Final Report. adpc ASIAN CITIES CLIMATE CHANGE RESILIENCE NETWORK (ACCCRN) THAILAND - PHASE I. October Asian Disaster Preparedness Center

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1 Final Report ASIAN CITIES CLIMATE CHANGE RESILIENCE NETWORK (ACCCRN) THAILAND - PHASE I October 2009 adpc Asian Disaster Preparedness Center

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3 Foreword Secondary and tertiary cities in Asia are often planned for development to relocate evenly both economic growth and populace. This economic goal makes smaller cities the site of increasing urbanization and land use change as they grow into the surrounding peri-urban space. However, these cities usually do not strictly enforce building regulations and monitor land use, nor do they have enough qualified technical staff to engage in planning, development control and construction regulation. This challenge is expected to be harder in the future. Coastal erosion and the projected increase in sea levels from climate change scenarios underline the need for city governments to re-plan their infrastructure to be ready for the future. There is a lot of indication of a global climate change; events around the world that can be evidence to it include the heat wave in Western Europe, the recent flooding in England, and the monsoon floods in South Asia. Urban planning of coastal cities should include a long-term climate scenario, and appropriately design the infrastructure. Unfortunately, city governments in general seem to fail to design action plans to address the problems associated with current vulnerability. City governments have limited institutional capacity to assess risk trends. This is related to the lack of technical information and probable scenarios of hazard exposure, socio-economic and physical vulnerabilities, risk assessment tools, early warning mechanism, and historical information on destructive events. It is also related to the ability to use technical information and probable scenarios within the urban planning and decision-making processes. The RF Climate Change Resilience Initiative is an important initiative that can be utilized by city governments to devise strategies to cope with the climate changes already happening, and other hydro-meteorological deviations that will accelerate in the next decades. Within this grant initiative, the Asian Disaster Preparedness Center has tried to emphasize the interface between climate and urban disaster risk: Urban areas will increasingly play a major role in any climate change-related strategy, because cities have the potential to be either major polluters or major engines for green technological innovations and adoption thereof. The urban poor are increasing in proportion of the urban population, but are the most disadvantaged sector vis-à-vis climate-induced disasters. They have the fewest resources to prepare and plan for the impacts, the lowest capacity to respond in their own survival, the exposed to climate extremes, and the most reliant on the climate for livelihood. Urban governments need to step up their capacities and plan for longer-term futures with greater uncertainties that are attendant with climate change. This document reports a six-month study for the purpose of creating snapshots of the climate scenarios prevailing in the five short listed urban areas, namely Muang Chiang Rai, ii

4 Muang Hat Yai, Muang Udon Thani, Muang Phuket, Muang Samut Sakorn. These snapshots are our contribution to a selection of two cities that can serve as urban climate resilience demonstration sites for the rest of Thailand. We tried to ascertain the real status of the readiness of the five cities by answering the following questions: How are disasters and climate hazards influencing the life of people in the selected cities? What impacts have climate-related hazards brought to these cities in the recent past? What sectors are the most affected by disasters and climate hazards? What data gaps exists in doing detailed studies on the changes in climate profiles? What is the technical capacity of cities to implement relevant projects and programs? TEI report is the companion report that provides details on the social, governance and institutional issues surrounding urban climate resilience. We wish to thank RF for providing Thailand an opportunity to open the discourse on urban climate resilience. We extend our heartfelt congratulations to the target cities for taking the steps to cooperate in this important project. ADPC wishes to acknowledge the government agencies that provided data for our study: Department of Disaster Prevention and Mitigation (DDPM), Thailand Meteorological Department, Geo-Informatics and Space Technology Development Agency (GISTDA) Department of Mineral Resources (DMR) Pollution Control Department (PCD) National Housing Authority (NHA) Office of National Environment Policy and Planning (ONEP) Municipality of Chiang Rai, Udon Thani, Hat Yai, Phuket, Samut Sakhon This study will be the beginning of more work from the Asian Disaster Preparedness Center to build the technical capacities of urban governments and their stakeholders for understanding climate risks, as well as for our advocacy for urban climate resilience. Dr. Bhichit Rattakul Executive Director iii

5 Table of Contents Foreword... ii Dr. Bhichit Rattakul... iii Table of Contents... iv List of Figures... vii List of Tables... xi List of Abbreviation... xiii 1 Background at country-level Trend of Urbanization trend Climate change overview Management framework on climate change impacts Objectives of the study under ACCCRN phase I Overall objectives of the project Main objectives of the study by ADPC under phase I Key expected outcomes Methodology Data needs for the study Data collection Steps used for delivery of final outputs Detail explanation of study approach Identification of source agencies Establishment of survey teams and conducting survey Analysis of data Scoring and methodology for prioritization Brief introduction to 5 selected cities Chiang Rai Location Resources Climate Climate hazard and extreme events Udon Thani Location Resources Climate Climate hazard and extreme events Hat Yai Location Resources Climate Climate hazard and extreme events Phuket Location Resources Climate Climate hazard and extreme events Samut Sakhon Location Resources iv

6 4.5.3 Climate Climate hazard and extreme events Comparative assessment of Air and Water Quality in Five cities Climate scenario and observed trends in 5 cities Change of precipitation pattern Chiang Rai Udon Thani Hat Yai Phuket Samut Sakhon Change in temperature pattern Chiang Rai Udon Thani Hat Yai Phuket Sea level rise and storm surges Future sea level rise Effects of sea level rise Disaster impacts and extreme natural hazard events Natural disaster events and impacts within the target provinces Muang Udon Thani Muang Chiang Rai Muang Hat Yai Muang Phuket Muang Samut Sakhon Natural Disaster Impacts in Muang district areas recorded by DDPM Actions taken to reduce impacts of climate hazard extreme events Air and water quality observations Air Quality Variations Water quality indicators / Water Pollution Assessment of sector based vulnerability Vulnerability of housing and human settlements Health and Sanitation Education sector Infrastructure Utility services Industrial/commercial sector Urban Planning Data availability for further study Availability of spatial data Chiang Rai Udon Thani Phuket Hat Yai Samut Sakhon Comparative assessment of spatial data Availability of meteorological and atmospheric data Chiang Rai Udon Thani Phuket v

7 9.2.4 Hat Yai Samut Sakhon Comparative assessment on meteorological condition data availability Availability of disaster related data, damage and loss data Chiang Rai Udon Thani Phuket Hat Yai Samut Sakhon Comparative assessment on disaster related data availability Recommendations Comparative assessment of Impact of Climate hazard r events Comparative Assessment in relation to Climate Change scenario of target cities Comparative assessment of air and water quality Comparative assessment of the Vulnerability of various sectors to climate change Overall assessment References Annexure vi

8 List of Figures Figure 2.1. Map of study area... 7 Figure 2.2. Map of UN-Habitat on the Asian LECZ cities Figure 4.1. Map of Chiang Rai district (Source: GISTDA) Figure 4.2. Normal monthly mean temperature over Chiang Rai from 1980 to (a) maximum temperature(tmax) and highest Tmax (Ext. Tmax), (b) same as a but for minimum temperature and (c) mean temperature (Source: Thailand Meteorological Dept.) Figure 4.3. Normal monthly mean rain parameters over Chiang Rai from 1980 to (a) total rain (b) number of rainy days and (c) maximum rain in 1 day (Source: Thailand Meteorological Dept.) Figure 4.4. Map of Udon Thani district (Source: GISTDA) Figure 4.5. Normal monthly mean temperature over Udon Thani from 1980 to (a) maximum temperature(tmax) and highest Tmax (Ext. Tmax), (b) same as (a) but for minimum temperature and (c) Mean temperature (Source: Thailand Meteorological Dept.) Figure 4.6. Normal monthly mean rain parameters over Udon Thani from 1980 to (a) total rain (b) number of rainy days and (c) maximum rain in 1 day (Source: Thailand Meteorological Dept.) Figure 4.7. Map of Hat Yai district (Source: GISTDA) Figure 4.8. Normal monthly mean temperature over Hat Yai from 1980 to 2008 (Source: Thailand Meteorological Dept.) Figure 4.9. Monthly normal rainfall over Hat Yai (mm) from 1980 to 2008 (Source: Thailand Meteorological Dept.) Figure Map of Phuket Province (Source: GISTDA) Figure Monthly mean normal of temperature; Tmax, Tmin, mean Temperature, Ext. Tmax and Ext. Tmin obtained from the data 1980 to 2008 over Phuket (Source: Thailand Meteorological Dept.) Figure Normal monthly mean rain parameters over Phuket from 1980 to (a) total rain (b) number of rainy days and (c) maximum rain in 1 day (Source: Thailand Meteorological Dept.) Figure Map of Samut Sakhon Provice (Source: GISTDA) Figure Particulate matters.pm10 concentration in urban areas from 1997 to 2008 (Source: Thailand Pollution Control Dept.) Figure O3 Low-Ozone concentration in urban areas from 1997 to 2009 (Source: Thailand Pollution Control Dept.) Figure SO2- Sulfur Dioxide concentration in urban areas from 1997 to 2009 (Source: Thailand Pollution Control Dept.) Figure 5.1. Annual mean temperature & yearly total rainfall over Chiang Rai (Source: Thailand Meteorological Dept. and Analysis) Figure 5.2. Frequency of rainy days & different rainy days over Chiang Rai in Apr-May (Source: Thailand Meteorological Dept. and Analysis) Figure 5.3. Frequency of rainy days & different rainy days over Chiang Rai in Oct-Nov (Source: Thailand Meteorological Dept. and Analysis) Figure 5.4. Frequency of rainy days & different rainy days over Chiang Rai in JJAS (Source: Thailand Meteorological Dept. and Analysis) Figure 5.5. Annual mean temperature & yearly total rainfall over Udon Thani (Source: Thailand Meteorological Dept. and Analysis) vii

