Climate Change Impact and Adaptation Study for the Bangkok Metropolitan

Region

Summary Note

3/4/2010

East Asia and Pacific Region

Sustainable Development Department

World Bank

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Climate Change Impact and Adaptation Study for the Bangkok Metropolitan Region This note is based primarily on a study with the same title that was commissioned by the World Bank and written in 2009 by Panya Consultants Co. Ltd. The note aims to provide an accessible summary of a very complex analysis and to add new and contextual information to the main study.1 Global and Regional Context A recent global screening study for the Organisation for Economic Co-operation and Development (Nicholls et al. 2008) estimated for the first time the exposure of the world’s largest port cities to coastal flooding due to storm surge and damage due to high winds. In addition, it investigated the likely impact of climate change on each port city’s exposure to coastal flooding by the 2070s, coupled with subsidence, population growth, and urbanization of those cities. The analysis focused on the exposure of the population and assets to a 1-in-100-year surge-induced flood event. It demonstrated that about 40 million people are already exposed to coastal flooding during such an event. For 2005, the top 10 cities in terms of exposed population were Mumbai, Guangzhou, Shanghai, Miami, Ho Chi Minh City, Kolkata, Greater New York, Osaka-Kobe, Alexandria, and New Orleans. When assets are considered, the distribution becomes more heavily weighted toward industrial countries. By the 2070s—assuming no additional defensive measures—the total population exposed could grow more than threefold to around 150 million people due to the combined effects of climate change (sea level rise and increased storm intensity), land subsidence, population growth, and urbanization. At that point, the top 10 cities in terms of population exposed are expected to Kolkata, Mumbai, Dhaka, Guangzhou, Ho Chi Minh City, Shanghai, Bangkok, Rangoon, Miami, and Hai Phòng. In terms of assets exposed, the top 10 are projected to be Miami, Guangdong, Greater New York, Kolkata, Shanghai, Mumbai, Tianjin, Tokyo, Hong Kong, and Bangkok. Hence, cities in Asia, particularly those in China, India, and Thailand, become even more dominant in terms of population and asset exposure as a result of the rapid urbanization and economic growth expected there.

Against the backdrop of increasing climate change–related threats to the coastal populations in Asia, the World Bank—in collaboration with the Asian Development Bank (ADB) and the Japan International Cooperation Agency (JICA)—launched a set of studies in 2008. ADB assumed leadership of a Ho Chi Minh study, JICA was the lead on a Manila study, and the World Bank took on studies in Bangkok and Kolkata. A synthesis of all four studies will be published by the World Bank in 2010. This note focuses on the Bangkok study only.

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Study Objectives The objectives of the Bangkok study were to:

Assess the knowledge base, historical climate information, coping strategies, and local capacity to deal with natural disasters

Assess climate change scenarios until 2050 and their social and economic consequences

Identify the areas most vulnerable to the impacts of climate change and variability and to associated flooding

Quantify the likely magnitude of social, environmental, and economic damage expected

Assess the capacity of the city’s government to manage this challenge

Analyze appropriate intervention scenarios. Geographic and Socio-economic Context Bangkok covers an area of almost 1,600 square km in the delta of the Chao Phraya River Basin (see Figure 1). The basin itself covers an area of almost 160,000 square km, or about one-third of the entire country. The basin area is flat, with an average elevation of 1–2 meters above sea level. The climate is characterized by the tropical monsoon. The population, including a large number of non-registered persons, was estimated to be about 15 million in 2008. According to official projections, this will only increase to about 16 million in 2050. This is an expression of the urban planning ambitions, but it is doubtful if this goal can realized, given the attraction of economic opportunities in the Bangkok area. The Bangkok Metropolitan Region (BMR) is the economic center of Thailand, accounting for more than 40 percent of the GDP in 2006. The official poverty estimate for BMR is very low: fewer than 90,000 people. The official poverty line, as given by the National Statistical Office for 2007, was about $45 per month per person.2 However, the Panya study estimates that almost 800,000 people, most of them unregistered, live in condensed housing areas signified by poverty. Therefore the flood impact assessment used this as a base for the assessment of income losses of this group considered as “the poor.”

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Figure 1: The Chao Phraya River Basin

Source: Panya 2009.

