in Annex I. The
ollowing section describes the main elements and data requirements. The methodology is imple-mented using a spreadsheet that includes various deault values and allows or the calculation o
benefts. Five steps are required or desiging and applying an appropriate methodology.
Dening the applicability and boundaries o the methodology
Deriving a baseline scenario
Description o project scenarios
Assessment o saved wealth, saved health and environmental benets/impacts
Denition o monitoring parameters
1
2
3
4
5
Figure 3:
Steps in assess-
ing an adaptation
project according
to a suitable
methodology
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4
The key steps 1, 2, 3 and 4 are explained in detail
in the ollowing section. Step 5 depends on the
indicator denitions rom the preceding steps, is
rather simple and can be ound in the methodol-
ogy in Annex I.
4 . 1 .
A P P L I C A B I L I T Y A N D
B O U N D A R I E S
The methodology has been designed or two main
types o intervention: (i) food prevention and
(ii) food mitigation in coastal zone areas where
negative impacts o climate change are already
occurring and/or are expected or the next 10-50
years. The methodology mainly covers physi-
cal interventions such as coastal inrastructure,
natural protection measures, erosion avoidance
and soil restoration and avoidance o salinisation.
Combinations o physical activities and capac-
ity building/policy planning measures such as
early warning systems coupled with emergency
shelters are addressed by the methodology. Stand-
alone capacity building/policy planning measures
are not suitable or a quantitative approach.
4 . 2 .
D E R I V I N G A B A S E L I N E
The baseline is the business-as-usual situation
in the project area including impacts o climate
change but excluding the proposed project
interventions. Both already observed and pre-
dicted climate change impacts have to be refected.
Adaptation measures implemented in the past and
expected autonomous adaptation orm part o the
baseline. Such data will be used to calculate pre-
dicted wealth and health losses. The ull ormula
can be ound in chapter 5 and in the Appendix.
The baseline is built rom project data on the
ground combined with deault values. The mini-
mum data requirements that cannot be provided
by deault values are listed in textbox 1 below.
4 . 3 .
C A L C U L A T I O N O F W E A L T H
A N D H E A L T H B E N E F I T S D U E
T O A N A D A P T AT I O N P R O J E C T
S C E N A R I O
The intervention to save wealth and health in the
project area is the main element o the concept.
First, the type o the project has to be specied. The
methodology covers the ollowing project types:
disaster mitigation, food protection, avoided ero-
sion and/or avoided salinisation. Specic ormulas
to calculate adaptation benets are provided in
our individual modules. Next, the required data
has to be gathered in order to provide sucient
project-specic input or the calculations. The pro-
ject specic results are then aggregated (see Project
T e x t b o x 1 :
Minimum data requirements*:
Project lietime in years
Population in start year
Total project area in hectares
Percentage o wealth and
(i applicable) health projected to
be lost due to climate change in
year t during project lietime
(i.e. percentage o wealth lost per
year during project)
*) Other values can be provided through
deault values. However, the validity o
the quantication increases when local
data are applied.
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curve has been included in the spreadsheet Saved
Health - Saved Wealth: Excel Tool (or the Dyke Case/
or the Mangrove Case)in the Damage curvetab.
Based on this requency unction curve one canderive the average damage during the project lie-
time that is prevented by the adaptation project.
As discussed above, both absolute and relative
wealth are assessed and combined in an index
result (see also section 3.1). Both components
are weighted equally and thus multiply absolute
wealth by relative wealth.
4 . 4 .S E N S I T I V I T Y A N A LY S I S
The uture development o wealth and health
conditions in the project area as well as the
impacts o climate change are very uncertain.
Thereore, a sensitivity analysis o project impacts
situationtab in the spreadsheet - modules (3)
disaster mitigation, (4) food protection, (5) avoided
erosion and (6) avoided salinisation).
A damage-requency unction o food events isthe main tool underlying both calculations. The
unction needs to be elaborated given the area-
specic situation. It demonstrates the damage
potential o an extreme event on the y-axis and
the requency on the x-axis (see gure 4). The
higher the damage potential o an event the lower
its requency. As an example, some river fooding
usually happens every year in the rainy season but
average damages are low, in part due to the adap-
tive capacity o local population. However, once
per decade, food levels are much higher leading
to signicant damages. An extreme food that on
average only happens once per century will lead
to catastrophic impacts. This relation is expressed
by the damage curve shown in gure 4. A damage
Figure 4:
Example o the
damage-requency
unction o food
events
10yr 5yr 1yr
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4
needs to be conducted. It will explore the impli-
cations o changes in major parameters and/or
changes rom minimum to maximum values.
The ollowing key parameters are to be assessed:
Extreme weather intensity and duration
Extreme weather requency
Value o public and private property
Number o deaths and incident cases
Annual maintenance costs during project
lietime
An automatically calculated sensitivity analysis
has been included in the spreadsheet Saved Health
- Saved Wealth: Excel Tool (or the Dyke Case / or the
Mangrove Case)in the Sensitivity analysistab.
4 . 5 .
A S S E S S M E N T O F
E N V I R O N M E N T A L I M P A C T S
This method only assesses sustainable develop-
ment and the environmental impacts o the adap-
tation project by means o a qualitative checklist
ocusing mainly on biodiversity. Thus, negative
impacts have to be identied and the implement-
ing entity has to describe which measures will be
implemented to mitigate such unwanted out-
comes. The assessment should include consulta-
tions with relevant stakeholders such as national
ministries, local governments, local and interna-
tional non-governmental organisations (NGOs) as
well as companies. The ull checklist or sustain-
able development can be ound on page 20 and
in the spreadsheet Saved Health - Saved Wealth:
Excel Tool (or the Dyke Case / or the Mangrove
Case)in the Sust. development check listtab.