9 Figure 5.6. Frequency of rainy days & higher than heavy rainfall days over Udon Thani during April-May(Source: Thailand Meteorological Dept. and Analysis) Figure 5.7. Frequency of rainy days & higher than heavy rainfall days but for Oct-Nov over Udon Thani (Source: Thailand Meteorological Dept. and Analysis) Figure 5.8. Frequency of rainy days & higher than heavy rainfall days for June- September over Udon Thani (Source: Thailand Meteorological Dept. and Analysis) Figure 5.9. Annual mean temperature & yearly total rainfall over Hat Yai (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly rainfall over Hat Yai during the peak monsoon months of October- December during the period from (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of rainy days & heavy rainy days over Hat Yai in Apr-May (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of rainy days & heavy rainy days over Hat Yai in Oct-Nov (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of rainy days & heavy rainy days over Hat Yai in June- September (Source: Thailand Meteorological Dept. and Analysis) Figure Annual mean temperature & yearly total rainfall over Phuket (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of rainy days & higher than heavy rainfall days over Phuket during April-May (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of rainy days & higher than heavy rainfall days for October- November (Phuket) (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of rainy days & higher than heavy rainfall days for June- September (Phuket) (Source: Thailand Meteorological Dept. and Analysis) Figure Frequency of annual rainy days and other rain days over Samut Sakhon (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean temperature variation during hot weather season (March to May) from 1980 to 2008 over Chiang Rai. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for April is plotted (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean temperature variation during cold weather season (December to February) from 1980 to 2008 over Chiang Rai. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for December is plotted (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean extreme maximum temperature (highest Tmax) variation during April and monthly mean extreme minimum temperature (lowest Tmin) during December over Chiang Rai (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean temperature variation during hot weather season (March to May) from 1980 to 2008 over Udon Thani. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for April is plotted (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean temperature variation during cold weather season (December to February) from 1980 to 2008 over Udon Thani. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for December is plotted (Source: Thailand Meteorological Dept. and Analysis) viii

10 Figure Monthly temperature variations (Tmax, Tmin) from 1980 to 2008 during winter season (Apr) over Hat Yai (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly temperature variations (Tmax, Tmin) from 1980 to 2008 during winter season (Jan) over Hat Yai (Source: Thailand Meteorological Dept. and Analysis) Figure Number of days with Tmax more that 35 0 C during hot weather season from March to May over Hat Yai. The linear trend for April is plotted in the figure (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean temperature variation during hot weather season (March to May) from 1980 to 2008 over Phuket. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for April is plotted (Source: Thailand Meteorological Dept. and Analysis) Figure Monthly mean temperature variation during cold weather season (December to February) from 1980 to 2008 over Phuket. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for January is plotted (Source: Thailand Meteorological Dept. and Analysis) Figure 6.1. Map of LECZ of Thailand (Source: CIESIN, Columbia University) Figure 6.2. Damages and destruction in Muang Udon Thani due to disaster (Source: DDPM provincial office, Municipality) Figure 6.3. Damages and destruction in Chiang Rai province (Source: DDPM provincial office, Municipality) Figure 6.4. Damages and destruction in Hat Yai (Source: Municipality) Figure 6.5. Landslide events map in Phuket province (Source:GERD Kasetsart University, ADPC RECLAIM II ) Figure 6.6. Damages and destruction in Phuket (Source: RECLAIM II, Municipality) Figure 6.7. Damages and destruction in Samut Sakhon (Source: Municipality) Figure 6.8. Projects relevant to climate change and disaster risk reduction (Source: Provincial office, Municipality, field survey) Figure 6.9. Flood protection scheme in Muang districts (Source: Municipality) Figure Landslide early warning measures developed by ADPC and Kaasetsart universities in Phuket (Source: ADPC RECLAIM II) Figure Tsunami warning system in Phuket (Source: field survey and National Disaster Warning Center) Figure Community level training and capacity building program organized by municipality and DDPM in Hat Yai and Phuket (Source: Municipality) Figure Community level training and capacity building program organized by municipality and DDPM in Udon Thani and Chiang Rai (Source: Municipality) Figure Community and municipality capacity building program organized by municipality, DDPM, and ADPC in Phuket (Source: Municipality and ADPC RECLAIM II) Figure Various publication relevant to disaster capacity building development Figure 7.1. Pm 10 and O 3 concentration (Source: Thailand Pollution Control Dept.) Figure 7.2. CO, SO 2 and NO 2 concentration (Source: Thailand Pollution Control Dept.) Figure 8.1. Inundation map of Chiang Rai (Source: DDPM Chiang Rai province, Municipality, Field survey) Figure 8.2. Inundation map of Hat Yai (Source: ADPC TUDMP, Municipality, Field survey) Figure 8.3. Inundation map of Phuket (Source: Municipality, Field survey) ix

11 Figure 8.4. Pictures of occupancy types in Chiang Rai (Source: Field survey) Figure 8.5. Pictures of occupancy types in Udon Thani (Source: Field survey) Figure 8.6. Pictures of occupancy types in Hat Yai (Source: Field survey) Figure 8.7. Pictures of occupancy types in Phuket (Source: Field survey) Figure 8.8. Pictures of occupancy types in Samut Sakhon (Source: Field survey) Figure 8.9. Vulnerable buildings in Udon Thani (Source: Field survey) Figure Vulnerable buildings in Chiang Rai (Source: Field survey) Figure Vulnerable buildings in Hat Yai (Source: Field survey) Figure Vulnerable buildings in Phuket (Source: Field survey) Figure Ratio of malaria cases per 100,000 of population (Source: Department of disease control, Ministry of Public Health) Figure Ratio of leptospirosis cases per 100,000 of population (Source: Department of disease control, Ministry of Public Health) Figure Ratio of dengue hemorrhagic fever (DHF) cases per 100,000 of population (Source: Department of disease control, Ministry of Public Health) Figure Hospitals and health public awareness program (Source: Field survey) Figure School building in Muang district (Source: Field survey) Figure Flooded school in Hat Yai (Source: Municipality) Figure Disaster capacity building program in school (Source: DDPM Udon Thani municipality) Figure Inundation area due to flood (Source: ADPC TUDMP, ADPC RECLAIM II, Municipality) Figure Damaged infrastructure due to disaster in Muang district (Source: DDPM, Municipality) Figure Flood protection systems in Udon Thani (Source: Municipality) Figure Flood protection systems in Chiang Rai (Source: Field survey) Figure Flood protection systems in Hat Yai (Source: Field survey) Figure Coastal erosion protection system in Samut Sakhon (Source: Municipality, Field survey) Figure Example of flood protection scheme in Udon Thani (Source: Municipality) Figure Example of flood protection scheme in Hat Yai (Source: Municipality) Figure Utilities in Muang district (Source: Municipality, Field survey) Figure Commercial areas in Muang district (Source: Field survey) Figure Vulnerable commercial and tourism facilities (Source: ADPC RECLAIM II, Municipality) Figure Land use plan of Udon Thani (Source: Municipality) Figure Land use plan (Top) and flood inudation map (Bottom) of Chiang Rai (Source: Municipality) Figure Land use plan (Top) and flood inundation map of Hat Yai (Source:ADPC TUDMP, Municipality) Figure Land use plan (Top) and landslide hazard map (Bottom) of Phuket (Source: ADPC RECLAIM II, Municipality) Figure Land use plan of Samut Sakhon (Source: Municipality) Figure Urban development in Muang district (Source: Municipality, Field survey) x