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Methodology The key parameters for the analysis were based on models used for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change in 2007. Specifically, the scenarios known as A1FI and B1 were selected.3 These results were interpreted for local conditions by a team at the University of Tokyo and by Panya Consultants. By 2050, the local mean temperature is estimated to rise by 1.2–1.9 degrees Celsius, and the basin mean precipitation may rise by 2–3 percent. The sea level in the Gulf of Thailand is estimated to rise by 19–29 cm by 2050. Land subsidence has been reduced in recent years, thanks to controls of groundwater pumping, but is expected to continue, totaling about 5–30 cm by 2050, varying considerably across locations. The maximum storm surge was estimated to 61 cm. To put these assumptions into perspective, it is instructive to look at the most recent data for carbon dioxide emissions (see Figure 2). This can be compared with the scenarios that were used in the Bangkok study (A1FI and B1). Actual emissions closely follow the higher scenario used. Figure 2. CO2 Emissions

Source: Raupach et al. 2007; Global Carbon Project 2009. The red dots denote the recent International Energy Agency (IEA) carbon dioxide projections (IEA 2009).

IEA

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Note: CDIAC is the Carbon Dioxide Analysis Center, the primary climate change data center of the U.S.

Department of Energy. The Global Carbon Project is a shared partnership between the International

Geosphere-Biosphere Programme (IGBP), the International Human Dimensions Programme on Global

Environmental Change (IHDP), the World Climate Research Programme (WCRP), and Diversitas. This

partnership constitutes the Earth Systems Science Partnership (ESSP).

The short-term caveat for Figure 2 is the recent findings in the World Energy Outlook 2009, which stated that “global energy use is set to fall in 2009—for the first time since 1981 on any significant scale—as a result of the financial and economic crisis; but, on current policies, it would quickly resume its long-term upward trend once economic recovery is underway” (IEA

2009: p. 42). Reemphasizing the need for a continued urgent response to climate change, the World Development Report 2010 adds that a decline in emissions should not be an excuse to postpone the mitigation actions needed to bend the emissions curve toward a level that is sustainable and does not inflict very costly repercussions on the ecosystems and therefore the economy (World Bank 2009). Future paths are obviously uncertain, and much will depend on what commitments major greenhouse gas (GHG) emitters enter into. At the time of writing, the U.N. Framework Convention on Climate Change negotiations in December 2009 produced a rather open-ended outcome. The Copenhagen Accord does not entail binding commitments for GHG reductions but commits some of the major emitters to submit targets by the end of January 2010. A simulation model was developed by Panya Consultants to simulate the impacts of rainfall, sea level rise, storm surges, and land subsidence. This was calibrated against observations from floods in 1995 and 2002. Simulations covered the entire flood season from July to December and incorporated 10 (T10), 30 (T30), and 100-year (T100) return floods. The return period is an average frequency. A 10-year flood has a 1/10 or 10 percent chance of being exceeded in any one year, a 30-year flood has only 1/30 or 3.33 percent chance, etc. The scenarios generated data on inundated area, water depth, and duration of each scenario. Using different combinations of flood return periods with land subsidence (LS), seal level rise (SR), storm surge (SS), and climate change scenarios (A1FI and B1), 3 baseline and 13 flooding scenarios for 2050 were derived. The simulations derived the depth of inundation across the BMR and the duration of flooding. The damage assessment considered two main categories. Direct damage relates to the replacement value of damaged assets, primarily buildings. These damages occur at the time of the disaster or shortly thereafter. Indirect damage includes sales loss due to temporary suspension of business or income loss because of failure to operate normal economic activities. It also includes loss of informal income among the poor, as defined by the study. (Indirect damage is often called “losses” in the post-disaster assessment literature, but the terminology of the Panya study is used here.) Damage costs were estimated for the base year (2008) and the end year (2050). Inflation was not considered, and all estimates were done using 2008 year prices. Damage assessments were done across all 16 scenarios for nine damage categories.

