Eacc ghana

G h a n a CO U N T RY ST U DY i

Economics of Adaptation to Climate Change

GHANA

ii E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

EACC Publications and Reports

1. Economics of Adaptation to Climate Change: Synthesis Report
2. Economics of Adaptation to Climate Change: Social Synthesis Report
3. The Cost to Developing Countries of Adapting to Climate Change: New Methods
and Estimates

Country Case Studies:
1. Bangladesh: Economics of Adaptation to Climate Change
2. Bolivia: Adaptation to Climate Change: Vulnerability Assessment and Economic Aspects
3. Ethiopia : Economics of Adaptation to Climate Change
4. Ghana: Economics of Adaptation to Climate Change
5. Mozambique: Economics of Adaptation to Climate Change
6. Samoa: Economics of Adaptation to Climate Change
7. Vietnam: Economics of Adaptation to Climate Change

Discussion Papers:
1. Economics of Adaptation to Extreme Weather Events in Developing Countries
2. The Costs of Adapting to Climate Change for Infrastructure
3. Adaptation of Forests to Climate Change
4. Costs of Agriculture Adaptation to Climate Change
5. Cost of Adapting Fisheries to Climate Change
6. Costs of Adaptation Related to Industrial and Municipal Water Supply and
Riverine Flood Protection
7. Economics of Adaptation to Climate Change-Ecosystem Services
8. Modeling the Impact of Climate Change on Global Hydrology and Water Availability
9. Climate Change Scenarios and Climate Data
10. Economics of Coastal Zone Adaptation to Climate Change
11. Costs of Adapting to Climate Change for Human Health in Developing Countries
12. Social Dimensions of Adaptation to Climate Change in Bangladesh
13. Social Dimensions of Adaptation to Climate Change in Bolivia
14. Social Dimensions of Adaptation to Climate Change in Ethiopia
15. Social Dimensions of Adaptation to Climate Change in Ghana
16. Social Dimensions of Adaptation to Climate Change in Mozambique
17. Social Dimensions of Adaptation to Climate Change in Vietnam
18. Participatory Scenario Development Approaches for Identifying Pro-Poor Adaptation Options
19. Participatory Scenario Development Approaches for Pro-Poor Adaptation: Capacity
Development Manual

G h a n a CO U N T RY ST U DY i

Economics of Adaptation
to Climate Change

G hana

Ministry of Foreign Affairs
Government of the Netherlands

ii E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

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G h a n a CO U N T RY ST U DY iii

Contents

Abbreviations and Acronyms vii
Acknowledgements ix
Caveat xi

Executive Summary xiii
Impacts of Climate Change xiii
Adaptation to Climate Change xiv
Lessons and Policy Recommendations xiv

1 Introduction 1
Study Objectives 2
Organization of Report 3

2 Overview of the EACC Global Track Study 5

3 Methodology 11
Overall Approach and Key Assumptions 11
Climate Forecasts 12
Sector-Specific Approaches 14

4 Study Results 35
Overview of the Ghanaian Economy 35
Climate Change Projections 39
Economic Impacts of Climate Change – CGE Model Results 42
Economic Implications of Adaptation to Climate Change – CGE Model Results 54
Adaptation Options 57
Adaptation Costs 59
Social Dimensions 62

iv E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

5 Summary and Policy Implications 69
Climate Change Impacts 69
Adaptation to Climate Change Costs 70
Looking forward 70
Summary Matrix 73

References 77

Annexes (available on line at www.worldbank.org/eacc)

Annex 1. Cli-Crop Modelling for Agriculture
Annex 2. Dose-Response Model for Roads
Annex 3. IMPEND Model for Energy and Water
Annex 4. DIVA Model for Coastal Zone
Annex 5. Social Dimensions of Climate Change
Annex 6. Computable General Equilibrium (CGE) Modeling

Tables

Table 1. Total Annual Costs of Adaptation for All Sectors, by Region, 2010–50 7
Table 2. Total Annual Costs of Adaptation for all Sectors, by Region and Period, 2010–50 7
Table 3. A Comparison of Adaptation Cost Estimates ($ billions) 8
Table 4. GCM Scenarios for Ghana Country Track Study 12
Table 5. Trends in the Growth Rate of the Transport Sector 19
Table 6. Share of the Transport Sector in Total GDP in Purchaser’s Value, 2002–2007 (%) 19
Table 7. Road Sector Vulnerability to Potential Climate Change 20
Table 8. Dose-Response Descriptions for Maintenance Costs 20
Table 9. Electricity and Water Subsectors Growth Rates of Real GDP 23
Table 10. Electricity and Water’s Share of GDP and Contribution to Overall GDP Growth 23
Table 11. Projected Population of the Coastal Regions and

Estimated Population at risk to Sea Level Rise 27
Table 12. Land Area Distributions of the Ten Provinces of Ghana, divided into three zones 30
Table 13. Economic Development Indicators in Ghana, 2005 to 2008 36
Table 14. Temperature (Co) in Regional CC Scenarios, 2010–50 38
Table 15. Precipitation Projections for Ghana’s 16 subbasins – Descriptive Statistics 41

G h a n a CO U N T RY ST U DY v

Table 16. Standard Deviation of Annual Real Consumption Growth 45
Table 17. Welfare Impact without Adaptation Investments 45
Table 18. DIVA Annual Results for High Sea Level Rise Scenario 51
Table 19. DIVA Annual Results for Low Sea Level Rise Scenario 52
Table 20. Mean, Standard Deviation, and Extreme Values of Annual GDP

Growth Rates by Region, 2006–50 53
Table 21. Deviations of Welfare from Baseline under Alternative Adaptation Strategies 56
Table 22. Average Annual Real GDP Growth Rates (2010–50)

under Alternative Adaptation Strategies (%) 56
Table 23. Regional Shares in Agricultural Production by Commodity 60
Table 24. Commodity Composition of Agricultural Production by Region 61
Table 25. Summary of Ghana Coastal Seal Level Rise (SLR) Annual Adaptations Costs 65
Table 26. Summary recommendation on low-regret options and policy interventions

in short and long term following the Ghana EACC Analysis 74

Figures

Figure 1. Shares of the Total Annual Costs of Adaptation by Region 2010–50 7
Figure 2. Flow Chart of Model Sequencing 14
Figure 3. Trends in the Growth Rate of the Agricultural Sector, 2002–10 16
Figure 4. Rural-Urban Potable Water Coverage by Region, 2006 and 2007 (%) 26
Figure 5. Ghana, West Africa: (a) Geographical location, (b) Administrative units

(termed provinces) and major coastal towns, and (c) The coastal zone 29
Figure 6. Ghana Sector Contribution to the GDP 37
Figure 7. Annual Real Growth Rate by Sector, 2002–09 37
Figure 8. Ghana Dry Scenario Temperature Changes Compared to Base, 2010–50 39
Figure 9. Temperature Variability Compared to Base 40
Figure 10. Surface flow average difference from the no-climate change scenario, 2010–50 41
Figure 11. Annual Deviations of Real GDP from Base, 2010–2050 (%) 42
Figure 12. GDP Growth Path in Levels 2010–2050 43
Figure 13. Terminal Period Real GDP (average annual GDP, 2046–50) 43
Figure 14. Terminal Real Household Consumption Level

(annual average, 2046–50) relative to 2005 Level 45
Figure 15. Decomposition of Climate Change Impacts on Present Vale of Real Absorption

(deviation from base in billion $) 46

vi E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

Figure 16. Average Annual Agricultural Real GDP, terminal period 2046–50 46
Figure 17a. Real GDP Deviation from Base for Maize, 2020–50 47
Figure 17b. Real GDP Deviation from Base for Cocoa, 2020–50 47
Figure 17c. Real GDP Deviation from Base for Cocoa, South Savannah 2020–50 47
Figure 18. Climate Change Impacts of Cocoa Productivity in Ghana

(deviations from baseline yields) 48
Figure 19. Decadal Average Ratios of Future Livestock Net Revenues to Net Revenues under

Baseline Conditions, Ghana Dry (on left) and Wet (on right) Scenarios, 2001–50 50
Figure 20. Decadal Average Ratios of Future Livestock Net Revenues to Net Revenues under