12 List of Tables Table 1.1. Population Projection for the whole Kingdom in Thousand (Source NESDB)... 2 Table 4.1. Income of Phuket (Department of Provincial Administration) Table 5.1. Annual mean temperature and rainfall comparison during two periods over Chiang Rai; and (Source: Thailand Meteorological Dept. and Analysis) Table 5.2. Annual mean temperature and rainfall comparison during two periods over Udon Thani; and (Source: Thailand Meteorological Dept. and Analysis) Table 5.3. Annual mean temperature and rainfall comparison during two periods over Hat Yai; and (Source: Thailand Meteorological Dept. and Analysis) Table 5.4. Annual mean temperature and rainfall comparison during two periods over Phuket; and (Source: Thailand Meteorological Dept. and Analysis) Table 5.5. SRES scenario (Source: United Nations IPCC) Table 6.1. Worst cases of flood events in provinces (Source: DDPM main office) Table 6.2. Drought data from 2004 to 2009 (Source DDPM main office) Table 6.3. Tropical storm data (Source: Thailand Meteorological Dept) Table 6.4. Summary of flood disaster in Muang district areas (Source: DDPM provincial office) Table 6.5. Summary of strong wind disaster in Muang district areas (Source: DDPM provincial office) Table 6.6. Summary of fire disaster in Muang district areas (Source: DDPM provincial office) Table 6.7. Summary of landslide disaster in Muang district areas (Source: DDPM provincial office) Table 6.8. Summary of drought disaster in Muang district areas (Source: DDPM provincial office) Table 6.9. Existing and previous major projects relevant to climate change and disaster risk reduction in Udon Thani (Source: Udon Thani Municipality) Table Existing and previous major projects relevant to climate change and disaster risk reduction in Chiang Rai (Source: Chiang Rai Municipality) Table Existing and previous major projects relevant to climate change and disaster risk reduction in Hat Yai (Source: Hat Yai Municipality) Table Existing and previous major projects relevant to climate change and disaster risk reduction in Phuket (Source: Phuket Municipality) Table 7.1. Availability of pollution (Source: Thailand Pollution Control Dept.) Table 7.2. Summarize of the pollution types (Source: Thailand Pollution Control Dept.) Table 8.1. Building occupancy type (Source: Municipality) Table 8.2. Building in flood prone area (Source: ADPC TUDPM, DDPM provincial office, Municipality, Calculation by ADPC) Table 8.3. Ratio of disease per 100,000 population of Hat Yai municipality (Source: Municipality) Table 8.4. Ratio of disease per 100,000 population of Udon Thani municipality (Source: Municipality) Table 8.5. Ratio of disease per 100,000 population of Phuket municipality (Source: Municipality) Table 8.6. List of universities in target cities (Source: Commission of Higher Education) xi

13 Table 8.7. Location of water supply source and sanitary landfill in Muang district (Source: Municipality) Table 9.1. Spatial data source Table 9.2. Comparative assessment of spatial data availability Table 9.3. Comparative assessment of meteorological and atmospheric data availability Table 9.4. Comparative assessment on disaster related data availability among five cities Table Comparative assessment of five provinces evaluating their relative impact due to disaster events Table Comparative assessment of five provinces evaluating on climate change scenario and water-air quality Table Comparative assessment on five cities evaluating on vulnerability of various sectors to climate change (Rate as "Highest vulnerable = 5 to Lowest vulnerable = 1") Table Summary of comparative assessment of data availability xii

14 List of Abbreviation ACCCRN ADPC BMA BOD CO CO 2 DDPM DHF DMCR DMR DO FCB GIS GISTDA IPCC LECZ MoU NESDB NHA NOX O 3 ONEP PCD PM PMBC ppm ppb RECLAIM RF SO X TCB TEI TMD TUDMP Asian Cities Climate Change Resilience Network Asian Disaster Preparedness Center Bangkok Metropoltan Administration Bio chemical Oxygen Demand Carbon Monoxides Carbon Dioxides Department of Disaster Preparedness and Mitigation Dengue Hemorrhagic Fever Dept of Marine and Coastal Resources Dept of Mineral Reources Dissolved Oxygen Fecal Coliform Bacteria Geographical Information System Geo- Informatics and Space Technology Development Agency Intergovernmental Panel on Climate Change Low Elevation Coastal Zone Memorandum of Understanding National Economic and Social Development Board National Housing Authority Nitrogen Oxides Ozone Office of National Environmnet Policy and Planning Pollution Control Dept Particulate Matter Phuket Marine Biological Centre Part per Million Part per Billion Regional Capacity Enhancement for Landslides Impact Mitigation Rockefeller Foundation Sulfur Oxides Total Coliform Bacteria Thailand Environment Institute Thailand Meteorological Department Thailand Urban Disaster Management Project xiii

15 1 Background at country level 1.1 Trend of Urbanization trend Bangkok Metropolis is still considered the prime city of the country. The size of the city s population is 36 times of the second largest city, Nakhonrajchasima Municipality. There are 10 large sized cities (100, ,000 persons), 27 medium sized cities (50, ,000 persons), 91 urban communities (25,000 50,000 persons), 962 small urban communities (10,000 25,000 persons), and 6,687 rural communities in the country. Source (NESDB, 2006). The majority of urban population agglomerated in the central region of the country, especially in the Bangkok Metropolitan region, the Eastern Seaboard and the Western Seaboard. The urban expansion has occurred in the industrial region and peri-urban areas such as Ayuthaya, Chonburi and Rayong. When looking at the general global urban development in the future, the United Nations stated that within next 20 years there will be more urban than rural population. Six out of ten world populations will reside in urban areas. The increase in number of population will be mainly in the large cities as people will migrate from rural to urban area. There will be more megacities and these megacities will especially locate in Asia. It is expected that in 2010, 50% of the country s population will live in cities. The Bangkok Metropolis will be one of the megacities in the year 2030 with more than 10 million populations. The five cities in the selection process will also be more populated as they are the major growth centers in different regions of the country. There will be 14 million population increases in urban area in 20 years (2030). In the year 2006, there were 21.5 million people out of the country s 62.8 million people residing in urban areas. If the projected population in 2030 is 70.6 million, then, there will be 35 million urban populations. Of all these urban population, 14 million people will reside in the Bangkok Metropolitan Region. As analyzed by the Department of City Planning, BMA, about 10 percent of the country s population will be in the Bangkok Metropolis whereas the rest (10%) will be in the region (BMA, Department of City Planning, 2006). When looking at the population pyramid of the country s population in 2030 projected by NESDB as seen in Table 1.1, there will be changes in the age and sex structure. The trend for increase of female than male, making the sex ratio change to 51.15% of female and 48.85% of male is predicted. The age structure shows that the youth population will decrease meanwhile the middle aged (15-59) and the aging population (60+) will increase. The NESDB reveals that the country is moving forward to an aging population society. 1

16 Table 1.1. Population Projection for the whole Kingdom in Thousand (Source NESDB) Age Sex Year Male 7,866 7,698 6,924 7,404 Female 7,477 7,381 6,605 6, Male 20,143 22,462 2,3330 2,2422 Female 20,882 23,025 23,574 2, Male 2,656 3,525 5,334 7,656 Female 3,211 4,468 6,918 10,064 Total 62,236 68,559 72,685 76,734 Moreover, NESDB proposed that the country will move towards a creative and green economy for the next 5 years and onwards. This state of economy is based in more urban than in rural areas. As a result, they will draw the population of years old to the cities. The aging population will reside both in urban and rural areas. 1.2 Climate change overview The utilization of fossil fuel in the country is among many causes resulting in climate change phenomena in the country. From research conducted for MANRES project on the economics of watershed management with a case study of Mae Teng (TDRI, 1995), it is found that urban areas, especially those locate along the waterways (canals and rivers) and coastal area are subjected to impacts from climate change. The effects are the result from release of green house gases to the global atmosphere. The phenomena include change in temperature (average temperatures high and low temperature, number of hot and cool days in a year) and changes in precipitation pattern (amount of rainfall, number of rainy days in a year and intensity). The study on the impact of climate change on natural resources and environment in Thailand conducted by Mahidol University in 2008 divided the time period into 3 periods; , , and The assessment is based on SEA START (2008) study. The findings for the climate change scenario for the country area: 1) The average highest temperature during the first period ( ) will not change much and it will be C. But, the area coverage will expand to cover the whole country region, lower northern region and part of the southern region. By the end of the century, the average high temperature will increase about 4 C (38-40 C) covering the 2