T e x t b o x 2 :
Minimum data requirements*:
Project budget over lietime (in USD)
Maximum damage potential o
climate change impacts
Probability o occurrence o climate
change impact or every year t(i.e. probability per each year)
Negative economic impact due to
project implementation
Percentage o wealth and health
(i applicable) projected to be lost
due to climate change in year t
Total wealth o the region
*) Other values can be provided through
deault values. However, the validity o
the quantication increases when local
data are applied.
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5.C A S E S T U D Y V I E T N A M
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5
The methodology or coastal adaptation projects
has been applied to the Vietnamese case study on
coastal protection in the Au Tho B village in the
south-eastern Soc Trang province o Viet Nam.
First, the vulnerability o the coastline in the con-
text o a changing climate is described, highlight-
ing historical and expected impacts on the local
population. Second, the basic socioeconomic and
biophysical parameters o the project region are
outlined, providing the background or develop-
ing the baseline scenario. The two adaptation
options, a concrete dyke and mangrove rehabilita-
tion, are explained and the benets o each o theactivities are quantied. Third, a comparison o
both project scenarios that also takes investment
and operating costs into account is given.
5 . 1 .
V U L N E R A B I L I T Y
O F V I E T N A M S C O A S T L I N E
Viet Nam is likely to be one o the most vulner-
able nations in the world regarding impacts o
climate change. Due to its very long coastline and
river deltas with low elevation, its dependence
on agriculture (more than 70% o the population
lives in rural areas), amount o rural areas with
relatively low levels o development and expo-
sure to sea level rise and extreme meteorological
events is high, while adaptive capacity is low
(McElwee 2010, p.1).
The average surace temperature has risen by 0.7
C since 1950; the typhoon and food seasons are
longer than they used to be; heavy rainall and
fooding is becoming more requent and storms
are impacting coastal areas that had not been
aected so ar (McElwee 2010, p.1). The Soc Trang
province is particularly exposed to foods and
storm surges as well as an increasing requency o
typhoons. It is located in south-east Viet Nam (see
red circle in gure 5).
The projected sea level rise in Viet Nam will have
signicant impacts on coastal areas. As simulated
in models by the Ministry o Natural Resources
Figure 5:
Geographic distri-
bution o primary
climate exposure
hazards in Viet Nam
Source:
McElwee 2010, p.9
Flood
Flash food
Storm and typhoon
Storm surges
Not on map:
. Drought
. Salt intrusion
. Forest re
. River bank and shoreline erosion
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and the Environment (MONRE), the average sea
level at the coast o Viet Nam will likely increase
by 65 to 100 cm until the year 2100 (see table 1)
Such increases in sea level will also lead to higherimpacts o extreme events triggering e.g. ero-
sion in coastal areas; estimations o 5-10 metres
o eroded area per year have been reported (see
McElwee 2010, p.14). Annual erosion rates o up
to 30 m have been recorded or the coast o Soc
Trang Province (Jore 2010, Pham 2011). Addi-
tionally, increasing salinisation due to salt water
intrusion rom rising sea levels is a major issue or
many armers. As gure 6 shows, the whole south-
ern coastline o Viet Nam has been aected by salt
water intrusion in the year 2000; projections show
signicantly increased salinity o shallow coastal
aquiers with rising sea levels.
Summing up, the southern Vietnamese coastline
is increasingly exposed to the ollowing negative
climate impacts:
Storm surges
Floods
Erosion
Salinisation
Successul coastal adaptation projects will have
to protect public and private health as well as
human lie against one or several o the identied
impacts. As discussed in chapter Error! Reerence
source not ound. and section 4.4, all projec-
tions o climate change impacts are challenged
by uncertainty. Furthermore there are no local
projections or the Soc Trang province; only na-
tional data was available or the case study. Thus,
discount actors have been included to guarantee
conservative estimates or the achieved adapta-
tion benets and a sensitivity analysis or the
main parameters.
5 . 2 .
P R E S E N T A T I O N
O F T H E B A S E L I N E
A D A P T A T I O N O P T I O N S
A N D B E N E F I T S
The assessed community, Au Tho B village has acoastline length o 2.76 kilometres comprising
agricultural areas with adjoining mudfats and
sandbanks; the village itsel is protected by an
earth dyke and a mangrove belt (see Lloyd 2011,
p.14). This levee is aected by extreme events and
rising sea levels, requiring increased maintenance
eorts. A study conducted by the International
Low emission
scenario (B1)
Medium emission
scenario (B2)
High emission
scenario (A1F1)
Table 1: Projected average sea level rise (in cm) in Viet Nam, relative to average o the 1980-99 period, Source: MONRE (2009)
2020 2030 2040 2050 2060 2070 2080 2090 2100
11 17 23 28 35 42 50 57 65
11 17 23 30 37 46 54 64 75
11 17 24 33 44 57 71 86 100
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5
Federation o Red Cross and Red Crescent Societies (IFRC 2010) revealed costs o about USD 97,000 or
rehabilitation per kilometre o dyke per extreme event. As such extreme events historically occur in average
every ten years and are expected to increase in intensity and requency; expected maintenance or Au Tho B
sums up to more than USD 560,000 over a 20 year period.
About 169 households with about 700 inhabitants are located between the sea and the dyke (see buer
zone in gure 7). As the inhabitants o the buer zone are dependent on agricultural activities (mainly
onion cultivation) erosion and salinisation are major issues jeopardising the economic sustainability o
the local population.
Figure 7:Satellite image o
Au Tho B village
with a co-managed
zoning plan
Source:
Lloyd 2011, p. 20
Figure 6:
Salinity boundary
in the Mekong river
delta in 2000 (let)
and projection or
a 1 m sea level rise
(right);
Source:
van Sanh (2009)
< 1 g/L
1 - 4 g/L
4 - 15 g/L
> 15 g/L
Salinity boundary
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Based on the observed and expected climate
change induced impacts on Au Tho B, two
possible adaptation project scenarios have been
identied:
dyke upgrade through replacing the earth
dyke with a concrete one, or
protective mangrove belt in ront o the dyke.