Baseline Conditions, Global Dry (on left) and Wet (on right) Scenarios, 2001–50 50
Figure 21. Average Annual Water and Energy Sector Real GDP, 2046–50 51
Figure 22. Deviations of Welfare from Baseline under Alternative Adaptation Strategies 56
Figure 23. Annual Road Maintenance Costs, 2010–50 63
Figure 24. Annual Average Road Maintenance Costs, 2010–50 63
Figure 25. Total Energy Adaptation Costs 63

G h a n a CO U N T RY ST U DY vii

Abbreviations
and Acronyms

AR4 Fourth Assessment Report ITCZ Inter-Tropical Conversion Zone
BAU Business-as-usual LCA Latin America and Caribbean Region
CAADP Comprehensive Africa Agriculture MDGs Millennium Development Goals
Development Program NCAR National Center for
CGE Computable general equilibrium Atmospheric Research
CO2 Carbon dioxide NAPA National adaptation plans of action
CMI Climate moisture index NCCAS National Climate Change
CSIRO Commonwealth Scientific and Adaptation Strategy
Industrial Organisation NGO Nongovernmental organization
DIVA Dynamic and interactive ODA Official development assistance
vulnerability assessment PaMs Policies and measures
EACC Economics of Adaptation PET Potential evapotranspiration
to Climate Change Ppm Parts per million
EAP East Asia and Pacific Region RD Research and development
ECA Europe and Central Asia Region SAS South Asia Region
ENSO El Niño-Southern Oscillation SRES Special Report on Emissions
GCM General circulation model Scenarios
GDP Gross domestic product SSA Sub-Saharan Africa
GHG Greenhouse gases SST Sea surface temperature
GIS Geographical information system TAR Third Assessment Report
GPRS Ghana Poverty Reduction Strategy UNDP United Nations Development
GWCL Ghana Water Company Limited Programme
HDI Human Development Index UNFCCC United Nations Framework
IFPRI International Food Policy Convention on Climate Change
Research Institute VRA Volta River Authority
IMPACT International model for policy
analysis of agricultural
commodities and trade
IPCC Intergovernmental Panel
on Climate Change Note: Unless otherwise noted, all dollars are U.S. dollars.

G h a n a CO U N T RY ST U DY ix

Acknowledgments

This study would not have been successfully the specific situation of Ghana. Particularly, we
completed without the inputs of a large number gratefully acknowledge Dirk Willenbockel, Ken
of organizations and individuals. Profound grat- Strzepek, Eihab Fathelrahman, Robert Nicholls,
itude goes to officials from all the government Len Wright, Chas Fant, Paul Chinowsky, Chan-
ministries, departments, and agencies, who con- ning Arndt, Sherman Robinson, Michelle Mini-
tributed immensely to the success of the study by hane, William Farmer, Brent Boehlert, Alyssa
providing data and other information for the McClusky, and Jean-Marc Mayotte. Thanks also
analysis as well as the validation of methodology to the social scientist team that developed the
and adaptation options. social dimensions of climate change, including
Tony Dogbe, Joseph Yaro, David Pessey, Emilia
In particular, we would like to recognize the Arthur, George Ahiable, Tia Yahaya, Kamil
teams at the Environmental Protection Agency, Abdul Salam, Samantha Boardley, Simon Mead,
Ministry of Environment, Science and Technol- and Livia Bizikova. In Ghana, consultants Daniel
ogy, Ministry of Finance and Economic Plan- Sarpong, Dyson Jumpah, and Philip Acquah
ning, the National Development Planning reviewed sector strategies and adaptation options,
Commission, and Ministry of Agriculture. In and Saadia Bobtoya supported the team with
particular, we would like to thank William Agye- information management and communications.
mang-Bonsu, Jonathan Allotey, Alhassan Iddi- The technical writer for Ghana Case was John
risu, David Quist, Rudolph Kuuzegh, George Asafu-Adjaye.
Scott, Winfred Nelson, and Regina Adutwum
for the overall guidance provided in the course The team would also like to thank development
of the study. Many more contributed with ideas partners in Ghana for excellent coordination of
and technical input in July, August, and October work related to this study, including Sean Doolan
of 2009 during workshops and meetings, and (United Kingdom Department for International
well as during the final validation workshop in Development), Ton van der Zon (Royal Nether-
September 2010. lands Embassy), Wagn Winkel (Royal Danish
Embassy), Shigeki Komatsubara and Stephen
We wish to also acknowledge the inputs of the Duah-Yentumi (United Nations Development
global modeling team for their diligence in fitting Program), and Jannik Vaa (European
climate change scenarios and economic models to Commission).

x E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

The study was kindly financed by the govern- Mearns, Sergio Margulis (team leader of the
ments of the United Kingdom, The Netherlands, overall EACC study) , Stephen Mink, Urvashi
and Switzerland, as well as the governments of Narain, and Victoria Bruce-Goga. Several Bank
Norway and Finland through the Trust Fund for staff have commented and provided insight to
Environmental and Social Sustainable Develop- sectors covered in this report, including Ajay
ment (TF-ESSD) and the World Bank. Kumar, Chris Jackson, Herbert Acquay, Ishac
Diwan, John Richardson, Osman Kadir,
The World Bank Task Team included Peter Sebastien Dessus, Shelley McMillan, and Sunil
Kristensen (Task Team Leader), Aziz Bouzaher, Mathrani. Robert Livernash provided editorial
Anne Kuriakose, John Fraser Stewart, Kiran services, Jim Cantrell contributed editorial input
Pandey (Coordinator EACC country studies), and coordinated production, and Hugo Mansilla
Raffaello Cervigni, Robert Schneider, Robin provided editorial and production support.

G h a n a CO U N T RY ST U DY xi

Caveat

This study is experimental and innovative in
nature. The CGE modeling has made use of
many assumptions to estimate the economics of
adaptation to climate change in Ghana in a long
time horizon. The numbers and results in the
report should be used with caution, and consid-
ered indicative. While the report suggests short
and long-term policy and investment options, the
authors believe that further review of the cost-
benefit of adaptation options should be
undertaken.

G h a n a CO U N T RY ST U DY xiii

Executive Summary

Impacts of Climate Change fluctuations will increase the risk of floods and/or
droughts in both rural and urban areas. Because most
Climate change is projected to have significant impacts of these changes are caused by upstream areas out-
on Ghana. Although there will be fluctuations in both side the territory of Ghana, there is a need for dia-
annual temperatures and precipitation, the trend for logue with Ghana’s neighbors on the management of
temperature over the period 2010–50 indicates warm- shared water resources.
ing in all regions. The highest temperature increases
will be in the Northern, Upper East, and Upper West Because Ghana’s economy is predominantly based
regions, while the lowest will be in the Brong Ahafo on agriculture, it will suffer severe economic conse-
region. For example, under one of the climate scenar- quences from climate change. Although there will be
ios (Ghana Dry), temperatures in the three regions of considerable variation in real gross domestic product
the North will rise by 2.1–2.4°C by 2050. In compari- (GDP) growth, the overall trend over 2006–50 clearly
son, the predicted rise in the Ashanti, Western, East- indicates a downward trajectory in the absence of
ern, Central, and Volta regions will be 1.7–2.0°C, and adaptation to climate change. Toward 2050, annual
the rise in the Brong Ahafo region will be 1.3–1.6°C. real GDP is projected to be 1.9 to 7.2 percent lower
than in a dynamic baseline scenario without anthro-
The forecast for precipitation indicates a cyclical pogenic climate change. Real household consump-
pattern over the period 2010–50 for all regions, with tion also declines relative to the base scenario in all the
high rainfall levels followed by a drought every four climate change scenarios analyzed in this study.
decade or so. The wettest parts of the country are
expected to be the Forest agroecological zone Adverse agricultural productivity impacts become
(Ashanti and Western regions) and Coastal agroeco- more pronounced over time. Relative to the baseline
logical zone (Volta, Eastern, Central, and Greater projection for the middle of the 21st century, agricul-
Accra regions). The northern and southern Savan- tural GDP is estimated to decline by 3 to 8 percent.
nah zones are expected to be relatively dry. The projections for cocoa pose serious socioeconomic
implications in view of cocoa’s significant contribu-
There will also be wide fluctuations in runoff and tion to national income and farmers’ livelihoods.
stream flows, with areas in the Volta basin experienc-
ing significant reductions in runoff, while the south- Damage to the coastal zone in the form of flooding,
western area will experience increases. These land loss, and forced migration is estimated to be