17 whole country. The country will experience longer summer periods. By 2039, all the central region and part of the southern region will have summer periods longer than 8 months in a year. By the end of the century, the summer for the whole country will last longer than 8 months/year (Mahidol University (2008) pp 24-25). 2) Secondly, the average lowest temperature for every region, except the northern region, will be 24 C from which will be higher than the past minimum temperatures. The average lowest temperature in the north will maintain at C. Further, the extent of area coverage for lowest temperature will be decreased. By the end of the century (2089), more than 90 percent of the area of the country will have the lowest temperature as high as 24 C. The period of cold season will be decreased. In the area of the northern and the northeastern regions, the duration of cold period with 16 C will be reduced from months during the beginning of the century to 1 month (Source Report, Mahidol University (2008), pp 24-25). 3) Thirdly, there will be increase in annual rainfall for the whole country. However, the total annual rainy days will remain more or less the same as before (Mahidol University (2008), pp 25). As a result, Institute of Public Studies of Chiang Mai University has assessed that there are 3 areas of risks and vulnerability for the country: Physical, infrastructure, settlement and tourism; Agriculture and food security; and Health and public health services The assessment is in the process to propose national plan to encounter climate change. 1.3 Management framework on climate change impacts Following the Kyoto Protocol 2002, Thailand is classified in the group of the countries under Non-Annex I Countries. Thailand does not have obligation to reduce greenhouse gases. Nevertheless, the government considered that the country is in the process of continuous socio-economic development, there may be increase in greenhouse gas emission in the future. The country should participate in global forum on alleviating the impact of climate change. As a result, the Ministry of Natural Resource and Environment started establishing work plan to follow the international agreement on climate change in This project incorporated all related government and non-government agencies to work together. The Office of Environment Policy and Planning (ONEP) have integrated many ideas, policies, and plans from related agencies. Then the first national strategy on climate change was formulated in 2006 under the participatory process of involving all concerned parties. By the beginning of 2008 the cabinet approved the national strategies ( ). The related government agencies had to use as the framework for their own organizations policies, plans, and actions. The objective of the national strategy on climate change management is as follow; 3

18 1. To prepare the country to understand the issue, to mitigate, and to adapt to the impacts from climate change. 2. To join the global panel in reducing the emission of greenhouse gases on the sustainable development basis following the international agreement at the Kyoto Protocol. 3. To promote the integration from concerned parties in planning and implementation in order to solve the country s climate change problems systematically. There are 6 strategies to fulfill the above objectives. These strategies for action plans are: 1) To build capacity in adaptation to mitigate and reduce the vulnerability results from climate change. 2) To support the reduction of greenhouse gas emission and increase of area absorbing gas on the sustainable development basis. 3) To support research and development in order to promote clear understanding on climate change. 4) To build awareness and participation in problem solving related to climate change. 5) To increase potentiality of related personnel and agencies in implementing climate change related projects and 6) To develop international corporation tasks with foreign counties The proposed strategies were proposed by ONEP, the Ministry of Natural Resources and Environment. The implementations of these strategies are suggested to be performed by almost all government agencies. The local administrative organization is also play important roles in the strategies suggested. As seen from above the objectives of the National Strategy proposed are in line with the objectives of the Program under Asian Cities Climate Change Resilience Networks implemented jointly by Thai Environmental Institute (TEI) and Asian Disaster Preparedness Center (ADPC) in selected cities in Thailand and supported by Rockefeller Foundation. 4

19 2 Objectives of the study under ACCCRN phase I The environmental issue of climate change poses great challenges facing decision makers at many levels. Shifting weather patterns threatens food production, infrastructure durability and livelihood sustainability through increased unreliability of precipitation and increased unpredictability of temperature; Storm surges demolish fragile economic activities; rising sea levels contaminate water bodies and increase the risk of catastrophic flooding; and a warming atmosphere expands the risk of pests and diseases once limited to the tropics to widespread pole-ward. Climate change still relies on potential climate patterns. Uncertainties remain in climate change science, especially regarding the operation and interaction of Earth systems over various timeframes and how subsystems react to feedbacks. But, unpredictability of climate change is part of what it makes it so dangerous (Smith 2008). Subsequently, building climate change scenarios is crucial to encompass the whole range of climatic possible evolutions. Each scenario will be attributed a percentage reflecting its reliability and its propensity to occur. The linkage between the climate change effects and its impacts, logically demonstrated through the scenarios, will enable the decision makers to get a clear picture of the potential changes and will guide them to take the necessary steps to adapt to climate change impacts. The project is working in urban context, where most of the local assets in terms of economic, social and cultural values are concentrated. The vulnerability assessment ADPC will further conduct on infrastructure and built up environment will give a comprehensive understanding of what is at risk at the micro-scale level in the two selected cities. TEI will further identify the most accurate stakeholders to carry on climate change adaptation initiatives at the city level. Decision makers can consequently identify and advisedly take decision on the most accurate mechanisms towards climate change at local adaptation. 2.1 Overall objectives of the project The primary objective of the ACCCRN Program is to build climate change resilient urban communities with a focus on poor and vulnerable groups by creating robust models and methodologies for assessing and addressing risk through active engagement and analysis of various cities. India, Indonesia, Vietnam and Thailand are the selected countries by ACCCRN initiatives to foster urban resilience against changing climate patterns. Under Phase I, ACCCRN has a broad review for selection of number of cities to Understand the vulnerability to climate change in those cities Investigate the readiness of those cities to engage with the project on resilience Understand the physical. Social, political and economic context of the selected cities In line with the broader objectives of ACCRN, through the Phase I of the Thailand Project, a screening survey of some of the selected secondary cities in Thailand is carried out to help identifying most promising two cities to be the Pilot cities of the Phase II of the Project. 5

20 The main objective of the project phase I is to: 1. Develop the potential climate change scenarios and short, medium and long term impacts to urban built up 2. Assess previous or/and existing adaptation measures on climate change which have been implemented at city level 3. Present data gaps observed in five cities for developing the profile of physical vulnerability in relation to climate change adaptation 4. Identify two cities which can be studied in detail to identify options for integrating climate change adaptations in the governance process considering pre identified indicators for modifications to built environment Initially, the Rockefeller Foundation has identified five (5) cities in Thailand which have different background on the geographical location, types of main income generation activities, population structure and other key parameters. The ADPC executed project activities in association with Thai Environmental Institute (TEI) in the following urban areas in Thailand. They are 1. Udon Thani Province - Muang District 2. Chiang Rai Province - Muang District 3. Phuket Province - Muang District 4. Songkhla Province - Hat Yai District 5. Samut Sakhon Province - Muang District and selected suburban districts 6

21 Figure 2.1. Map of study area The Rockefeller Foundation under its ACCCRN initiative has requested ADPC and TEI to study jointly and report in the suitability of above cities to be identified as potential Pilot 7

22 Demonstration Cities under the Phase II. The study area of the selected cities is within Muang District boundary but in some cases (such as Samut Sakhon, Phuket) the study area are extended beyond the Muang District limits in order to capture potential climate change impacts and other variations of physical vulnerability considering the rapid urban expansion. The decision on Pilot Demonstration Cities under the Phase II, will be largely depending on the availability of data for further studies for delineating the degree of vulnerability to climate change impacts and associate risk which is the focus area of the study carried out by ADPC. It also based on other criteria such as availability of institutional support for undertaking reforms for building Climate Change resilient urban communities, which are the focus of the study carried out by TEI. Although two cities are selected for further activities, studies carried out in other cities will still have a benefit as the study findings will be useful to respective cities as well as to ACCCRN for future interventions. Adaptation of a long term climate risk reduction strategy and promoting a risk based development agenda for sustainable development is the ultimate aim. The study will benefit the potential decision making, planning and implementation of short, medium and long term strategies for building climate resilient cities and urban communities. 2.2 Main objectives of the study by ADPC under phase I The purpose of the present initiative by ADPC is to conduct an evaluation which will establish the preliminary findings and its status on data availability for assessment. Finally, it helps identification of most promising two Pilot cities in the context of data availability and assessment of climate change impacts and risk factors. Through the project phase I, ADPC, based on the technical parameters, addresses the issues on physical risk factors such as vulnerability of built environment, infrastructure, lifeline facilities, natural and environmental resources etc. where as TEI evaluates the human, social, economic aspects of vulnerability. ADPC and TEI work very closely having a partnership arrangement to support each other ensuring close association with local, provincial authorities, cities and other relevant agencies to obtain necessary inputs for the study. The findings of this city assessment would create the basis for the design of the project phase II of ACCCRN program in Thailand. Through this city level engagement in subsequent phases, awareness creation and capacity development will be expected to undertake based on the detailed comparative assessment among the selected cities and findings. The study aims at: 1) Understanding risk profile of five cities/provinces on climate change and trends observed 2) Assessing the context of vulnerability to climate change impacts of five cities/ provinces in terms of physical, environment point of view 3) Identifying the gaps in terms of availability of Technical data and data sources for building the climate change scenarios and impacts to urban built up area 8

