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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

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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 .


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 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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15

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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16

5.C A S E S T U D Y V I E T N A M


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17

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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18

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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19

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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20

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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21

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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22

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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23

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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24

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


1.88

1,087,337

2,324,225

0.80

index

index

USD

index


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25

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


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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26

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


29/56

27

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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6.

28

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

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