xiv E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

$4.8 million per annum by the 2020s, rising to Incomplete partial equilibrium modeling puts econo-
$5.7 million per annum by the 2030s. mywide adaptation costs in a mid-range of $300–
$400 million per annum. Partial equilibrium, as
The predicted climatic changes will have adverse opposed to the general equilibrium approach, consid-
effects on human well-being and activities, food secu- ers each subsector of the economy in isolation from
rity, and water availability. In response to these climate the other sectors when it comes to prices and income
changes, people will migrate in search of better land interactions among stakeholders.
and environment. The migration and relocation of
population from rural to urban areas will raise
demand and put pressure and on municipal ser- Lessons and Policy
vices—including water supply and sanitation, public Recommendations
health, energy, transportation, and housing services.
Such higher demand coupled with weak infrastruc-
ture and lack of services will slow economic growth Agriculture
and development. Migration will occur not only There is a need to (a) increase investment in agri-
within the country, but also from countries to the north cultural RD, backed by extension services, to
of Ghana, which will also become hotter and drier. produce new crops and livestock, as well as early-
maturing varieties; (b) improve water storage
capacity to utilize excess water in wet years and
Adaptation to Climate use it when it is needed during dry years; (c)
Change improve agricultural and livestock extension ser-
vices and marketing networks; (d) construct small
to mid-size irrigation facilities; (e) improve entre-
Adaptation in this study is aimed at restoring aggre- preneurial skills to generate off-farm income
gate national output to baseline, rather than restoring (alternative livelihoods); and (f) improve access to
each sector to the baseline. This suggests that even loans and microcredit.
with adaptation, there will still be some residual dam-
age at the sector level. Given the scarcity of resources Road transport
at the government’s disposal, tough choices must be Recommended actions include proper timing of road
made in the design and sectoral balance of the construction; for example, before the rainy season.
national development strategy in light of the chal- There is also a need to ensure routine and timely
lenges posed by climate change. maintenance; review overall road design criteria,
including materials and drainage, road sizes, and pro-
In the absence of adaptation, climate change tection of road shoulders; and reform road design
causes a decline in real output growth for all the standards to meet higher needs against extreme
global circulation model (GCM) results. Planned events such as floods and droughts.
adaptation can be effective in compensating the
adverse impacts of climate change. Water and energy
Recommended hard options for the water subsec-
The general equilibrium modeling indicates that tor include increased water transfer from the Volta
losses in agriculture could be as much as $122 mil- basin to meet the needs of a growing urban popu-
lion per annum, while losses in transport and hydro- lation; construction of efficient infrastructure; and
power could be up to $630 million and $70 million, blocking of dry-stream channels to harvest rainwa-
respectively. Total economywide impacts are esti- ter to recharge the groundwater system, which
mated to range from $158–$765 million per annum. serves as an alternative water supply during dry

G h a n a CO U N T RY ST U DY xv

years. A number of soft options were also deemed level. The poorest are particularly vulnerable to
to be of high priority: afforestation, improved land climate shocks, as they do not have stored assets to
use practices, protection of river courses, and use during times of stress. A pro-poor approach
desedimentation of reservoirs. to climate change adaptation would look not only
at reducing shocks to households, but also engage
Diversification of the energy mix and development in transformative adaptation strategies that
of renewable sources—such as solar, wind, biomass, increase resilience and overcome past biases in
waste conversion, and mini-hydro dams—are priori- subnational investment.
ties, as are soft options such as promoting policies and
measures aimed at enhancing energy efficiency in all Geographically targeted, multisectoral interventions
sectors. The government also should commit to a are needed to reduce the “development deficit” of
strict infrastructure maintenance regime. vulnerable regions. Poverty and sensitivity to climate-
related hazards are increasingly concentrated in par-
Coastal zone ticular regions within the country. In many cases,
The modeling results generally show that the poor communities—such as recent urban in-
investment costs of coastal zone adaptation are migrants—are relegated to the most marginal areas
likely to be uneconomic because the costs are likely of the city. Adaptation policies at the national level
to far exceed any benefits, so defending the entire must take into account the diverse socioecological set-
coastline by building dikes and sea defense walls is tings within the country, and devise area-specific
not a sensible strategy. A better strategy would be interventions that can support the livelihoods of these
to protect key investments and natural resources— vulnerable populations. Multisectoral interventions
ports, harbours, beaches, and coastal mangroves— that aim to improve area resilience through reducing
and to zone significant new infrastructure away the development gap are particularly effective forms
from vulnerable areas to the greatest extent possi- of investment, including programming in education,
ble. Emphasis must be placed on soft options such social protection and health, roads, market services,
as enhancing capacity in early warning systems natural resource management, and skills training.
and the use of GIS and satellite imagery for coastal
zone management. New oil and gas development Regional integration
and related infrastructure and regional develop- It is important for Ghana to strengthen dialogue
ment in the Western region would need to be with neighboring countries to effectively deal with
designed with climate change adaptation in mind. the challenges of climate change. Areas where
negotiations and consultations would be required
Social dimensions are in the management of shared water resources
Complementary investments in both hard and soft and regional migration of people.
adaptation options are needed to ensure effective
use of infrastructure and to meet the needs of the Long-term planning
poorest. Adaptation investments in hard infrastruc- Given the development challenges and threats posed
ture without complementary investments in policy, by climate change and variability, Ghana needs a
service, and extension support will not operate in an long-term national plan that takes these factors into
optimally efficient manner. account. Currently, Ghana only has a medium-term
development plan covering 2010–13. The long-term
A policy shift is needed—from support for coping plan also needs to be integrated into the plans of the
strategies for climate shocks at the household regional coordinating councils and the district devel-
level, to transformative adaptation strategies that opment plans to provide a coherent and integrated
can increase resilience at the household and area approach to development planning.

G h a n a CO U N T RY ST U DY 1

Introduction

Climate change and variability is arguably one of example, regional climate systems such as the El
the greatest challenges facing humankind this cen- Niño-Southern Oscillation phenomenon and the
tury and into the next. Developing countries, in par- Asian monsoon will be altered.
ticular those in Sub-Saharan Africa (SSA), are
particularly at risk because they are located in areas Even if GHGs are stabilized at 450ppm, the
where temperatures will rise the fastest. They are annual mean global temperature will be about
also more vulnerable because they are mainly 2°C above preindustrial levels by the middle of
dependent on agriculture, which is the most climate this century due to the amount of gases already
sensitive sector. Despite some uncertainty about the locked into the climate system. Therefore, the
precision of climate science, there is now general short-run option for both developed and develop-
agreement among climate scientists on a number of ing countries is to adapt. However, without any
issues. Firstly, it has been firmly established that the mitigation, an adaptation-based strategy for deal-
Earth is undergoing rapid changes due to significant ing with climate change is bound to be too costly.1
increases in greenhouse gases (GHGs). For example, This is because a temperature increase far in
global GHG emissions have roughly doubled since excess of 2°C (e.g., 4°C) is predicted to be associ-
the early 1970s; if current policies continue, emis- ated with potentially catastrophic impacts whose
sions could rise by over 70 percent during 2008–50. effects may be irreversible. Examples of such
Atmospheric concentrations of carbon dioxide impacts include extinction of half of all species
(CO2) have increased by nearly 100 parts per million worldwide, inundation of 30 percent of coastal
(ppm) compared to preindustrial levels, reaching wetlands, and increases in disease and malnutri-
379 ppm in 2005, and the Earth has warmed 0.7°C tion. Although autonomous (or private) adapta-
since 1900 (IPCC 2007; Brohan et al. 2006). Sec- tion is already occurring in various parts of the
ondly, human activities, particularly burning of fos- world, including SSA, the general view is that this
sil fuels and deforestation, have been identified as approach will be incapable of dealing with warm-
prime causes of the changes observed in the 20th ing in excess of 2°C. In such situations, planned
century and are likely to contribute to further adaptation would be required.
changes in the 21st century (IPCC 2001). Thirdly,
these atmospheric changes are highly likely to alter 1 While adaptation and mitigation are necessary responses to
temperatures, rainfall patterns, sea level, extreme climate change, they need not be mutually exclusive. In fact it has
been shown that there can be cobenefits and synergies between
weather events, and other aspects of climate. For the two responses.