23 Under the Phase I, ADPC expects that the recommendations (Phase I) will facilitate Rockefeller Foundation to decide on selection of priority cities for the 2 nd Phase. A parallel study on institutional, political, economical aspects and city readiness to undertake climate adaptation measures is carried out by TEI. 2.3 Key expected outcomes In most cases, climate change risk reduction is not viewed as a priority action in sustaining the urban development gains since currently no or limited attempts are being made for such analysis to be carried out for vulnerable secondary cities in Thailand. Further, there is a scarcity of monitoring tools available for analyzing the impacts. It is globally accepted that the human induced environmental degradation affects temperatures, precipitation patterns, sea levels and storm frequencies etc. in cities. These urban areas experience frequent occurrences of hydro-meteorological disaster events with direct and indirect losses of social and economic nature. Preliminary studies in the Phase I will be useful for city governing bodies and provincial authorities to initiate productive actions leading to long term solutions, local level adaptation options and identifying gaps. Using the results of these studies, city authorities can have opportunities for climate change adaptation strategies included in development planning, in the long run. For example, cities of Phuket, Hat Yai and Chiang Rai being predominantly cities of tourist attraction, city authorities will be able to mitigate climate change impact on the respective sectors in the long term. The outcome will be useful for the city authorities to initiate proactive actions to undertake appropriate long term solutions through integration of adaptation measures in urban development. In the light of above mentioned potential advantages, the key outcome of the proposed study can be identified as the following: Assessment of the status of impacts of climate change in five selected cities/provinces Assessment of the extent of vulnerability for disasters and the trend of change of disasters Evaluation of data availability for study on previous events and trends as well as for study of potential exposures to future climate change scenarios Identification of source agencies and data providers, availability of essential data and information gaps, outlining the areas for further qualitative and quantitative assessment Identification of the sources of most useful information for developing strategy for facing future challenges on climate change impacts 9

24 Figure 2.2. Map of UN-Habitat on the Asian LECZ cities Reducing physical vulnerability is thereby one of the priorities towards climate change adaptation. Hazard prone areas are firstly identified and well demarcated; the physical features within each defined areas are then listed and their weaknesses assessed. This study gives a clear idea of the current built up resilience statement and enables to formulate specific recommendations on adaptation measures to strengthen local resilience towards climate change effects. 10

25 3 Methodology 3.1 Data needs for the study Thailand country project phase I of ACCCRN program, considered five cities, and main objective was the selection of two cities for the study under next phase. In order to meet study objectives, ensuring the availability of data under each study component was a crucial factor. Outcome of phase I study expected to help evaluation of the potential and the feasibility of further analysis under phase 2 for the two cities selected as the core beneficiaries of ACCCRN program. To proceed towards in-depth studies, it was felt that a certain amount of base data is required covering a considerable period. The consistency in terms of data coverage for all cities and short time period available for the study were seen as challenges. Furthermore, even if data is available, reliability of data also needs to be evaluated. ACCCRN initiative focuses on urban areas; thereby district as well as city level information are needed to conduct a sector based urban climate change vulnerability assessment. The resolution of data for instance is of high importance for study on spatial distribution of relevant sectors at risk from climate hazards. With regards to climate parameters, the time period covered by the data set is important as it primarily will be used for trend analysis and also to draw some projections. Higher the coverage the team felt it will help to produce better future projections and also to come up with a better scenario assessment. Therefore, the team has developed initial plans to collect data concerning three categories; firstly infrastructure data including roads, buildings, drainage and sewerage network, power and communication; then meteorological data such as temperature data, precipitation data, wind data and air and water quality data and finally disaster related past data in terms of number of events, damages, and loss per disaster type etc. Each data category has been assessed and rated according to two other criteria also: namely data availability and data reliability. Rating has been assigned in a scale of 1 to 5 with 1 as the lowest and 5 as the highest. Zero 0 implies that no data exists. 3.2 Data collection Mode of data collection by ADPC team was through a combination of desk and field surveys by a team of specialists. The survey team made an attempt to collect data directly from source agencies as much as possible but in certain cases relied on secondary data sources also. Some of the information has been obtained through meetings and interviews with appropriate personnel from the relevant technical agencies located in Bangkok, in the target provinces, cities as appropriate. It was felt important to share the objectives and the method adopted by the study team with source agencies concerned in order to provide a clear understanding on the study objectives, expected outputs etc. Study team was careful not to raise expectations unnecessarily on the final outcome and subsequent process. 11

26 ADPC team representatives participated in initial meetings between city level officials and TEI to reinforce team efforts as well as to have better coordination. Subsequently ADPC study team made several field visits to cities as needed to gather information. In addition, information was obtained thro web search and also study of references, project reports available elsewhere. One such source was ADPC and AIT libraries. ADPC has already conducted few projects in target cities and such study reports produced by ADPC were found to be useful. ADPC team had meetings for checking the availability and field verification of data. Meetings were held with individuals and groups from target cities, government agencies, professional bodies, universities, relevant NGOs and CBOs. 3.3 Steps used for delivery of final outputs The delivery of final outputs was carried out in several steps, as given below: i. Preliminary investigation Identification of partners, stakeholders and source agencies Establishment of survey teams and appraisal of methodology adopted ii. Conduct literature survey for collecting information on previous studies on Assessment of vulnerability to disaster events Assessment of vulnerability to Climate change targeting cities, provinces of Thailand iii. Participation in meetings organized to introduce the project objectives to target cities/districts City workshop in Bangkok organized by TEI Workshops organized in respective cities iv. Detailed analysis for development of climate risk profile Scenario buildings on potential Climate Change impacts and trends Qualitative and quantitative analysis of data availability Setting up a criteria for study using different indicators Analysis under 3 main indicators Prioritization of Cities based on the scoring as per the selected criteria. v. Collection of disaster related data for target cities and sector based vulnerability assessment Visit source agencies in Bangkok Visit source agencies in the provincial officers Develop building foot print maps Develop preliminary survey for analysis of spatial distribution of hazard types 12

27 Sector based vulnerability assessment in the field Capacity assessment for undertaking relevant projects by cities vi. Reporting and recommendation Reporting the preliminary assessments and recommendations Data presentation to the Advisory committee City level meeting to present the final assessment results Submission of reports to ACCCRN/RF 3.4 Detail explanation of study approach The objective of data collection was to get a clear understanding of the availability and accuracy of technical data required to conduct appropriate assessments under three categories for 5 target cities; i. Climate scenario assessment ii. Assessment of disaster impacts iii. Sector based vulnerability assessment and assessment of capacity of cities to undertake relevant projects The available technical data has been evaluated methodically for each of the five cities. The following data categories were used in data collection. 1) Geographical data; The locality of the city/ province in Thailand, physical features such as rivers, lagoons, water bodies, boundaries on Province, municipal area, Amp hoe, and Tambon 2) Building footprint maps produced by National Housing Authority 3) Infrastructure and utility data; - roads, water supply, transportation, 4) Land use planning; urban built up area, housing and buildings, productive sectors such as agriculture, tourism, industry 5) Meteorological data; Temperature, precipitation, wind parameters 6) Pollution data; air quality, surface water /ground water data 7) Disaster related information; losses, affected numbers, agricultural areas records 8) Health (event data): Seasonal disorders such as Malaria, Dengue, Chikungunya, Lepropitis Considering the urban Land use planning data, sub-indicators identified are: land uses over the past 20 years and existing land use projections; physical coverage of the different productive sectors; availability of land for new developments etc. In terms of disaster related information following data categories have been used; records on past disasters, past losses and damages. It was planned to collect such information over the past 25 years but later it 13