The two scenarios do not ully refect the real
situation because mangrove rehabilitation has
been initiated already 20 years ago, the dykeupgrade has not been considered as an alternative
yet. So the scenarios serve as hypothetical exam-
ples, illustrating the situation o Au Tho B beore
mangrove rehabilitation.
5 . 2 . 1 . B a s e l i n e s c e n a r i o
We assume in the baseline scenario that Au Tho
B is only protected by a simple earth dyke but
not a mangrove belt. This used to be the situation
beore the year 1994, which is when the Province
o Soc Trang started mangrove rehabilitation
programmes. Hence a substantial mangrove orest
had already been in place when GIZ started the
co-management project. The aim o this activ-ity was mainly to protect and manage existing
mangroves in a sustainable manner.
Project country
Project region/community
Project start year
Total project area in ha
PLT (project lietime in years)
POP (population in start year) in project area
PGR (POP growth rate per year)
LE: lie expectancy at birth
WPCB: baseline wealth USD per capita/yr
IGR: income (GDP) per capita growth rate (%/yr)
AA: autonomous adaptation
D: discount rate o existing wealth per capita
Table 2: General baseline parameters. Source: Baseline situation tab in the spreadsheet
Parameter Value Source
Project document
Project document
Project document
Project document
Assumption
Project document
Viet Nam, 2008-2010, World Bank
Deault value, Viet Nam
Viet Nam, 2007, World Bank
Viet Nam, 2006-2010, World Bank
deault value
hal o average infation rate
Viet Nam
Au Tho B village
2007
439.28
20
700 (1277 or erosion)
1.06%
74.2
1222
5.9%
10%
0.04
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5
Based on the ollowing damage calculation, one
is able to derive the expected economic impact o
climate change driven impacts within the next 20
years (see Damage Curvetab in the spreadsheet).
Based on the likelihood o impacts, the spread-
sheet calculates average wealth losses per year (see
table 3). All categories o climate change impacts
introduced in section 3.3 are included: inra-
structure (dyke damages), loss o private property
(population in ront o the dyke), erosion and
salinisation. Total expected wealth loss is about
USD 150,000 annually or USD 2.91 million during
the lietime o the envisaged adaptation activities.The health impacts are taken rom the calculation
in the Damage curve SHtab in the spreadsheet
The baseline scenario thereore describes a rudi-
mentary dyke that can withhold extreme events
but has to be rehabilitated ater each storm surge
event. The adaptation project scenarios in the
subsequent section describe a potential situa-
tion or a coastal community in Au Tho B which
requires a decision between conventional dyke
upgrades and mangrove rehabilitation. The ull
benets and costs o a co-management system, as
implemented by GIZ in Au Tho B, are refected in
the mangrove rehabilitation scenario. The general
baseline parameters that are valid or both scenari-
os are taken rom the spreadsheet Saved Health- Saved Wealth: Excel Tool (or the Dyke Case / or the
Mangrove Case)in the Baseline situationtab.
Public inrastructure
Private property, rich
Private property,
middle class
Private property, poor
Total private property
Avoided erosion
Avoided salinisation
Total wealth losses
per year
Table 3: Expected annual wealth losses (in USD million/yr). Source: Damage Curve tab in the spreadsheet
Type o wealthTotal value: average over
lietime; defated)
10 yr
foods
6-9 yr
foods
1-5 yr
foods
2 week
spring tide Total
0.54 0.03 0.00 0.00 0.00 0.03
1.53 0.02 0.02 0.01 0.00 0.05
1.53 0.00
3.24 0.01 0.01 0.01 0.00 0.03
1.29 0.00 0.00 0.00 0.03 0.03
0.063 0.027 0.021 0.035 0.15
Table 4: Expected annual health losses (in DALYs/yr). Source: Damage Curve SH tab in the spreadsheet
Average health loss1-5 yr
foods
2 week
Spring tide Total
Averageduration(years) DALYs
10 yr
foods
6-9 yr
foods
Deaths
Fractures
Diarrhoea
...
0.03 0.1 - - 0.1 n. a. 4
0.1 0.1 - - 0.1 0.167 0.024
1.6 1.8 2.1 110.9 116 0.115 13.429
Grand total DALYs p. a. 17
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maintenance is decreased by USD 97,000 was the
construction o extreme event compared to the
rudimentary dyke that currently exists (see sec-
tion 5.2 above). As destructive extreme events his-
torically occur every ten years on average and will
become more intense and requent in the uture,
the upgrade is projected to save public wealth in
Au Tho B village totalling USD 588,000 in 20 years.
Costs or concrete dykes are USD 200,000 per
kilometre o dyke line. Thus, the ull upgrade o
Au Tho B villages levee structure is estimated to
cost about USD 550,000 or a 20 years period.
The ollowing section shows the application
o the methodology as described in chapter 3.
For the dyke upgrade, only module (3) covering
extreme events is applicable, as requent fooding,
erosion and salinisation in the buer zone are not
avoided or mitigated through the improved dyke.
5 . 2 . 2 . 1 . A p p l i c a t i o n o t h em e t h o d o l o g y
The Methodology or estimating wealth and
health benets o climate change adaptation
projects: Adapting coastal zones to rising sea
levels (see Annex I) has been applied to quantiy
the benets o the dyke upgrade. As outlined in
chapter 4, three key dimensions related to adverse
and are summarised in table 4. It outlines the
DALYs resulting rom deaths, ractures and diar-
rhoea during requent foods and extreme events
that can be expected during the 20-year lietime
o the project. One has to note that estimates re-
garding the constant diarrhoea o the population
living in ront o the dyke are mainly responsible
or the DALYs that occur. The spring tides that
occur every two weeks would food housings and
surrounding areas leading to inection. Death is
only expected during extreme events occurring
every 6-10 years. These values and estimations are
based on historical data sets rom the World Bank.