2 E C O N O M I C S O F A D A P T AT I O N T O C L I M A T E C HAN G E

At the 2007 Bali Conference, the developed coun- lacking for many developing countries. To close
tries pledged among other things to provide “ade- this information gap, the World Bank initiated the
quate, predictable, and sustainable financial Economics of Adaptation to Climate Change
resources and the provision of new and additional (EACC) study in early 2008, supported by funds
resources, including official and concessional fund- from the governments of the Netherlands, Switzer-
ing for developing country parties” to assist them in land, and the United Kingdom. The objectives of
adapting to climate change (UNFCCC 2008). In the EACC are to develop an estimate of adapta-
order to determine the order and magnitude of the tion costs for developing countries and to help
financial assistance required, it is necessary to know decision makers in developing countries under-
how much adaptation would cost. Unfortunately, stand and assess the risks posed by climate change
current information on adaptation costs, particu- and design better strategies to adapt to climate
larly for developing countries, is not sufficiently change (World Bank 2010a). At the 2007 Bali
comprehensive. For example, the World Bank pro- meetings, the Ghana delegation made a request to
duced one of the first estimates of adaptation costs the World Bank for assistance to estimate the cost
for developing countries in 2006, with estimates of climate change adaptation for planning and
ranging from $9–$45 billion a year (World Bank budgetary purposes. Ghana was therefore included
2006). However, these estimates were restricted to among six other countries in which country-based
the cost of climate-proofing only three categories of EACC studies would be undertaken. The other
investments: official development assistance (ODA) participating countries are Bangladesh, Bolivia,
and concessional finance, foreign direct investment, Ethiopia, Mozambique, Samoa, and Vietnam.
and gross domestic investment. The Stern Report
(Stern 2007) estimated that adaptation costs would This report presents a synthesis of the findings
range from $4–$37 billion per year by 2050, using from the Ghana EACC case study. The study
the World Bank (2006) approach, while the UNDP’s benefited from close collaboration and input from
estimates were $5–$67 billion a year by 2015. Oxfam various stakeholders, including government agen-
International (2007), using national adaptation cies (Ministry of Environment, Science and Tech-
action plans (NAPAs), estimated global adaptation nology; Environmental Protection Agency;
to be at least $50 billion per year, while UNFCCC Ministry of Finance and Economic Planning; and
(2007) estimated adaptation costs for five major sec- Ministry of Energy), civil society organizations,
tors to range from $26–$67 billion per year by 2030. and development partners. As part of the Ghana
One of the latest estimates is by the Climate Works EACC study process, a series of participatory sce-
Foundation; under their Project Catalyst Initiative, nario development (PSD) workshops highlighted
the costs of adaptation for developing countries are the impact of climate change on vulnerable
estimated to lie between $15 and $30 billion for groups and also identified and vetted adaptation
2010–20 and $30–$90 billion by 2030 (European strategies for further analyses.
Climate Foundation 2009). A recent review of cur-
rent climate change adaptation estimates (Parry et
al. 2009) argues that the existing estimates are likely Study Objectives
to be gross underestimates due to the exclusion of
some sectors or the incomplete accounting of cli- The main objectives of this study are to present
matic effects. estimates of the impacts of climate change for key
selected sectors for Ghana and to discuss the
Whereas considerable work has been done in a implications for climate change adaptation
large number of advanced countries on the cost of options and adaptation costs. This type of infor-
climate change adaptation, such information is mation can assist policy makers in a number of


areas. First, it would assist them to make appro- discussing the global EACC study and the
priate budgetary allocations for climate change EACC methodology, which was applied in this
adaptation and to inform the debate on the level study at a more disaggregated level. The sec-
of assistance required for the development effort. tion highlights the differential impacts of cli-
Secondly, given that scarce resources must be mate change among different regions of the
allocated amongst competing needs, the informa- world, including Africa. Chapter 3 presents an
tion would enable them to make tough choices on overview of the methodology used, including
the design and sectoral balance of the national the key assumptions. An effort has been made
development strategy in light of the challenges to present this information in nontechnical lan-
posed by climate change. The beneficiaries of this guage where possible. The more technical
report will include not only the government, but aspects of the study can be found in the annexes.
also the development partners, nongovernmental The sector results are contained in chapter 4.
organizations, researchers, students, and citizens The chapter begins with an overview of the
concerned about the impacts of climate change. Ghanaian economy, followed by the climate
projections for Ghana and the overall economic
impacts. Next, the results for each sector are
Organization of the Report presented in three parts: climate change
impacts, the adaptation options, and the adap-
The report is organized as follows. The next tation costs. The final chapter concludes with a
section puts the study into context by briefly summary and policy implications.


Overview of the EACC
Global Track Study

The approach adopted in the global track study availability. Construction of the baselines also
was to use country-level data sets to estimate involved the use of a consistent set of GDP and
adaptation costs for all developing countries for population forecasts for 2010–50.2 Two climate
seven key sectors of the economy — infrastruc- models were chosen to capture as large a range as
ture, coastal zones, water supply and flood pro- possible of model predictions, including model
tection, agriculture, fisheries and ecosystem extremes of dry and wet climate projections.
services, human health, and forestry. In line with These were the National Center for Atmospheric
the Bali Action Plan’s call for “new and addi- Research (NCAR) CCSM3 and Commonwealth
tional” resources to meet adaptation costs, the Scientific and Industrial Research Organization
study considered adaptation costs as additional (CSIRO) Mk3.0 models. There is not much dif-
to the costs of development. Therefore, the costs ference in the model projections for warming by
of measures that would have been undertaken 2050, with both models projecting increases of
even in the absence of climate change were not about 2°C above pre-industrial levels. However,
included. Adaptation cost was thus defined as the projections do vary substantially for precipita-
the cost of appropriate capacity to deal with tion changes. Based on the climate moisture index
future climate change minus the cost of appro- (CMI), the NCAR model predicts the wettest sce-
priate capacity to deal with current climate vari- nario globally (but not necessarily the wettest and
ation. The latter therefore includes the driest in every location), whereas the CSIRO
“adaptation deficit,” which is defined here as the model predicts the driest scenario.
lack of sufficient capacity to deal with current
climate variation. The next step in the process was to predict what
the world would look like with climate change. The
The process of estimating the cost of adaptation 2050 time frame was chosen because of the many
began with the establishment of a development uncertainties associated with forecasting climate
baseline for each sector. This is the growth path change beyond this period. This was done by esti-
that would be followed in the absence of climate mating the impacts on agriculture, forestry, fisher-
change to the year 2050 and which determines ies, consumption, human health, water availability,
sector-level performance indicators—for exam-
ple, productivity growth in agriculture, level of 2 The year 2050 was chosen due to the increasing error associated
infrastructure assets, level of nutrition, and water with trying to make forecasts beyond this time period.


and physical infrastructure. Adaptation cost was In general, the adaptation costs are dominated by
then calculated as the cost of climate-proofing the costs of infrastructure, coastal zones, and
these resources to enable them to withstand the water supply and flood protection in both scenar-
impacts, as well as the cost of assisting people to ios. In terms of the sectoral breakdown, the high-
deal with the impacts. Due to the complexity of est costs for East Asia and the Pacific are in
modeling different sectors at a global level, a zero infrastructure and coastal zones; for Sub-Saharan
discount rate was assumed with costs expressed in Africa, water supply and flood protection and
2005 constant prices.3 A World Bank study— The agriculture; for Latin America and the Carib-
Costs to Developing Countries of Adapting to Climate bean, water supply and flood protection and
Change: New Methods and Estimates—offers a detailed coastal zones; and for South Asia, infrastructure
discussion on the logic behind the zero discount and agriculture.
rate at the global level (World Bank 2010a).
Table 2 indicates that under both climate scenar-
The study used three different methods to aggre- ios, total annual adaptation costs rise over time.
gate adaptation costs and benefits across sectors For example, for the NCAR model, annual adap-
and countries. These were gross (no netting of tation costs are $73 billion during 2010–19, rising
costs), net (benefits are netted across sectors and 45 percent over the next 30 years to reach $106
countries), and X-sums (positive and negative items billion in 2040–49. Similarly, for the CSIRO
are netted within countries but not across coun- model, costs also increase but more rapidly, rising
tries). The study estimates that the global cost 67 percent over the entire period, from $57 bil-
between 2010 and 2050 of adapting to an approxi- lion a year in 2010–19 to $95 billion by
mately 2°C warmer world by 2050 lies between 2040–49.
$75 billion and $100 billion a year (Table 1).