28 was found that the data is available only with DDPM (they started systematic collection and recording of data after establishment of the institution) and they can provide authentic data only for the years they have in their database. ADPC study team could acquire adequate information only for the past 5 years. The first above mentioned five categories have been presented as GIS maps and overlaid with hazard maps when available. The percentage of different building typologies has been analyzed to see what category of buildings is located in hazard prone areas for respective types of hazards. For Meteorological data, six sub-indicators have been identified and evaluated according to see the trends to project the future scenarios. They are: variations over annual mean temperature, variations over seasonal mean temperature (During hot weather season and cold weather season), and variations over extreme temperature (T max and T min), variations over frequency (Number of extreme cold/ warm days) Similarly, Precipitation data also categorized in to few sub parameters: variations in seasonal and annual mean precipitation, frequency on deficiency rain fall or drought, variation on the number of rainy days and variations over intense precipitation days (heavy, moderate, light). 3.5 Identification of source agencies The following technical source agencies and organisations were identified as potential data sources to obtain relevant data. Dept of Public Works and Town and Country Planning Dept of Natural Resources and Environment Geo- Informatics and Space Technology Development Agency (GISTDA) Thai Meteorological Department National Housing Authority Dept of Disaster Preparedness and Mitigation (DDPM) Pollution Control Dept Royal Thai Navy Irrigation Dept Dept of Mineral Resources; Mekong River Commission Ministry of Health ADPC had good working relationship with some agencies but with some other agencies ADPC team had to establish new partnerships or sign MOU to collect data. The procedural problems created some delays but all agencies were corporative and supportive. 14

29 3.6 Establishment of survey teams and conducting survey Survey team members were selected from in-house staff of ADPC and thro short term hire and survey teams were provided with a comprehensive awareness and training on conducting the desk survey and subsequent field verifications. Each study team was headed by a specialist and other members included were research assistants/coordinators. Appraisal on the indicators, data quality, quantity and manners to conduct a survey was arranged to foster a common framework among the survey team members. A Meteorology and air and water quality related desk studies were carried out initially by Research assistants to avail information on climate related parameters and to identify best sources. Subsequently, ADPC has employed subject specialists to verify the relevant information needed for the study (as there were several data sets obtained from different data collection centres) and to conduct the scenario assessment. 3.7 Analysis of data Gathered information and data were thoroughly examined by ADPC team with a broad focus on whether the city/province is prone to single hazard or multiple hazards; whether the Climate Change impacts at present are prominent or minor. More than one hazard will give more visibility and possibility for easy replication. i. Vulnerability to disasters During the process of analysing, ADPC has observed that floods. Landslides, droughts and cyclones are the recurring major natural disasters in the selected provinces. Information recorded are mainly from with details of the number of events, number of people affected, number of households affected, area of agriculture affected and the estimated losses. Although the information is available for damaged infrastructure, it was not possible to arrive at a qualitative or quantities assessment as the units measured were so broad. For example, the extent of roads damaged is indicated as a number which is difficult in evaluation as the category and the length of the road was not specified. In some cases data for flash floods and landslides were given as a combined loss. In the same way fire incidents have been recorded without identifying the same as a man-made event or natural event. How ever, ADPC team considers that the available data assessment is adequate for the phase 1. ii.climate change scenario study ADPC team was able to collect data for the last 29 years ( ) with details of precipitation and temperature as main parameters. For a comprehensive study, data were accessible and obtainable even to a level of details up to daily as well as monthly mean values. Accordingly, analysis for temperature variations for annual mean temperature, annual maximum and minimum temperatures, and monthly mean temperatures for cold weather season and hot weather seasons could be undertaken. 15

30 Similarly, precipitation data were also recorded and scrutinized for variations over average annual rain fall, heavy and very heavy rain fall intensities during monsoon seasons. 3.8 Scoring and methodology for prioritization Natural hazards occurrence and their past impacts within target urban areas were evaluated against several sectors taking in to consideration the natural hazard exposure levels. A matrix was created to evaluate and assign a score as per the degree of impact from respective hazard types. This approach has helped to identify and prioritize the cities in terms of impact from extreme events. The appraisal was on qualitative terms based on a comparative subjective assessment..for easy reference, a score of five (5) was assigned for a worst case and one (1) was for the least case. When data is not available, the score of zero was allocated. Similar approach was used for presentation of the results of Climate scenario study as well as sector based vulnerability assessment and study of data availability and to prioritize the cities for detail study under Phase 2. 16

31 4 Brief introduction to 5 selected cities 4.1 Chiang Rai Population : 141,291 Economy Role in the province : Agriculture, Trade : Administrative, Commercial and Educational Center Major Climate hazards and impacts : Floods, Landslide, Tropical storm; River erosion; : Water pollution Location Chiang Rai province is Thailand s northernmost province. Clipped to the north by the Mae Kok River, Chiang Rai city is 60 kilometers far from Thailand s northern border where the Mekong River skirts the boundaries of Thailand, Lao PDR and Myanmar. Muang Chiang Rai, the district capital of the province of the same name, approximately 785 km north of the nation s capital, Bangkok and located at N, Longitude E and with an elevation of 395m is included in the Lower Mekong basin with its boundary stretching to Lampang in the south, Phayao in the east and Chiang Mai in the west. The watershed area of the Mae Kok River is 7,895 square kilometers with an annual run-off of 5,119 million cubic meters. The general landscape consists of a large fertile plain, set within a midst of crisp and scenic mountain ranges. These form into a pan shape with elevations at approximately 580 m above sea level. Figure 4.1. Map of Chiang Rai district (Source: GISTDA) 17

32 4.1.2 Resources Formerly part of the Golden Triangle, the substitution program to replace opium production with tea, coffee and rice cropping has led to the increase of border trade and commerce. Thus the economy of the city relies mostly on agricultural resources, small business owners, especially with the extension of tourism. Although over 30% of the land area is officially classed as farmland, only about 19% is really considered suitable for cultivation and most of the cultivatable area is located along the Phaholyothin highway, which runs through the districts of Phan, Muang and Mae Chan and ends in Mae Sai. Moreover through the development of tourism and its associated increasing transport facilities, the city is gradually becoming a privileged gateway to reach China, Myanmar, Lao PDR, Vietnam and Cambodia. The city currently plays the role of a major transport hub in the whole region, using also the river as a transportation channel. These dynamics contribute to the urban extension of Muang Chiang Rai over the past years Climate Because of its higher elevations, the climate in Chiang Rai province is generally somewhat cooler when compared to the rest of the country. However, there are still three distinct seasons; the hot season, the rainy season and the cool season. Throughout the winter months, nighttime temperatures can drop considerably from the average daytime figures. At other times during the year, day and night temperatures do not vary significantly. The Cool Season lasts from late October until the end of February with temperatures ranging from 13 C to 28 C. The coldest months are December and January. The Hot Season begins at the end of March and lasts until the end of May, with temperatures ranging between 17 C and 36 C. The hottest month is April. In Chiang Rai, the monsoon or rainy season starts around May and ends in October - earlier than in Central Thailand. The average rainfall in Chiang Rai is considerably higher than its neighbor, Chiang Mai province. So much so that during the months of August and September, (when rainfall is heaviest), many of the streets throughout the province will flood. At most other times the rain will normally fall sporadically The hot season lasts from March to May with a daytime average temperature of 26 C. The rainy season actually presents two peaks: one in May-June (200mm average in one day) and one in August-September (up to 380mm average in one day). The average precipitation amount in a year is around 150 millimeters. The refreshing season starts in October and continues until the month of January. The average daytime temperature drops to 21 C during this period. The monthly mean data of temperature and rainfall over Chiang Rai during the period is used in the present analysis. The monthly mean data of maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (mean T), total rain, number of rainy days and maximum rain in 1 day is analyzed for 29 years from 1980 to 2009 to prepare the monthly normal. In addition, the highest Tmax and lowest Tmin in a given month are also considered to calculate the normal of these two parameters during the 29 years period 18

33 mentioned here. The normal of temperature parameters are shown in Figure 4.2 and normal rainfall parameters during this period is discussed in Figure 4.3. It is seen from Figure 4.2 that the peak summer is in April (about 35 C) with March to May as the hot weather season. The extreme Tmax normal is about 4 to 5 degree higher than that of normal Tmax during whole season (Figure 4.2a). Similarly extreme cold temperature reported during Dec to Feb (Figure 4.2b). There is not much variation in the mean temperature from April to October, 2009 (Figure 4.2c) The peak rainfall months and the observation of highest rainfall in a day (of the order to 6 cm/day) are reported mainly during July to September (Figure 4.3a&c). The number of rainy days is also highest in August followed by July, June, May, September and October (Figure 4.3b). 19

34 Figure 4.2. Normal monthly mean temperature over Chiang Rai from 1980 to (a) maximum temperature(tmax) and highest Tmax (Ext. Tmax), (b) same as a but for minimum temperature and (c) mean temperature (Source: Thailand Meteorological Dept.) 20