Overall projected climate change driven coastal
impacts as described above will lead to estimated
absolute wealth losses o about USD 2.9 million
and health impacts o about 350 DALYs in Au Tho
B during the upcoming 20 years without addi-
tional adaptation (see table 5).
5 . 2 . 2 . A d a p t a t i o n m e a s u r e :
D y k e u p g r a d e
The rst climate change adaptation measure
that was assessed was the construction o su-
ciently high dykes made out o concrete. Such
a structure is able to withstand storm surges or
typhoons. Damages are reduced signicantly and
WL CPLT
HL CPLT
Table 5: Wealth and health losses in baseline. Source: Baseline tab in the spreadsheet
Name Result Unit
million USD
Disability-Adjusted Lie Years
(DALYs)
Wealth losses due to
climate change during the
project lietime (absolute)
Health losses due to
climate change during theproject lietime
Description
2.9
348
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5
Index/USD million o project budget
(combined SW REL & ABS)
Absolute Saved Wealth
Saved wealth in relation to climate
change losses in the project lietime (%)
eects o climate change are assessed: economic
value at risk, health o people at risk, and envi-
ronmental benet. However, the project design
only allows or the protection o public wealth
as the adaptation impact is decreased rehabilita-
tion eort. As only extreme events are seriously
damaging the existing dyke, module (3) (disaster
mitigation) could be used or the calculation. This
module covers damages rom extreme events but
not the requent fooding rom e.g. the spring tide.
Relevant data has been gathered and ed into the
ready-to-use spreadsheet (see spreadsheet Saved
Health - Saved Wealth: Excel Tool or the Dyke Case).Calculations in the spreadsheet are based on both
specic project values or Au Tho B, mainly re-
garding dyke characteristics and national deault
values or predicted climate change impacts on
Viet Nam and regional economic development.
The calculated results in table 6 show that the
adaptation activity has a negative benet/cost
ratio. Saved Wealth (SW) in absolute terms isabout USD 530,086 or 96% o the project budget
(SWABS
indicator). The lower value o absolute SW
compared to the maintenance savings outlined
above is explained through the deault 10%
ailure rate o the adaptation activity. Taking
into account the relative wealth savings o the
local population living in Au Tho B (see also
section 3.1) which is calculated by dividing the
absolute wealth savings by the overall wealth o
the region, one can derive the mixed absolute and
relative index value (MISW) which, or the dyke
scenario, is 56,559 average personal wealth units
saved (MISWindex indicator
). I this index is divided by
the project budget one gets a MISW per million
USD o 0.1 (MISWindex per USD indicator). The
prevented losses through the dyke compared
to overall losses due to climate change impacts
are about 20% (SW%CC
indicator). The sensitivity
analysis shows that extreme weather intensity orrequency would need to increase by 5% to get a
positive benet/cost ratio in absolute terms. As
there are no additional Saved Health or envi-
ronmental benets provided through the dyke
upgrade, the adaptation measure is estimated to
be economically unavourable.
5 . 2 . 3 . A d a p t a t i o n m e a s u r e :
M a n g r o v e p l a n t a t i o n
The second project scenario assumes the planting
o a mangrove belt in ront o the shoreline (as
shown as a ull protection zone in gure 7). The
process o planting and initial growth lasts or
three years, during this timerame no adaptation
Table 6: Main results o th e Saved Wealth calculation or th e dyke scenario. Source: Saved Wealth as in the Project
situation tab in the spreadsheet Saved Health - Saved Wealth: Excel Tool or the Dyke Case
MISWINDEX per USD
MISWindex
SWABS
SW%CC:
Name Result UnitDescription
0.10
56,559
530,086
0.18
index
index
USD
index
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benets are assumed. According to Mr Hoang o
the Forest Protection Sub-department Soc Trang
(personal comment), the costs depend on the
soil and mangrove species and range between
USD 715 and USD 3,430 per hectare. Applying an
average value o USD 1,550 per hectare, planting
the ull protection zone o 160 hectares results in
overall costs o USD 250,000. Additional costs occur
through the implementation o the co-manage-
ment system in Au Tho B and rehabilitation ater
extreme events (a conservative value o 5% reha-
bilitation eort additional to the overall costs was
assumed). The overall project budget or a 20 yearperiod is estimated to be about USD 580,000. The
mangrove belt provides several adaptation benets:
The earth dyke structure is granted the same
protection against extreme events as rom a
concrete dyke upgrade.
The vulnerability o people living in ront o
the dyke to extreme events is reduced.
Mangroves deliver protection against re-
quent fooding (spring tides) that consistently
damages the private property o people
living in ront o the dyke. Health benets
are also created as requent fooding leads to
indirect health impacts through e.g. diseases.
The mangrove belt provides basic protec-
tion against erosion o agricultural land in
ront o the dyke. The economic benets o
saved area suitable or onion cultivation are
considered.
Mangroves provide protection against salini-
sation in ront o the dyke. Frequent foods
would lead to signicantly salinised soil
which makes agricultural activities impos-sible. The plantation saves 80 hectares or
onion cultivation.
The mangrove belt itsel provides economic
co-benets. The orest provides a habitat or
a wide range o aquatic species such as crabs
or snails that can be collected by the local
population. Furthermore it oers rewood
and serves as breeding place or sh. Due tomangrove co-management introduced by the
GIZ project Protected Area in the Wetlands o
Soc Trang Province on behal o BMZ, har-
vesting is conducted in a sustainable way.