Figure 1 Shares of the Total Annual
Figure 1 presents a chart of the share of the total
Costs of Adaptation by Region, 2010–50
costs by region using the CSIRO model and the
X-sum cost aggregation method. The East Asia
$7
and Pacific Region has the highest share of the
$4
adaptation cost with 25 percent, followed by 7%
4% $25
Sub-Saharan Africa and Latin America and the 25%
Caribbean with 22 percent each, and then by
South Asia with 20 percent. Europe and Central $22
22%
Asia and the Middle East and North Africa have
the lowest shares of 8 percent and 4 percent,
respectively. Although the NCAR model esti- 22%
mates tend to be generally higher than the $22
20%
CSIRO estimates, the rankings of the shares are
$20
similar in both models.

Middle East Sub-Saharan Africa
3 Discounting the time stream of investment costs would lower and North Africa
the net present value of total investment or adaptation costs, but Europe and Latin America
would not influence the choice of investments or the underlying Central Asia and Caribbean
investment costs. South Asia East Asia and Pacific
5 World Bank. 2010. The Costs to Developing Countries of Adapt-
ing to Climate Change. http://beta.worldbank.org/content/
economics-adaptation-climate-change-study-homepage.
Source: (World Bank 2009)


Table 1 Total Annual Costs of Adaptation for All Sectors by Region,
2010–50 ($ billions at 2005 prices, no discounting)

Cost Middle East
aggregation East Asia Europe and Latin America and North Sub-Saharan
type and Pacific Central Asia and Caribbean Africa South Asia Africa Total
National Centre for Atmospheric Research (NCAR), wettest scenario
Gross sum 28.7 10.5 22.5 4.1 17.1 18.9 101.8
X-sum 25.0 9.4 21.5 3.0 12.6 18.1 89.6
Net sum 25.0 9.3 21.5 3.0 12.6 18.1 89.5
Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario
Gross sum 21.8 6.5 18.8 3.7 19.4 18.1 88.3
X-sum 19.6 5.6 16.9 3.0 15.6 16.9 77.6
Net sum 19.5 5.2 16.8 2.9 15.5 16.9 76.8
Source: (World Bank 2010a)

Table 2 Total Annual Costs of Adaptation for all Sectors by Region and
Period, 2010–50 (X-sums, $ billions at 2005 prices, no discounting)
Middle East
East Asia Europe and Latin America and North Sub-Saharan
Period and Pacific Central Asia and Caribbean Africa South Asia Africa Total
National Centre for Atmospheric Research (NCAR), wettest scenario
2010–19 22.7 6.5 18.9 1.9 10.1 12.8 72.9
2020–29 26.7 7.8 22.7 2.0 12.7 17.2 89.1
2030–39 23.3 10.8 20.7 3.0 13.5 19.2 90.5
2040–49 27.3 12.7 23.7 5.0 14.3 23.2 106.2
Commonwealth Scientific and Industrial Research Organization (CSIRO), driest scenario
2010–19 16.4 3.9 11.6 2.4 11.9 10.3 56.5
2020–29 20.1 4.7 13.1 2.6 17.5 13.3 71.3
2030–39 20.9 6.4 20.2 3.0 17.7 20.0 88.2
2040–49 21.0 7.6 22.8 3.9 15.3 24.1 94.7
Source: (World Bank 2010a).


Table 3 A Comparison of Adaptation Cost Estimates ($ billions)

World Bank Economics of Adaptation
to Climate Change (EACC) Study

UNFCCC Parry et al. NCAR CSIRO
Sector (2007) (2009) (wettest Scenario) (driest scenario)
Infrastructure 2–41 18–104 29.5 13.5
Coastal zones 5 15 30.1 29.6
Water supply and flood 9 9 13.7 19.2
protection
Agriculture, forestry, 7 7 7.6 7.3
fisheries
Human health 5 5 2 1.6
Extreme weather events — — 6.7 6.5
Total 28–67 — 89.6 77.7
Source: (World Bank 2010a).

Such a trend is to be expected as, under a busi- effects and refinements in the cost estimations,
ness-as-usual (BAU) scenario, rising emissions adaptation costs tend to lie in the upper ranges of
result in more than proportional environmental the UNFCCC estimates. In the area of coastal
impacts. Another important finding (not shown zone management and defense, the EACC esti-
here) is that adaptation costs decline as a percent- mates actually represent a six-fold increase com-
age of GDP over time. This suggests that coun- pared to the UNFCCC estimates.4
tries become less vulnerable to climate change as
their economies grow if the countries considered The only area where the EACC estimates are
adaptations to climate changes in their strategic lower is in human health; the UNFCCC study
planning processes. Development enhances projects a cost of $5 billion per annum, whereas
households’ capacity to adapt by increasing levels the EACC projects $2 billion (NCAR model) and
of incomes, health, and education. $1.6 billion (CSIRO model). This difference is
partly explained by the inclusion of the develop-
The study results indicate that there are consid- ment baseline in the EACC study, which reduces
erable regional variations in the share of adapta- the number of additional cases of malaria, and
tion costs as a percentage of GDP. The share is thereby adaptation costs, by some 50 percent by
highest in Sub-Saharan Africa, in large part 2030. With the exception of coastal zones, the
because GDP is lower in the region. Percentages Parry et al. (2009) adaptation costs are much
remain stable in Europe and Central Asia and higher than the EACC study. Their estimate for
the Middle East and North Africa, and fall infrastructure, for example, ranges from $18 to
sharply in all other regions. $104 billion per annum. They come up with
higher estimates because they argue that low- and
Table 3 compares adaptation costs derived from
the EACC study with those of UNFCCC (2007) 4 This difference reflects the effects of the following refinements:
and Parry et al. (2009). Given that the EACC better unit cost estimates, including maintenance costs, and the
inclusion of the costs of port upgrading and risks from both sea-
study uses a more comprehensive coverage of level rise and storm surges.


middle-income countries have a large infrastruc- ability of governments to provide assistance.
ture deficit and that the costs of climate-proofing Also, by its very nature, economic development
this additional infrastructure must be included in tends to shift resources away from agriculture,
the adaptation cost. which is the most climate-sensitive sector, into
less climate-sensitive areas such as services and
For Sub-Saharan Africa, as well as other devel- manufacturing.
oping regions such as South Asia and East Asia
and the Pacific, the study results highlight a The global track study provides policy makers
number of salient issues. First, for these regions with an indication of global adaptation costs.
as a whole, the results indicate that adaptation to However, modeling of the climate scenarios and
climate change will be costly to implement and the climate change impacts are at a relatively high
would subject national budgets to further strain. degree of aggregation. It is highly likely that when
Secondly, given that the effects of climate change the models are downscaled to the country/local
are already being felt in these regions, failure to level, the nature and pattern of the effects might
take immediate action would even be costlier in be entirely different from those obtained at the
the future as the effects are bound to escalate regional level. For that reason, country-level stud-
over time. Thirdly, economic development plays ies such as the Ghana EACC study are necessary
a key role in enhancing adaptive capacity. By to complement the global track study.
increasing levels of incomes, health, and educa-
tion, economic development enhances the
capacity of households to adapt; and by improv- Overall Approach and Key
ing institutional infrastructure, it enhances the Assumptions