35 Figure 4.3. Normal monthly mean rain parameters over Chiang Rai from 1980 to (a) total rain (b) number of rainy days and (c) maximum rain in 1 day (Source: Thailand Meteorological Dept.) 21

36 4.1.4 Climate hazard and extreme events During the monsoon period, heavy rainfall trigger every year flooding of various intensity. The carriage way of the main river and associated drainage network is not sufficient to cope with the sudden amount of water. The water level thereby rises rapidly, leading to flooding and further erosion. Recently, in July 2000 massive floods, destroying the surrounding fields, affecting livelihood and leading to business interruption, overwhelmed the city. In 2006, flash floods occurred and affected the built-up environment as well as the utility and facility networks within the city. Transportation system was blocked and tourist activities ceased for various days. Loss of crop and economic breakdown led to migration wave to Bangkok. Water run-off is constantly increasing due to inadequate land-use planning coupled with increasing climate variability. Landslide and mudslide are substantial issues Chiang Rai has to face over the past decade. The topography of the zone associated with heavy rainfalls and unplanned human settlements, leads to increase the landslide risk and therefore the correlated damages on livelihoods, infrastructures and property. In fact, each year landslide occurs in the zone. For instance, in 2005, seven events have been reported in Chiang Rai province, affecting a total area of 800 square meters; and in 2007, four landslide events occurred, affecting 300 square meters. Tropical storms are highly frequent in Chiang Rai. Since the beginning of the eighties, the cyclone frequency tends to be accelerated. Strong winds, comprised between 63 km/h and 118 km/h and heavy rainfalls are associated to cyclone period. In recent times several ice rains and gale has been common phenomena. Drought is also of main concern in the province. In April 2008, a period of extreme drought hit the province. The Mekong River was very shallow, impeding the boat tour to work. According to TNA, 314,000 families in 18 districts have been hardly affected by water shortages. The lack of irrigation facilities for agriculture has led to the lost of the crops. In fact, more than 68,000 rai (27,700 acres) of agricultural lands have been damaged. The provincial authorities have declared the 18 districts of Chiang Rai as a drought ravaged area. 4.2 Udon Thani Population : 174,531 Economy : Agriculture, Trade, Industry Role in the province : Administrative, Commercial, Industrial and Educational Center Major Climate change issues : Flooding; Soil acidity and salinity; Tropical storms erosion, water shortage 22

37 4.2.1 Location In the northern part of the Isan region, Udon Thani is the capital (Amphoe Muang) of Udon Thani province (latitude 17 24'27''N and longitude '35''E) with its boundary stretching to Nong Khai in the north, Khon Kaen in the south, Sakon Nakhon in the east and Nong Bua Lamphu in the west. Located 60 kilometers away, from the Lao PDR border and the Nong Khai checkpoint, Muang Udon Thani forms a plateau, 187 meters above sea level. Muang Udon Thani is part of the Lower Mekong Basin. Three affluents of the Songkhram River, which is the third largest tributary of the Mekong, run through the city. The riverbanks are currently and increasingly endangered by human population growth and it s correlated increasingly with urbanization trends and associated activities. The erosion process is thus accelerated, with the risk of riverbank slope destabilization and river widening. Increasing human settlements nearby the canals amplify the potentiality of these areas to be badly affected in case of heavy rainfalls coupled with insufficient water retaining capacity. In fact, the river flows within concrete channels, which reduce the drainage Resources Figure 4.4. Map of Udon Thani district (Source: GISTDA) The city plays a major role as a regional and international transport hub as the gateway to Laos, North Vietnam and Southern China. Muang Udon Thani is thereby easily accessible from Bangkok by train or by plane or even by route. Furthermore the main agricultural productions of the region, such as sugarcane, rice straw, cassava, corns, converge to Muang 23

38 Udon Thani. The city is thus well known for being a primary resources market hub for neighboring provinces. Muang Udon Thani relies on agriculture as income generating primarily derives from local communities by rice farming, rising in wholesale and retail trading activities. Nevertheless most of the soils are sandy loams and loamy sands, which are very low in fertility, very low in water holding capacity, often highly acidic and low in their organic matter content. No efficient irrigation system has been so far developed in the zone. Weather forecast is thereby of primary importance for crop production and the necessary potential adaptation towards possible changes. Large-scale industries include sugar, jute, cassava and rice mills are located in Udon Thani. Small-scale industries such as cotton, silk and mat weaving have also brought revenue to the city. Meanwhile, Udon Thani is part of the northeast region of Thailand, which is the most deprived region economically, with per capita average income less than 40% of the national average. The trend of Udon Thani s urbanization is rapid and mostly unplanned. The city encompasses four reservoirs, two of them in the direct urban environment. These reservoirs are of important use for the whole region as they provide water supply for public, cattle and agriculture purposes. Meanwhile the gravity of the July 2000 flooding was increased by the overflow of two reservoirs. In fact, water shortage has become a pressing issue as the water supply encounters difficulties to meet the increasing demand. This might have some negative repercussions over agricultural business and could trigger food shortage within the city but also at the regional scale Climate Udon Thani climate is tropical savanna and can be divided into three main seasons. The hot season is running from March to May with temperatures comprised between 24 C and 36 C. Rainfalls start to me more frequent as the hot season moves forward, leading to a very high humidity rate in May. The monsoon then starts in June and lasts until October, characterized with two peaks, one in June (230mm for the highest average record) and the other one in August (280 mm for the highest average record). Then the cool season runs from November to February with a 15 C to 30 C temperature range. Therefore temperatures range from 16 C to 36 C with January as the coldest month; and precipitation varies from 6.0 to mm per month with the heaviest rainfalls during the month of August. The monthly mean data of maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (mean T), total rain, number of rainy days and maximum rain in 1 day is alalysed for 29 years from 1980 to 2009 to prepare the monthly normal. In addition, the highest Tmax and lowest Tmin in a given month is also considered to calculate the normal of these two parameters during the 29 years period mentioned here. The 29 years normal of temperature parameters are shown in Figure 4.5 and normal rainfall parameters during this period is discussed in Figure

39 It is seen from Figure 4.5 that the peak summer is in April (about 36 0 C) with March to May as the hot weather season. The extreme Tmax normal is about 4 to 5 degree higher than that of normal Tmax during whole season (Figure 4.5a) and the peak values in hot weather season is about 2 0 C higher that the corresponding values of Chiang Rai as shown in Figure 4.2a. Similarly extreme cold temperature reported during Dec to Feb (Figure 4.5b). The extreme Tmin during winter is slightly higher compared to that of Chiang Rai values as shown in Fig. 2b. There is not much variation in the mean temperature from April to October, 2009 (Figure 4.5c). The peak rainfall months and the observation of highest rainfall in a day (of the order to 6 to 7 cm/day) are reported mainly during May to September with peak during August (Figure 4.6a&c). Number of rainy days is also highest in August followed by July, June, May, September and October (Figure 4.6). 25

40 Figure 4.5. Normal monthly mean temperature over Udon Thani from 1980 to (a) maximum temperature(tmax) and highest Tmax (Ext. Tmax), (b) same as (a) but for minimum temperature and (c) Mean temperature (Source: Thailand Meteorological Dept.) 26

41 Figure 4.6. Normal monthly mean rain parameters over Udon Thani from 1980 to (a) total rain (b) number of rainy days and (c) maximum rain in 1 day (Source: Thailand Meteorological Dept.) Climate hazard and extreme events Muang Udon Thani is no exception concerning climate change effects. The city has to cope with climate unpredictability comprising unseasonable and intense weather events. In July 2000, the highest record of rain for the whole province fell over the city and led to massive floods, causing two fatalities and interruption of all activities for several days. In August, 2001 torrential monsoon rainfalls for more than two weeks, triggered many fatalities and 27