Index/USD million in project budget
(combined SW REL & ABS)
Absolute Saved Wealth
Saved Health in relation to climate
change losses in the project lietime (%)
Table 7: Main results o the Saved Wealth calculation or the mangrove scenario. Source: Saved Wealth as in the
Project situation tab in the spreadsheet Saved Health - Saved Wealth: Excel Tool or the Mangrove Case
SWINDEX per USD
SWINDEX
SWABS
SW%CC
Name Result UnitDescription
1.88
1,087,337
2,324,225
0.80
index
index
USD
index
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5
Results rom planting the mangrove presented
in table 7 have a positive benet/cost ratio. The
absolute wealth savings are almost our times
higher than the overall project budget (SWABS indica-
tor). Taking into account the relative wealth savings
o the local population living in Au Tho B (see
also section 3.1) that are calculated by dividing
the absolute wealth savings by the overall wealth
o the region one can derive the mixed absolute
and relative index value (MISW) which is or the
mangrove scenario 1,087,337 average personal
wealth units saved (MISWINDEX
indicator). I this
index is divided by the project budget the result isa MISW per million USD o 1.88 (MISW
INDEX per USD
indicator). Interestingly almost 80% o the wealth
losses can be prevented through mangrove activ-
ity (SW%CC
indicator). The dierence o 20% o the
damage is explained through conservativeness
values that estimate particular adaptation ailures
as well as the time required or the mangroves to
grow until ull benets can be provided.
Besides economic benets, the mangrove orest
also reduces the vulnerability o human health
(seetable 8). Overall, an estimated 243 DALYs are
saved over the period o 20 years (SH indicator).
Per USD million in invested budget, one could
5 . 2 . 3 . 1 . A p p l i c a t i o n o t h em e t h o d o l o g y
Again, the Methodology or estimating wealth
and health benets o climate change adaptation
projects: Adapting coastal zones to rising sea lev-
els (see Annex I) has been applied to quantiy the
benets o the mangrove plantation. As outlined
above, the mangrove belt not only protects the
existing dyke rom serious extreme event damag-
es, but also enhances the resilience o the popula-
tion in ront o the dyke against requent fooding,
erosion and salt water intrusion. Thus, module
(3) (disaster mitigation), module (4) (food protec-
tion), module (5) (avoided erosion) and module
6 (avoided salinisation) have been used or the
calculation. Compared to the dyke upgrade, the
mangroves also provide economic co-benets o
more than USD 120,000 through opportunities
or shing and re wood. Again, relevant data
has been gathered and ed into the ready-to-use
spreadsheet. Calculations in the spreadsheet arebased on both Au Tho B specic project values
(mainly regarding dyke characteristics, erosion
reports or the infuence o salt water intrusion
on agriculture) and national deault values or
predicted climate change impacts in Viet Nam.
Table 8: Main results o the Saved Health calculation or the mangrove scenario. Source: Saved Health as in the
Project situation tab in th e spreadsheet Saved Health - Saved Wealth: Excel Tool or the Mangrove Case
SH
SHper$
SH%CC
Name Result UnitDescription
243
421.1
0.70
DALYs
DALYs/
USD million
index
Absolute Saved Health over project
lietime
Saved Health/USD million
in project budget
Saved Health in relation to climate change
losses in the project lietime (%)
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5 . 3 .
C O M P A R I S O N O F P R O J E C T
S C E N A R I O S
The application o the Methodology or estimat-
ing wealth and health benets o climate change
adaptation projects: Adapting coastal zones to ris-
ing sea levels shows signicantly dierent results
or the two project scenarios.
Whereas the dyke upgrade leads to a negative
benet/cost ratio over the 20 years, the mangrove
plantation provides a broader mix o adaptation
benets resulting in an overall positive evaluation.
even achieve 421 DALYs (SHper$
indicator).This
equals about 70% o the total expected climate
change induced health impacts during the project
lietime (SH%CC
).
The sensitivity analysis shows that even signi-
cant deviations o up to 20% regarding extreme
weather requency and intensity, food requency
or a stronger devaluation o public and private
property do not lead to a negative benet/cost
ratio (see gure 8). I one e.g. decreases the value
o public and private property by 20%, the Saved
Wealth index value only alls to 900,000 which
would still justiy the project costs o about
USD 580,000.
-20 -15 -10 -5 0 5 10 15 20
Deviation o criteria (in percent)
SavedWealthI
ndexvalue
1,800,000
1,600,000
1,400,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000
0
Extreme weather intensity and requency
Value o public and private propertyProject implementation and maintenance costs
Sensitivity analysis Saved Wealth MISW index
Figure 8:
Sensitivity analysis
o critical param-
eters or calculating
Saved Wealth
Source:
Sensitivity analysis
tab in the spread-
sheet Saved Health
- Saved Wealth:
Excel Tool or the
Mangrove Case
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The SWindex
per USD invested is about 1.9 or the
mangroves compared to 0.1 or the dyke upgrade.
Hence the overall economic impact (based on
the selected weighting o relative and absolute
wealth) is more avourable or the mangrove
planting. In terms o an absolute assessment o
wealth, the mangroves result USD 2.3 million
Saved Wealth versus USD 0.5 million or the dyke.
Additionally the mangroves are able to provide
health benets o 243 DALYs in 20 years whereas
the dyke upgrade does not deliver any positive
health impacts.
With regard to the results one has to take into
account that the mangrove planting is a realis-
tic scenario whereas the dyke is a hypothetical
scenario. In reality the people in ront o the dyke
might have moved to dierent places or would
have installed breakwaters to reduce requent
fooding leading to erosion and salinisation.
Nevertheless the quantication showed clear
advantages or mangroves when competing withconventional dyke constructions.
From the perspective o the ex-post impact
evaluation the indicator concept can provide the
ramework or monitoring and quantication o
benets. As the mangrove rehabilitation has been
implemented already, the exercise o calculating
Saved Wealth and Saved Health benets can be
seen as an ex-post assessment with signicant
overall positive results.