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The main sectors assessed for both direct and indirect impacts included population, building and housing (residential, commercial, and industrial), transportation, water supply and sanitation, energy, and public health. Indirect damage cost on public health refers to the additional health care cost due to flooding. During a flood, the occurrence of tropical infectious diseases such as acute diarrhea, pneumonia, conjunctivitis, typhoid, and cholera will increase due to the intrusion of wastewater and hazardous waste into the living environment. Obviously, a number of strongly simplifying assumptions had to be made in order for the study to be feasible. Bangkok in 2050 will be quite different from the city of 2008. Known investment plans for further flood protection were taken into account, but other changes in infrastructure could not be projected with sufficient certainty and detail within this study. It is therefore a very stylized calculation of the impacts of climate change—not a forecast of what will actually happen. Nevertheless, it serves the purpose of isolating and illustrating the magnitude of potential impacts of climate change and therefore assists in preparations to mitigate them. The database for making this type of calculation is also highly imperfect. For example, there is little empirical evidence of the actual damage rates related to flooding, but the best available records from previous flooding in Bangkok were used to calculate damage rates on the basis of flood depth. The book value of buildings from legal records may deviate from actual market prices, but it was not feasible to collect market data. The results should therefore be seen as indications of magnitudes—not as precise measurements. Assumptions used and impacts in terms of damage costs of all scenarios considered for the study are available in considerable detail as a part of the full Panya report. This note highlights only the key results and magnitudes of the impact assessment. Findings Overall, the study finds that the damage from a 30-year flood will increase from a bit more than $1 billion to more than $4.6 billion in 2050 due to climate change and land subsidence. The former is already a large sum, but to put it into perspective it represents only about 1 percent of the Bangkok gross regional product. The damage to buildings will be by far the most significant economic impact, much larger than income losses and health care costs (see Figure 3). The poor constitute a minority already in 2008, and they can be expected to represent an even smaller part of the population in 2050. Using current data, one in eight affected inhabitants will be from the condensed housing areas, where most people live below the poverty level. Hence they would be disproportionally affected as a group. Their low average income contributes to the relatively minor aggregate economic loss, but behind that figure is a group of people with limited coping capacity who would suffer the most in relative terms. Health impacts are expected to be of less importance, and the panorama of disease and the quality of health care in 2050 will also be much different, which will serve to further mitigate any health damage from flooding.

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Figure 3. Damage Costs per Category, 2008 and 2050 (million dollars, 2008 prices)

Source: Adapted from Panya 2009. Note: The left set of bars denotes the 2008 situation in a 30-year flood scenario, while the right set denotes the 2050 impact with climatic factors and land subsidence incorporated. Damages to residential buildings in 2050 far exceed those to commercial and industrial buildings (see Figure 4). Damages to residential building are estimated at $1.7 billion, to commercial properties at $1.4 billion, and to industrial buildings at $381 million.

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Figure 4. Damage Costs for Residential, Commercial, and Industrial Buildings

Source: Adapted from Panya 2009. As expected, the study finds that the damage is strongly dependent on the size of the flood and increases to $7.5 billion under the 1-in-100 years scenario (see Figure 5). Figure 5. Damage and Losses Associated with Different Flooding Levels

Source: Adapted from Panya 2009. Note: T10 denotes a flood with a 10 percent chance of being exceeded in any given year, T30 one with a 3.3 percent chance of being exceeded, etc.

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When estimating the damage and losses across the two climate change scenarios considered with land subsidence impacts and sea level rise in the study, the A1FI scenario accrues only 7 percent higher costs than the B1 scenario (see Figure 6). Hence, for the purposes of this study, the differences in climate change scenarios are not that critical, as the difference in precipitation is not expected to be considerable. Figure 6. Damage and Losses across Climate Change Scenarios B1 and A1FI

. Source: Adapted from Panya 2009. However, it is important not to ascribe the increase in future damage to climate change alone. Land subsidence turns out to be a very important factor. While this is not driven by climate change, it amplifies the vulnerability to such change considerably. In 2050, this factor alone will be more important than the direct influence of climate change via precipitation, sea level rise, and storm surge. Hence, addressing land subsidence will be critical. Flooding is not uncommon in Bangkok, and adaptation is already a part of life. Structural measures were undertaken particularly after the devastating 1995 flood—which corresponds to the T30-scenaro—and additional works are under way. However, the current study shows that even with existing plans for extended adaptation, further measures will be required to manage anything beyond a 10-year return flood in 2050. Hence, the study recommends that dikes be raised, pumps be upgraded in capacity, and coastal erosion protection be strengthened. To further underpin those recommendations, a cost-benefit analysis (CBA) was carried out for two flood investment options, as protection against 30-year and 100-year floods. The present value of costs until 2050 is estimated at about $1 billion and $1.5 billion respectively. In the first round, future benefits were calculated on the basis of a static infrastructure as of 2008. Realistically, however, future investments will take place to upgrade infrastructure, residences, and industrial and commercial buildings. Population will grow, albeit not very much according to official planning statistics.