Methodology

The overall approach adopted in the study follows it is assumed that policy makers know what the
closely on the method used in the global track future climate will be and act to prevent its damages.
study. Using a 2050 time frame, development base- Second, only four climate models (described below)
lines are first developed for each sector. The base- are used in the Ghana case study; it is implicitly
line represents the growth path the economy would assumed that they cover the breadth of climate
follow in the absence of climate change. It is a rea- change impacts. Third, in costing the adaptation
sonable trajectory for growth and structural change options, the study focuses on “hard options”—such
of the Ghanaian economy over a period of 40 as building dams and dikes—and ignores “soft”
years that can be used as a basis of comparison options such as early warning systems, community
with the climate change scenario. The baselines for preparedness programs, watershed management,
each sector utilize a common set of GDP and pop- and urban and rural zoning. This approach was
ulation forecasts for 2010–50. From the baselines, deliberately chosen because the former options are
sector-level performance indicators—such as the easier to value and cost; it does not mean that the
stock of infrastructure assets, level of nutrition, and latter are less important. Fourth, the adaptation costs
water supply availability—are determined. Next, are based on current knowledge. This implicitly
GCM projections of climate change are used to assumes that there will be no innovation and techni-
predict changes in various variables, including cal change in the future. However, we know that
agricultural output, consumption, water availabil- economic growth and hence development depends
ity, and infrastructure such as roads and ports. The on technical change, which is likely to reduce the
final steps involve identifying and costing adapta- real costs of adaptation over time. The only case
tion options for the key economic sectors — agri- where technical change is considered is in the agri-
culture, road transport, water and energy, and the cultural sector, where growth in total factor produc-
coastal zone. For all sectors, the adaptation costs tivity is built into the model, and explicit investment
include the costs of planned, public policy adapta- in research is included in the costs. (We consider the
tion measures and exclude the costs of private possible effects of these assumptions in the discus-
(autonomous) adaptation. sion of the study’s limitations below.)
Given the complexity of climate change and the
number of variables and actors involved in the Climate Forecasts
impacts, a number of simplifying assumptions have
been made in order to facilitate the modeling. First,


Historic and future climate inputs specific to Ghana climate moisture index.
and its river basins—such as monthly temperature
and precipitation—were used to drive the river In line with the global track, the climate projec-
basin and water resource model and crop models tions from these two GCMs are used to generate
outlined below. Historic inputs were obtained using the “Global Wet” and “Global Dry” scenarios for
the University of East Anglia’s Climate Research the Ghana country-track study. In addition, the
Unit’s global monthly precipitation and tempera- climate projections from the two GCM/SRES
ture data. Future inputs were taken from four combinations with the lowest and highest climate
GCMs forced with different CO2 emission scenar- moisture index for Ghana are used to generate a
ios to represent the total possible variability in pre- “Ghana Dry” and a “Ghana Wet” scenario. In
cipitation. In line with the approach taken in the the case of Ghana, the globally “wettest” GCM
global track study, climate projections from the actually projects a drier future climate for Ghana
NCAR and CSIRO models were used to generate than the globally “driest” GCM under emission
the “Global Wet” and “Global Dry” scenarios for scenario A2.
the Ghana case study.
Four climate change scenarios are selected to rep-
In the EACC global track study, the National resent the largest possible ranges of changes in
Center for Atmospheric Research (NCAR) temperature, precipitation, and water runoffs.
CCSM3 and Commonwealth Scientific and The climate moisture index (CMI) is used as a cri-
Industrial Research Organization (CSIRO) terion to select the Ghana climate change scenar-
Mk3.0 models with SRES A2 emission forces ios. The index is a measure of the water balance
were used to model climate change for the analy- of an area in terms of changes in precipitation (P)
sis of most sectors because they capture a full and losses of potential evapotranspiration (PET).
spread of model predictions to represent inherent The moisture index (CMI) is calculated as CMI =
uncertainty. In addition, they report specific cli- 100(P - PET)PET. The MI range in the various
mate variables—minimum and maximum tem- GCM scenarios is 115 percent—from -66 percent
perature changes—needed for sector analyses. in the Ghana dry scenario to 49 percent in the
Though the model predictions do not diverge Ghana wet scenario (Table 4).
much for projected temperature increases by 2050
(both projecting increases of approximately 2oC Precipitation and temperature data obtained from
above preindustrial levels), they vary substantially these simulations were used to estimate the avail-
for precipitation changes. Among the models ability of water at a subbasin scale. Historical cli-
reporting minimum and maximum temperature mate data for each basin were gathered using
changes, the NCAR was the wettest and the available precipitation and temperature data
CSIRO the driest scenario globally, based on the when available, along with the Climate Research

Table 4 GCM Scenarios for Ghana Country Track Study

Scenario GCM SRES CMI Deviation (%)
Global Wet ncar_ccsm3_0 A2 -17

Global Dry csiro_mk3_0 A2 9

Ghana Wet ncar_pcm1 A1b 49

Ghana Dry ipsl_cm4 B1 -66

Source: Strzepek and Mccluskey (2010)


Unit’s 0.5° by 0.5° global historical precipitation modified Hargreaves method was used. Actual
and temperature database. evapotranspiration is a function of potential
evapotranspiration and soil moisture state (follow-
CLIRUN-II is used in this study to forecast runoffs ing the FAO method). Soil water is modeled as a
in Ghana. CLIRUN-II is the latest model in a two-layer system: a soil layer and a groundwater
family of hydrologic models developed specifically layer. These two components correspond to a
for the analysis of the impact of climate change quick and slow runoff response to effective
on runoff. Kaczmarek (1993) presents the theo- precipitation.
retical development for a single-layer lumped
watershed rainfall runoff model-CLIRUN. Kacz- The soil layer generates runoff in two ways. First
marek (1996) presents the application of CLIRUN there is a direct runoff component, which is the
to Warta River catchment, Poland. Another cor- portion of the effective precipitation (precipita-
nerstone publication on the family of hydrologic tion plus snowmelt) that directly enters the stream
models and water balance components is pre- systems. The remaining effective precipitation is
sented in Cohen et al. (1999). CLIRUN-II (Strze- infiltration to the soil layer. The direct runoff is a
pek et al. 2008) is the latest in the “Kaczmarek function of the soil surface and modeled differ-
School” of hydrologic models applied to the anal- ently for frozen soil and non-frozen soil. The infil-
ysis of water flow and economic impacts of the tration then enters the soil layer. A nonlinear set
High Dam in Egypt. It incorporates most of the of equations determines how much water leaves
features of the water balance module WATBAL the soil as runoff, how much is percolated to the
and CLIRUN, but was developed specifically to groundwater, and how much goes into soil stor-
address extreme events at the annual level, model- age. The runoff is a linear relation of soil water
ing low and high flows. CLIRUN and WATBAL storage and percolation is a nonlinear relation-
did very well in modeling mean monthly and ship of both soil and groundwater storages. The
annual runoff, important for water supply studies, groundwater receives percolation from the soil
but was not able to accurately model the tails of layer, and runoff is generated as a linear function
runoff distribution. CLIRUN-II has adopted a of groundwater storage.
two-layer approach following the framework of
the SIXPAR hydrologic model (Gupta and Soil water processes have six parameters simi-
Sorooshian 1985) and a unique conditional lar to the SIXPAR model (Gupta and Sorooshian
parameter estimation procedure was used. In the 1983) that are determined via the calibration
following section a brief description of the com- of each watershed. When CLIRUN-II is cali-
ponents of the model will be presented. brated in a classical rainfall-runoff framework,
the results are very good for the 25th to 75th
CLIRUN-II models runoff as a lumped water- percentile of the observed streamflows, produc-
shed with climate inputs and soil characteristics ing an R2 value of 0.3 to 0.7 However, for most
averaged over the watershed, simulating runoff at water resource systems, the tails of the stream-
a gauged location at the mouth of the catchment. flow distribution are important for design and
CLIRUN can run on a daily or monthly time operation planning. To address these issues, a
step. In the CLIRUN-II system, water enters via concept know as localized polynomial—devel-
precipitation and leaves via evapotranspiration oped by Block and Rajagopalan (2008) for
and runoff. The difference between inflow hydrologic modeling of the Nile River—was
and outflow is reflected as change in storage extended to calibration of rainfall runoff mod-
in the soil or groundwater. A suite of potential eling in CLIRUN-II (Strzepek et al. 2008).
evapotranspiration models are available for use in When calibrating, each observed year is catego-
CLIRUN-II. For this study, the rized as to whether it falls into a dry year (0–25