From the perspective o ex-ante cost beneft
analysis, it can be concluded that the concept
provided clear guidance to prioritise the man-
grove option. The comparison o benets with
implementation costs showed a positive outcome.
The second option, improvement o the dyke,
cannot be justied rom an economical perspec-
tive as repairing the climate change-induced
damages would actually be a cheaper option.
5
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C O N C L U S I O N S R E G A R D I N G T H E
Q U A N T I F I C A T I O N F R A M E W O R K A N D
A P P L I C A T I O N I N T H E C O N T E X T O F T H E
V I E T N A M E S E C A S E S T U D Y
By applying the methodological ramework in the
coastal zone protection sector, plausible and de-tailed inormation on the eectiveness o adap-
tation options was gained. Both the baseline and
two potential interventions have been assessed
and estimated benets have been quantied. The
comparison has shown that the mangrove belt
has signicant advantages compared to the dyke
upgrade that would not even justiy its imple-
mentation according to an economic cost/benet
assessment. The results are useul or ex-post
M&E as well as or ex-ante adaptation planning.
The indicators are suitable or hardware in-
terventions. The methodology, which is based
on a spreadsheet, allows project benets to be
quantied by applying comparable and transpar-
ent assumptions. From a technical point o view,
comparisons o projects in the same region are
preerable to comparisons o projects in dierent
countries as in the ormer case, the same datasets
regarding social and economic variables can be
applied. Projections will have the same level o
uncertainty.
We have identifed several challenges. Adaptation
based on pure capacity building projects cannot
use the quantication concept. As many coastal
adaptation interventions include inrastructure
hardware activities this shortcoming is not seen
as critical or the general applicability and dissem-
ination o the concept. It was not possible to assess
combinations o climate change induced impacts
or extreme events, e.g. sea-level rise and typhoons
or other storms, thereore they were not included.
Data gathering is challenging at a local level.
Whereas national data or natural disasters and
extreme events as well as predictions o increased
exposure are available, detailed inormation
or local areas such as the Soc Trang province
are lacking. This prevents accurate results and
challenges comparability within one country.
The uncertainty o climate change projections is
high or many parameters. It hampers the proper
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6
quantication o adaptation benets. However,
this uncertainty also exists in the case o other
adaptation planning methods. The tool requires a
good understanding o economic methods such
as CBA and possible impacts o climate change
rom its users. Ideally, it is applied by central
government planners in host country capitals
evaluating all adaptation projects rom dierent
donors, or example in the context o the biennial
update reports under the UNFCCC. In terms o
applying the ramework or M&E, it might also
be challenging or local project managers to use a
standardised set o quantiable criteria includinga detailed development o a baseline instead o
other non-standardised indicators as in ormer
projects. Thus it seems useul to develop a simpli-
ed version to allow easy access to this new tool.
Recommendations or urther improvements
that have been identied in the context o this
study include support or enhanced publicly
available climate change exposure projections.
They would make the tool more robust. A source
or such improvements would be the interna-
tional disaster database (http://www.emdat.be/)
that will be expanded to include local levels in
the uture. Identication o local data will be
unavoidable i project developers do not want to
rely on the national deault values included in the
spreadsheet.
Methodologies or other adaptation sectors
should be developed and tested in the uture, also
in cross-sector and cross-country comparisons.
This will require substantial data collection
eort. The methodologies should be tested with
users o dierent education levels in dierent
cultural backgrounds, ideally through hands-on
workshops. As a starting point, this methodology
can be increasingly used or M&E o adaptation
projects in coastal zone activities to identiy spe-
cic challenges and requirements o local project
developers in dierent locations.
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30
Binnendijk, A. (2001): Results-based manage-
ment in the development co-operation agencies:
A review o experiences background report,
OECD, Paris
http://www.oecd.org/dataoecd/17/1/1886527.pd
GIZ (2012): Adaptation made to measure. A guide-
book to the design and results-based monitor-
ing o climate change adaptation projects [An
updated version will be available by November
2013 on AdaptationCommunity.net under Knowl-
edge Management > Monitoring and Evaluation >
Further reading].
GIZ (2013): Economic approaches or assessing
climate change adaptation options under uncer-tainty. [Accompanied by two Excel tools available
on AdaptationCommunity.net under Knowledge
Management > Monitoring and Evaluation >
Tools and Training Material]
GTZ (2008): Results-based Monitoring Guide-
lines or Technical Cooperation, GTZ, Eschborn
IFRC (2010): Breaking the waves. Impact analysis o
coastal aorestation or disaster risk reduction in
Viet Nam, Published by International Federation o
Red Cross and Red Crescent Societies (IFRC)
Jore, O. (2010): Mangrove Dynamics in Soc Trang
Province 1889 1965. Deutsche Gesellschat r
Technische Zusammenarbeit (GTZ) GmbH, Man-
agement o Natural Resources in the Coastal Zone
o Soc Trang Province, Viet Nam
http://czm-soctrang.org.vn/en/Publications.aspx
Lloyd, R. (2011): Co-management in Au Tho B Vil-
lage: A pilot test or the coastal zone o Soc Trang
Province, GIZ, Eschborn
McElwee, P. (2010): The Social Dimensions o
Adaptation to Climate Change in Viet Nam, pub-
lished by World Bank, Washington
Michaelowa, A.; Khler, M. (2011): Monitoring theadaptive eect o GIZs natural resource man-
agement and adaptation projects, Perspectives,
Hamburg
Moench, M.; Fajber, E; Dixit, A; Caspari, E; Pokhrel,
A (2009): Catalyzing climate and disaster resilience.