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To allow for those factors, the CBA was repeated with the assumption that the value of benefits of flood control will grow 3 percent per year until 2050. This is obviously just an assumption, but it serves to inject the realistic notion of real growth in asset values and shows the importance of considering this factor. In that case, the net present values for the flood protection investments are positive when using an 8 or 10 percent discount rate, and particularly so in the more ambitious investment alternative (almost $400 million at 8 percent). The discount rate of 8 percent is commonly used to evaluate public investment options in Thailand. The results of the CBA are promising, but more detailed studies will be necessary before embarking on this sizable project. Recommendations As the study discusses in some detail, flood protection is not simply about dikes; it encompasses planning and investments to address a set of issues. In summary, the main recommendations of the study are as follows:

BMR planning needs to systematically incorporate the expected impacts of climate change. Land use planning needs to guide city development to minimize future damage.

Land subsidence is a crucial factor and needs to be more strictly controlled.

Dikes need to be raised, pumping capacity increased, and drainage improved.

Coastal erosion measures need to be undertaken urgently.

Early warning capacity and disaster response should be enhanced.

A flood insurance system needs to be put into place. This will be particularly important to protect farmers in the outer areas from direct flooding as well as from the indirect impacts of enhanced flooding protection of the urban areas.

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References

Global Carbon Project. 2009. Carbon Budget 2008. Global Carbon Budget Consortium, Canberra, Australia. IEA (International Energy Agency). 2009. World Energy Outlook 2009. Paris. Nicholls, R. J., S. Hanson, C. Herweijer, N. Patmore, S. Hallegatte, J. Corfee-Morlot, J. Château, and R. Muir-Wood. 2008. Ranking Port Cities with High Exposure and Vulnerability to Climate Extremes: Exposure Estimates. OECD Environment Working Papers No. 1. Organisation for Economic Co-operation and Development, Paris.

Panya Consultants Co., Ltd. 2009. Climate Change Impact and Adaption Study for Bangkok Metropolitan Region. Final Report. Bangkok.

Raupach, M. R., G. Marland, P. Ciais, C. Le Quere, J. G. Canadell, G. Klepper, and C. B. Field. 2007. Global and Regional Drivers of Accelerating CO2 Emissions. Proceedings of the National Academy of Sciences 104 (24): 10288–93. World Bank. 2009. World Development Report 2010: Development and Climate Change. Washington, DC. 1 The Panya study was carried out by a large team of consultants based in Bangkok, to whom the major credit is due for the analysis. Thanks are also due to the many Bangkok Metropolitan Administration professionals who contributed data and comments to make this study possible. The report was supported by a World Bank team led by Jan Bojö and consisting of Manuel Cocco, Brad Philips, Neeraj Prasad, Pongtip Puvacharoen, Priya Shyamsundar, and Yabei Zhang. Sunanda Kishore assisted in preparing this summary note, Jeffrey Lecksell contributed and cleared the maps, and Linda Starke edited the final version. The many participants in a series of consultative meetings in Bangkok and at the World Bank are thanked for their contributions. Financial support from the Norwegian government through a Trust Fund with the World Bank is gratefully acknowledged. This served as a complement to the World Bank’s own resources. The full study is 258 pages and is too large to be transmitted via regular e-mail because of its extensive use of maps. However, it is posted on www.worldbank.org/eapenvironment. 2 All dollars ($) are U.S. dollars, and an exchange rate of 32 baht per dollar was used. 3 The A1 scenario family describes a future world of very rapid economic growth, a global population that peaks in mid-century, and the rapid introduction of more-efficient technologies. The A1 scenario family develops into three groups, distinguished by their technological emphasis: fossil-intensive (A1FI), non-fossil energy sources (A1T), and a balance across all sources (A1B) (defined as not relying too heavily on one particular energy source). The B1 scenario family describes a convergent world with the same global population that peaks in mid-century and declines thereafter as in the A1 storyline but with rapid change in economic structures toward a service and information economy, with reductions in material intensity and the introduction of clean and resource-efficient technologies.