Figure 2 Flow Chart of Model Sequencing

Location
GCM
GENERAL CIRCULATION
MODEL

TEMPERATURE
PRECIPITATION
Surface Slope

CliRun
CLIMATE RUNOFF
TEMPERATURE
PRECIPITATION

TEMPERATURE

RAINFALL RUNOFF
Soil Composition
Reserve Specifications Crop Type
Discount Rate

IMPEND
INVESTMENT MODEL FOR
CliCrop
PLANNING ETHIOPIAN CLIMATE CROP
AND NILE DEVELOPMENT

WATER RESOURCE ALLOCATIONS IRRIGATION DEMAND
CROP YIELD
Reservoir Specifications
River Basin Management
Municipal and Industrial Demand
WEAP
WATER EVALUATION
AND PLANNING

RESOURCE ACCOUNTING

Discount Rate

CGE
COMPUTABLE GENERAL
EQUILIBRIUM

percent of the distribution), a normal year (25– data when available, along with the Climate
75 percent), or a wet year (greater than 75 per- Research Unit’s 0.5° by 0.5° global historical
cent). Separate model parameters were estimated precipitation and temperature database. CLI-
for the three different classes of annual stream- RUN-II is a two-layer, one-dimensional infiltra-
flow. The Climate Research Unit (CRU) and tion and runoff estimation tool that uses historic
Global Runoff Data Center (GRDC) are the surfaces. A 0.5° by 0.5° historic global surface
two major data sources for the CLIRUN-I. Pre- flow database generated by the Global Runoff
cipitation and temperature data obtained for the Data Center (GRDC) is used for modeling the
CLIRUN-II simulations were used to estimate surface flow, as explained above.
the availability of water at a subbasin scale. His-
torical climate data for each basin were gathered
using available precipitation and temperature


Sector-Specific Approaches shocks simultaneously on all sectors of the economy.
Third, CGE models are able to take into consider-
ation secondary or feedback effects caused by a
The modeling of the impacts of climate change given shock, and are therefore suitable for analyzing
in the selected sectors was carried out using a climate-related issues.5
suite of models (CLIRUN, CLICROP, IMPEND,
WEAP, DIVA) that are briefly described below. Assumptions about the behavior of economic
Figure 2 depicts the modeling process, starting agents in the CGE model are grounded in eco-
with the climate forecasts. Climate data from the nomic theory and the magnitudes of some model
GCMs are entered into CLIRUN and CLICROP parameters are determined by resort to second-
in order to produce streamflow runoff estimates ary econometric studies. Producers maximize
and crop irrigation demand estimates, respec- profits (and thus minimize costs) under constant
tively. Inflows calculated using CLIRUN are then returns to scale and consumers maximize utility
fed into IMPEND, where storage capacity and subject to their budget constraints. It was
irrigation flows are optimized to maximize net assumed that the economy is perfectly competi-
benefits. The outputs from IMPEND along with tive and that markets clear. The CGE model was
the irrigation demands estimated from CLICROP calibrated to a regional 2005 social accounting
are then entered into the Water Evaluation and matrix (SAM) of Ghana jointly constructed by
Planning System (WEAP), where water storage the International Food Policy Research Institute
and hydropower potential are modeled based on and the Ghana Statistical Service (GSS) using
their interaction with the climate and socioeco- national accounts, trade and tax data, and
nomics of the river basins. household income and expenditure survey data.
Further details on the features of the Ghana
Finally, this information is fed into a dynamic com- CGE model are provided in Annex 6.
putable general equilibrium (CGE) model where
the economic implications of the modeled data are The CGE modeling approach captures three
assessed. Within the river basin model there is, main mechanisms by which climate change is
however, one interaction with the potential for expected to influence Ghana’s economic growth
nonlinearity. The interaction between IMPEND and development. First, it estimates the economy-
and WEAP is an iterative process depending on wide impacts of productivity changes in dry-land
the scenario. Reservoir flow calculated in WEAP agriculture, using the CLICROP inputs. Second,
may change previous inputs into IMPEND, thus it incorporates the fluctuations in hydropower
requiring the net benefits to be re-calculated and production due to variation in river flow. River
their implications re-modeled in WEAP. flow will only affect agricultural production if the
irrigated area available for planting is greater
The CGE modeling approach was chosen to model than the maximum potential area that could be
the impacts of climate change because it has a num- irrigated given water availability constraints.
ber of features that make it attractive for analyzing Third, it will account for changes in temperature
such issues. First, these models portray the function- and precipitation, which in turn influence main-
ing of a market economy, including markets for tenance requirements for infrastructure, particu-
labor, capital, and commodities, and account for the larly roads. Rainfall or temperature realizations
role of relative prices and market mechanisms in the
decisions of economic agents. Second, CGE models 5 An alternative approach is to use partial equilibrium (i.e.
belong to the class of general equilibrium models econometric) models, which are limited in the sense that they
can consider the impact of only one variable at a time in a single
that are able to determine the impacts of exogenous sector.


outside of the band of design tolerances are likely (2) cocoa, (3) forestry and logging, and (4) fish-
to require more frequent or more expensive main- ing. Agriculture contributes to 40 percent of real
tenance costs. In the CGE model, these greater GDP, with the cocoa sector accounting for 32 per-
maintenance requirements result in either less cent of exports. Overall, over 50 percent of the
rapid expansion in the road network for a given population derives their livelihood from agricul-
level of spending on roads, or an actual shrinkage ture. Growth in the sector has been variable in the
in the network if the resources necessary to main- past few years. Starting from a low of 4.4 percent
tain the network are unavailable. in 2002, the sector’s growth rate rose to a high
of 7 percent in 2004 before declining to another
We now turn to the specific approaches used to low of 3.1 percent in 2007 (Figure 3). The growth
measure the impacts of climate change in the decline in 2007 was due to drought, particularly
selected sectors—agriculture, road transport, in the forest zone where cocoa is cultivated. The
water and energy, and coastal zone. For each 2009 budget projected growth of 5.3 percent in
sector, we briefly describe the sector’s contribu- 2009 and 5.9 percent in 2010.
tion to the economy, its vulnerability to climate
change, the baseline (BAU) scenario, and the Vulnerability to Climate Change. Across Ghana’s
methodology used. agroecological zones, there are some significant
differences in the regional distribution of agri-
Agriculture cultural GDP. The forest zone accounts for 43
Contribution to the Economy. The Ghanaian economy, percent of agricultural GDP, compared to about
like that of most developing countries, is based on 10 percent in the coastal zone, and 26.5 and 20.5
agriculture. The agricultural sector is composed percent in the southern and northern savannah
of four subsectors: (1) food crops and livestock, zones, respectively. The northern savannah zone