Processes or identiying tangible and economi-
cally robust strategies. Final Report o the Risk to
Resilience Study, Institute or Social and Environ-mental Transition, Kathmandu
MONRE (2009): Ministry o Natural Resources and
R E F E R E N C E S
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Environment Viet Nam. Climate change, sea level
rise scenarios or Viet Nam, Hanoi
Parry, M.; Arnell, N.; Berry, P.; Dodman, D.;
Fankhauser, S.; Hope, C.; Kovats, S.; Nicholls, R.
(2009): Assessing the costs o adaptation to cli-
mate change. A review o the UNFCCC and other
recent estimates, Imperial College, London
Pham, T.T. (2011): Mangroves o Soc Trang 1965
2007. Deutsche Gesellschat r Internationale
Zusammenarbeit (GIZ) GmbH, Management o
Natural Resources in the Coastal Zone o Soc
Trang Province, Viet Nam.
http://czm-soctrang.org.vn/en/Publications.aspx.
Spearman, M.; Mc Gray, H. (2011): Making Adapta-
tion Count: Concepts and Options or Monitoring
and Evaluation o Climate Change Adaptation,
WRI, Washington
UNFCCC (2007): Investment and Financial Flows
to Address Climate Change, United Nations
Framework Convention on Climate Change, Bonn
UNFCCC (2010): Synthesis report on eorts
undertaken to monitor and evaluate the imple-
mentation o adaptation projects, policies and
programmes and the costs and eectiveness o
completed projects, policies and programmes, and
views on lessons learned, good practices, gaps
and needs, FCCC/SBSTA/2010/5, Bonn
Van Sanh, N. (2009): Climate change impacts on
the Viet Nam Mekong river delta, http://ns1.mrc-
mekong.org/download/Presentations/2nd-BDP-
reg-stakeholder-orum/1.3.3-Dr-Sanh-climate-
change-ver091009.pd
WHO (2010): Global Burden o Disease. World
Health Organization, Geneva
World Bank (1993): World Development Report
1993: Investing in health. Oxord University Press,
Oxord
7
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Figure 9: P. 36
Boundary o this methodology
Figure 10: P. 41
Model to estimate the wealth and health
benets o the project
Figure 11: P. 43
Example o a damage-requency unction
o food events. Disaster mitigationmodule (3).
Figure 12: P. 45
Example o a damage-requency unction
o food events. Flood protection
module (4).
Figure 13: P. 50
Reerence map o vulnerable coastal
delta hotspots
Table 9: P. 38
Checklist o climate change impacts
on coastal zones
Table 10: P. 45
Example o wealth loss per
food event
Table 11: P. 45
Example o wealth loss per year
in % o total wealth
Table 12: P. 46
Example o average wealth loss
per year in USD million
Table 13: P. 48
Parameters to be assessed by
sensitivity analysis
Table 14: P. 51
Checklist or environmental impacts
and sustainable development
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APPENDIX
M E T H O D O L O G Y F O R E S T I M A T I N G W E A L T H A N D H E A L T H
B E N E F I T S O F C L I M A T E C H A N G E
A D A P T AT I O N P R O J E C T S :
A D A P T I N G C O A S T A L Z O N E S T O R I S I N G S E A L E V E L S
C o n t e n t
1. Abbreviations 34
2. Purpose and Applicability o this methodology 34
3. Denitions 35
4. Applicability and boundary o methodology 36
5. Baseline situation 37
6. Project situation 40
7. Sensitivity Analysis 47
8. Monitoring 48
9. Annex 50
10. Reerences 52
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1 .
A B B R E V I A T I O N S
C degree Celsius
g grams
ha hectares
LY lie years
m square metres
mm millimetres
PPP purchasing power parity
t metric tonnes
USD 2009 US dollars (USD have to be trans-
ormed to 2009 USD through division
using ocial DAC defators or the United
States, see http://www.oecd.org/dataoecd/
43/43/34980655.xls (OECD, 2012)
yr year
2 .
P U R P O S E A N D A P P L I C AT I O N
O F T H I S M E T H O D O L O G Y
This methodology helps project developers and
policy makers to assess the wealth and health
benets as well as environmental impacts o
climate change adaptation projects in coastal
zones. It is applicable or interventions protect-ing coastal zones against sea level impacts such
as inrastructure improvements (e.g. seawall
construction), natural protection measures (e.g.
mangrove plantations or sand dune stabilisation
through vegetation), erosion avoidance/restora-
tion (e.g. soil conservation, beach replenishment),
avoidance o salinisation (e.g. drainage, water
table control) and early warning systems. Accord-
ing to the specic intervention, several modules
or common climate change-induced impacts are
available (e.g. extreme events, requent fooding
or salt water intrusion). These modules can be
specically adjusted and expanded according to
the envisaged project type.
The methodology can both help to identiy
promising interventions and compare proposed
projects. It provides eectiveness criteria to assess
ex-ante where adaptation measures can bring
about the largest benets or the least cost, and to
assess ex-post whether or not an adaptation inter-
vention has been successul.
Target group
The main target group o the methodology is the
one o developers o climate change adaptation
projects in coastal zones. By applying the method-
ology, they can quantiy benets and negative im-
pacts o interventions in the context o monitor-
ing and evaluation ater project implementation
(ex-post). Furthermore the methodology provides
an approach in the context o cost benet analysis
which allows assessing ex-ante where adaptation
measures can bring the largest benets or the
least cost.
The secondary target group besides project devel-
opers is the one o policy makers who may use the
methodology to compare the wealth and health
benets o dierent climate change adaptation
projects. As the calculation requires detailed data
rom projects, policy makers will have to coop-erate with project developers. I policy makers
consider wealth and health benets as major
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Several shortcomings have been identied:
External terrestrial infuences (such as foods
coming rom rivers) are only covered marginally;
non-water related storm impacts (e.g. typhoons),
a closer link to climate change impacts and more
comprehensive fow charts/systems diagrams are
missing.
3 .
D E F I N I T I O N S
Baseline:
business-as-usual (social, economic and environ-
mental) situation in the project area including
impacts o climate change but excluding the
proposed project interventions.
Negative impact:
Unwanted eect o a project intervention on
parameters where the project mainly has positive
impacts (e.g. dyke construction). Not restricted
to impacts within the project boundary but also
beyond.
Saved Wealth:
Positive economic impact o the proposed project,
measured by changes in economic assets during
the project period compared to the baseline de-
velopment. While it primarily ocuses on income
and wealth endangered by climate change, other
economic benets are also accounted or.
Saved Health:
Positive health impact o the proposed project,
primarily by preventing deaths and illness due to
climate change impacts.
outcomes o climate change adaptation projects,
this methodology may also inorm decisions on
how to allocate adaptation unding.
Application
The simplest way o applying the methodology is
to ll out the spreadsheet Saved Health - Saved
Wealth: Excel Tool or the Dyke Case / the Man-
grove Case. This spreadsheet contains global de-
ault values, reerences tables or national deault
values and automatically calculates the benets
ater some basic project data is entered. The text
o the presented methodology is a reerence
document to better understand the assumptions
used to calculate the wealth and health benets.
Revision o the methodology
This methodology is considered to be work in
progress. The methodology simplies the real
world and new scientic evidence will make it
necessary to revise assumptions. Thereore, userso this methodology as well as other interested
persons are invited to suggest revisions or addi-
tions to this methodology.
Limitations o methodology
(areas or improvement)
Due to the complexity and the variety o potential
adaptation activities the methodology distin-
guishes between our intervention areas but does
not give detailed calculations or each possible
adaptation activity. The project developer will
have to justiy detailed calculations or specically
applied activities2. Typical interventions are listed
at the end o each module.
2 In parallel to the methodology, specic calculation models
have been developed or dykes, wave-breaking barriers and
mangrove planting/rehabilitation.
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4 .
A P P L I C A B I L I T Y A N D
B O U N D A R Y O F M E T H O D O L O G Y
This section describes the sectors, subsectors
and interventions to which this methodology
can be applied. Figure 9 shows the boundary
(orange line) o the methodology with regard to
sectors and type o intervention. Regarding the
latter, stand-alone capacity building and policy
planning has been distinguished rom physical
interventions. The orange line represents the
boundary describing the kind o intervention that
can be assessed with the methodology.
Sectoral boundary:
The methodology is applicable to interventions
protecting coastal zones such as
a) Inrastructure improvements
(e.g. seawall and dyke construction)
b) Natural protection measures
(e.g. mangrove plantations or sand dune
stabilisation through vegetation)
c) Erosion avoidance and soil restoration
(e.g. soil conservation, beach replenishment)
d) Avoidance o salinisation
(e.g. drainage, water table control)
Projects involving non-rising sea level related
activities (e.g. typhoons/wind disaster protection,
resh water supply, ood security etc.) have to be
assessed using dierent methodologies.
Protection opublic & pivate
property
Agriculturalproduction
Houses, jobs,inrastructure
e.g. tourism,shing
e.g. relocationo population
e.g. earlywarning systems
e.g. coastalinrastructure
e.g. erosionavoidance & soil
restoration
e.g. naturalprotectionmeasures*
e.g. avoidanceo salisination
Stand alone
capacity
building/
policy
planning
Physical
interventions
Physical
interventions &
capacity
building/policy change
Soilconservation,dune creation
Wetland crea-tion, mangrove
planting
seawallconstruction
Radio stations,disaster plans
Services
*) includeswetland protection
Impact SectoralOutcome
SubsectoralOutcome
Intervention area(examples)
Type ointervention
Protectedpopulation
Saved Health/Wealth
Drainage, watertable controlling
Drinking wateravailability
New coastalzone related
income sources
Figure 9:
Boundary o this
methodology
(symbolised by
orange line)
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only quantiy economic and health benets but
also assess i the project results in any major harm
to the environment, society or the economy. For
this purpose, the sustainable development check-
list in the Appendix shall be completed.
5 .
B A S E L I N E S I T U AT I O N
The baseline is the business-as-usual situation
in the project area including impacts o climate
change but excluding the proposed project
interventions.
a . D e s c r i p t i o n o c h a n g i n g c l i m a t e
Have any climate change trends been measured in
the last 10-50 years that are in line with expecta-
tions rom climate models?
Are any climatic changes expected or the next
decades in the project area?
Climate parameters to be considered include:
Sea level increase (in mm/yr)
Temperature (in C)
Extreme events relevant or coastal zones (e.g.
storm surges, foods), number o events per
year
Sources: ocial records or past (at least 10 years
o data, linear trend to be assessed) and climate
models or the uture. While current climate
models still ace major challenges when predict-
ing local temperature and precipitation changes
in the next 10 years (van Oldenborgh et al.,
orthcoming), they are the only source o avail-
able inormation to date. Thus, project developers
Type o intervention:
The project has to include concrete, physical
interventions (e.g. inrastructure investments,
soil conservation). Policy planning and capacity
building can also be part o the project but only
benets connected to the physical interventions
are accounted or. Stand-alone capacity building
or policy planning projects are to be assessed us-
ing dierent methodologies.
Geographic boundary:
The project covers the area where the project
interventions take place, e.g. the area inhabited by
beneciaries o direct ood distribution and arm-
ers targeted by other interventions.
Link to climate change impacts:
The project should intervene in coastal zone areas
(e.g. avoided erosion, coastal protection measures)
where negative impacts o climate change are al-
ready occurring and/or are expected or the next
10-50 years (see e.g. reerence map o vulnerable
coastal delta hotspots in the Appendix). As long as
this condition is given, all economic and health
benets o the project are accounted or, includ-
ing benets beyond projected climate change
damages (award or overcoming the adaptation
decit).
Project period:
Time during which the project interventions
have a direct impact on coastal zo