Figure 3 Trends in Agricultural Growth 2002 to 2010

35.0

30.0

25.0

20.0
GROWTH RATE (% P.A.)

15.0

10.0

5.0

0.0
2002

2003

2004

2005

2006

2007

2008

2009

2010

-5.0

-10.0

AGRICULTURE CROPS AND LIVESTOCK COCOA FORESTRY AND LOGGING

Source: (World Bank 2009)


is the main producer of cereals, accounting for The plan has been developed using a largely par-
more than 70 percent of the country’s sorghum, ticipatory process and based on food and agricul-
millet, cowpeas, groundnuts, beef and soybeans. ture development policy II (FASDEP II) objectives,
On the other hand, the forest zone supplies a large with a target for agricultural GDP growth of at
share of higher-value products such as cocoa and least 6 percent annually and government expen-
livestock (mainly commercial poultry) (Breisinger diture allocation of at least 10 percent within the
et al. 2008). Ghana’s agricultural sector is highly plan period. These targets are in conformity with
vulnerable to climate change and variability agricultural performance targets of the country’s
because it is predominantly rainfed and is charac- National Development Planning Commission
terized by low levels of productivity. (NDPC) and other relevant government develop-
ment policies. Ghana’s agriculture and irrigation
Baseline. The current development strategy for policies are expected to contribute significantly to
agriculture is to ensure sustainable utilization the achievement of the MDGs.
of resources and commercialization of activities
with market-driven growth. Commodity target- Irrigation in Ghana contributes only about 0.5
ing for food security and income diversification percent of the country’s agricultural production.
of resource-poor farmers is given a high priority. About 11,000 hectares (out of a potential irrigable
The strategy seeks to enhance the commodity area of 500,000 hectares) have been developed for
value chain using science and technology. There irrigation, and even the developed area is largely
is also an emphasis on environmental sustain- underutilized due to institutional, management,
ability and greater engagement with the private input, and other constraints. The investment plan
sector and other partners (GoG/NDPC 2009). concluded that: “It is necessary that the Govern-
As stated in the Ghana Poverty Reduction Strat- ment regards irrigated agricultural infrastructure
egy (GPRS, GoG 2003), Ghana’s agricultural as a public good, which can be leased to water
development strategy is to ensure a modernized users’ associations and/or private management
agriculture culminating in a structurally trans- bodies to ensure efficiency through better manage-
formed economy that will provide food security, ment practices.” METASIP estimated an irriga-
employment opportunities, and reduced poverty tion funding gap of $423 million in 2009, rising to
in line with the goal set for the sector in GPRS about $1.6 billion in 2015 (GoG 2009). METASIP
I. The strategy emphasizes the sustainable utili- noted that climate change— which has had a sig-
zation of all resources and commercialization of nificant adverse impact on the nation’s agriculture
activities in the sector based on market-driven over the years—added uncertainties to the agricul-
growth. Climate change impacts and national ture sector. The report also said that even though
plans to deal with these changes are not explicitly irrigated agriculture is well-known to be important,
stated in national and agricultural sector goals, it is yet to be significant in Ghana.
although there is provision for irrigation develop-
ment in various parts of the country. The policy Methodology. As indicated earlier, the impact of
document emphasizes that small- and large-scale climate change on the agricultural sector was
irrigation systems and efficient water harvesting estimated using CLICROP. CLICROP is a
and management systems are required to reduce generic crop model used to calculate the effect
reliance on rainfed agriculture (GoG 2003--). of changing daily precipitation patterns caused
by increased CO2 on crop yields and irrigation
Recently the government of Ghana issued vol- water demand. It was developed in response to
ume 1 of the Medium Term Agriculture Sector Invest- the available crop models that use monthly aver-
ment Plan (METASIP) 2009–2015 (GoG 2009). age rainfall and temperature to produce crop


outputs. These monthly models do not capture and the fraction already under irrigation; irriga-
the effects of changes in precipitation patterns, tion investment and maintenance cost per ha of
which greatly impact crop production. For exam- irrigated land; and the current level of provision
ple, most of the IPCC GCMs predict that total of extension services. These pieces of informa-
annual precipitation will decrease in Africa, but tion were then fed as inputs into the CGE model
rain will be more intense and therefore less fre- as shocks/stressors caused by the predicted
quent. Currently, CLICROP is able to produce weather changes from the GCMs. The model
predicted changes in crop yields due to climate then computes the values of the key economic
change for both rainfed and irrigated agriculture, variables based on the response of economic
as well as changes in irrigation demand. agents to these climate-related shocks. A detailed
description of the CLICROP methodology is
Five yield estimates (one for each of the four presented in Annex 1.
development stages, and one for the whole sea-
son) were computed using Equation 1. A specific module on the impact of climate
change on livestock productivity was created for
this study. To model the effect of climate on live-
[1 – Y ] = K [1 – ETC ]
Y d d
Equation 1: a
m
y
ETA d stock, this analysis relies on the approach and
results of a structural Ricardian model of Afri-
Where Ya = predicted actual yield
can livestock developed by Seo and Mendelsohn
Ym = maximum yield
(2006). This approach measures the interaction
Ya / Ym = % Yield d
d
between climate and livestock and considers the
Ky = yield coefficient, different for
development stage d to y adaptive responses of farmers by evaluating
ETCd = sum of daily ET crop demand for
which species are selected, the number of ani-
development stage d mals per farm, and the net revenue per animal
ETAd = sum of daily actual ET for under changes in climate. The current analysis
development stage d
transfers the findings from Seo and Mendelsohn
%Yieldd = ratio of actual yield over
maximum yield, value reported by
to the Ghana-specific context. Seo and Mendel-
CLICROP sohn rely on a survey of over 5,000 livestock

farmers in ten African countries. In this data set,
The inputs into CLICROP include weather the variation in livestock productivity and
(temperature and precipitation), soil parameters expected incomes in different regions demon-
(field capacity, wilting point, saturated hydraulic strates a clear relationship to regional climate,
conductivity, and saturation capacity), historic which provides a mechanism—through spatial
yields for each crop by ecological zone, crop dis- analogue—to statistically analyze how climate
tribution by ecological zone, and current irriga- change may affect livestock incomes across
tion distribution estimates by crop. These were Africa. The authors develop a three-equation
used to compute estimates for changes in annual farm-level model. The first equation predicts the
production (yield) for both irrigated and rainfed probability of selecting each livestock type as the
crops as well as irrigation demand (mm/ha) for primary animal for the farm, the second predicts
three industrial crops and four food crops (See the net income of each animal, and the final
Annex 1). The estimated yields reflect the reduc- equation predicts the number of animals on
tions in yield both due to the lack of available each farm. Farm net revenues are the sum prod-
water and due to the overabundance of water uct of these three outputs; that is, the probability
that causes waterlogging. Additional data of selecting each type of animal multiplied by
obtained included total area of irrigable land the number of animals and then the expected


Table 5 Trends in the Growth Rate of the Transport Sector, 2002–07 (%)

Subsector 2002 2003 2004 2005 2006 2007 2002–07
Transport, Storage, and 5.7 5.8 5.6 6.0 7.2 6.0 6.1
Communications
Source: ISSER (2008)

Table 6 Share of the Transport Sector in Total GDP in Purchaser’s Value,
2002–2007 (%)
Subsector 2002 2003 2004 2005 2006 2007 2002–07
Transport, Storage and 6.0 5.4 4.7 5.1 5.1 5.0 5.2
Communications
Source: ISSER (2008)

income per animal, summed across animal types. climate change on road transportation infra-
Details of the livestock modeling approach are structure. The extent of the impacts will, to a
presented in the Annex 1. large degree, be influenced by the environ-
ment in which the infrastructure is located. For
Transport example, increased precipitation levels will affect
Contribution to the Economy. The transport sector— moisture levels in the soil, hydrostatic buildup
covering roads, railways and maritime, is one of behind retaining walls and abutments, and the
the six subsectors under the services sector of the stability of pavement subgrades. Runoff from
Ghanaian economy. Over the past year, the trans- increased precipitation levels will also affect
port sector has received substantial allocations of streamflow and sediment delivery in some loca-
public resources, especially in the road transport tions, with potentially adverse effects on bridge
sector. The objective is for Ghana to become a foundations. And sea level rise will affect coastal
transport hub for West Africa. To achieve this, the land forms, exposing many coastal areas to
government is continuing with the maintenance storm surge as barrier islands and other natural
and completion of ongoing projects as well as ini- barriers disappear.
tiating new development projects. Currently there
are plans to improve the railway sector to divert Projected warming temperatures and more heat
some of the traffic from roads to reduce the high extremes will affect road transport infrastruc-
maintenance costs. The transport subsector’s per- ture. Periods of excessive heat are likely to
formance has declined by 17 percent, from 7.2 per- increase wildfires, threatening communities and
cent in 2006 to 6 percent in 2007 (ISSER 2008) infrastructure directly. Longer periods of
(Table 5). Share of the transport sector in the total extreme heat may compromise pavement integ-
GDP in purchase value was stagnant during the rity and cause thermal expansion of bridge
2002–07 at an average of 5.2% (Table 6) joints, adversely affecting bridge operation and
increasing maintenance costs.
Vulnerability to Climate Change. The primary focus
in this subsection is on the direct impacts of

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