42 displaced thousands. These massive climatic events meant to occur more frequently, unhinge the normal course of activities on the middle term and can foster new type of vulnerabilities and increase the existing one, if adaptation initiatives are not developed. Every one to two years, Udon Thani is issuing tropical storm warning, which originates over South China Sea during the months of May to October (see Table 1). Cyclones in the area trigger wind comprised between 63km/h and 118 km/h and high levels of rainfall. Largescale industries of the region include sugar mills are affected. Between January and July 2009, 2 tropical storms were reported by the Department of Disaster Preparedness and Mitigation (DDPM) of Udon Thani. 1,404 people and an overall of 434 households have been affected, leading to an economic loss of 4,236,290 Bahts. 4.3 Hat Yai Population : 53,638 Economy Role in the province Major Climate hazards : Trade, tourism : Commercial and Tourism Center : Flash floods; Droughts; Water shortage; Pollution during floods; Slope destabilization Location Located 50 kilometers from the Malaysian border at longitude ' 55" E and latitude 06 55' 46" N, 92 feet (28 m) above sea level, Hat Yai Municipality is the second most important city of Songkhla Province, forming the urban corridor known as the Greater Hat Yai- Songkhla Metropolitan Area. It has become a very popular tourist centre for Malaysian and Singaporean visitors. Songkhla Province shares its western boundary with Satun Province; Phatthalung lies north; Pattani and Yala south. Hat Yai Municipality is low-lying, sitting at the base of a roughly circular valley. Located in the downstream area of the Khong U-Taphao Basin, the Utaphao River flows through the heart of the city, often in concrete channels that provide limited drainage. The Utaphao River rises at Sadao, on the border with Malaysia and flows to Songkhla lake, a coastal lagoon just downstream of Hat Yai that is hydraulically connected to the Gulf of Thailand. 28

43 Figure 4.7. Map of Hat Yai district (Source: GISTDA) Resources As the centre of commercial trade and administration in Southern Thailand, Hat Yai is a bustling modern city, which concentrates increasing commercial and touristic activities. The city is also a major transportation hub with an international airport located in the suburbs of the city and other inner city transportation facilities as its geographical location makes it a gateway to the major neighboring countries of Malaysia and Singapore, and is thus a city with high tourism potential for domestic and foreign tourists who visit year-round Climate Hat Yai benefits from an equatorial climate. Temperatures range from 17 C to 39 C over the year, with a daily average of 26.8 C. The number of rainy days per month in a year is with an annual rainfall amount of 2 meters, with a peak during the months of May (161.7mm in a month) and November (318.1mm). Hat Yai only has two seasons; wet and dry. The wet season, influenced by monsoon and rainstorms, starts in May and ends in the month of December. Usually in November, heavy rainfall beat down on the city with sometimes twenty-two days of continuous rain leading to more than 500 mm of precipitation. The dry season lasts four months, January to April with average highest temperature of 33 C. 29

44 The monthly mean data of maximum temperature (Tmax) and minimum temperature (Tmin) obtained from Thai Met Department is shown in Figure 4.8. Similarly the normal monthly total rain obtained from 29 years (1980 to 2009) is shown in Figure 4.9. As seen from these figures the hottest month is April and the coldest month is January and is slightly similar to the condition over Phuket as shown in Figure But with respect to normal rainfall the pattern is slightly different over Phuket with peak rainfall varies from September to December (Figure 4.9) with highest in the month of November. Another peak is in the month of May. Figure 4.8. Normal monthly mean temperature over Hat Yai from 1980 to 2008 (Source: Thailand Meteorological Dept.) Figure 4.9. Monthly normal rainfall over Hat Yai (mm) from 1980 to 2008 (Source: Thailand Meteorological Dept.) 30

45 4.3.4 Climate hazard and extreme events Due to its geographical characteristics and to unplanned urbanization and deforestation in upstream areas, Hat Yai Municipality has become extremely vulnerable to flood disasters. With its population density and as a commercial center, the municipality has characteristics that can magnify the impact of flooding to which it is prone. Hat Yai Municipality is thus prone to inundation due to its hydraulic system combined with heavy annual rainfalls and rapid unplanned urbanization. In fact the river suffers from regular flash flooding during the monsoon season. Serious flooding events occurred in 1988 and again in Triggered by torrential rains, the flooding of November 2000 has been described as one of the worst natural disasters in the history of urban Thailand (Charlchai et. al., 2004). Flood depths of two to three meters height caused 40 fatalities, thousands of injuries and severe damages to property, livelihood, and lifelines, affecting drastically the economy of the city. More recently, in 2006 flooding also affected more than 200,000 people and paralyzed the city for various days. During the period the total amount of loss reached 23,194,466 Bahts with 290 transportation infrastructures affected and 3,792 Rai of agricultural lands damaged. Drought is also a substantial problem in the zone. This issue affected 2,137 people i.e. 613 households between 2005 and Phuket Population Economy Role in the province : 29,227 (Muang Phuket), 18,547 (Patong) : Tourism, Service : Touristic Center Major Climate change issues: Flood, Landslide, Sea level rise, Storm surge, Tsunami, Water shortage Location Phuket covers a total area of 543 km2, which comprises of Phuket Island and 32 nearby islands. Located 862 kilometers south of Bangkok, in the Andaman Sea, the main island is connected to the mainland by the older Sarasin Bridge and the newer Thep Krasattri Bridge. The two bridges running side-by-side spans over the Pak Prah strait. On the north of Phuket province lies Phang Nga Province, and on the Eastern side, Krabi Province lies on the other side of Phang Nga s sea. Phuket island is constituted at 70% of mountainous areas and 30% of plain areas mostly located in the central and eastern parts of the island. Phuket city is spreading from the coastline to the upper hill, with an elevation from 0 to 10 meters. The municipality covers the 31

46 subdistricts of Talad Yai and Talad Nuea. Patong city is on the Andaman coastline, characterized by a massive tourist industry attracted by its seashore and the development of numerous and unplanned human settlements in the toe of the mountains. Figure Map of Phuket Province (Source: GISTDA) Resources Phuket formerly derived its wealth from tin and rubber. The island was on one of the major trading routes between India and China, and was frequently mentioned in foreign trader s ship logs. The region now derives much of its income from tourism. The tourism service industries, such as lodging, restaurant, transportation and tourism commerce are clearly the most important sources of income in Phuket. In million tourists came to the island, generating revenue of 72,599 million Bahts. Patong area attracts the highest number of visitors. In fact Phuket accounts for 30% of the national tourism revenue. Following the service sector, the commercial and agricultural activities are also important economic sectors (Table 4.1). 32

47 Table 4.1. Income of Phuket (Department of Provincial Administration) Agriculture 4,886 4,945 5,529 5,788 Agriculture, Hunting and Forestry 1,642 1,947 2,402 2,537 Fishing 3,244 2,998 3,127 3,251 Non-Agriculture 50,076 45,427 51,599 56,268 Mining and Quarrying Manufacturing 2,037 2,271 2,394 2,556 Electricity, Gas and Water Supply 1,355 1,296 1,460 1,574 Construction 2,457 2,925 2,927 2,999 Wholesale and Retail Trade; Repair of Motor Vehicles, Motorcycles and Personal and Household Goods 4,603 5,089 6,043 6,275 Hotels and Restaurants 25,785 20,766 22,000 23,880 Transport, Storage and Communications 6,614 5,174 7,887 9,173 Financial Intermediation 1,459 1,660 1,924 2,176 Real Estate, Renting and Business Activities 1,424 1,516 1,713 1,923 Public Administration and Defence; Compulsory Social Security 1,155 1,227 1,306 1,432 Education 993 1,172 1,519 1,673 Health and Social Work ,127 Other Community, Social and Personal Services Activities 1,318 1,359 1,388 1,430 Private Households with Employed Persons Gross Provincial Product (GPP) 54,962 50,371 57,128 62,055 GPP Per capita (Baht) 201, , , ,621 Population (1,000 persons) Climate Phuket climate is characterized by two seasons. The hot season starts in December and ends in March, with a daily mean temperature average of 28.4 C and 40mm monthly average of rainfall amount. The rainy season begins in April and lasts until November, with rainfall peaks in May (up to 320mm) and September (up to 400mm). During this season the temperature is comprised between 32 C for the highest and 23.8 C for the minimum. The daily average temperature during the year is comprised between 23 C and 34 C. 33

48 The monthly normal as calculated from the monthly mean of different temperatures during the period from 1980 to 2008 is given in Figure Being a coastal station the minimum temperature is slightly higher compared to that of northern stations (particularly in winter). Figure Monthly mean normal of temperature; Tmax, Tmin, mean Temperature, Ext. Tmax and Ext. Tmin obtained from the data 1980 to 2008 over Phuket (Source: Thailand Meteorological Dept.) With respect to monthly normal rainfall it is found that September and October are the peak months followed by August, May, July and June Figure 4.12a. The peak no. of rainy days and the observation of highest rainfall in a day (more than 7 cm/day) is reported mainly during September and October (Figure 4.12a&c). 34

49 Figure Normal monthly mean rain parameters over Phuket from 1980 to (a) total rain (b) number of rainy days and (c) maximum rain in 1 day (Source: Thailand Meteorological Dept.) 35

50 4.4.4 Climate hazard and extreme events The coastline of the island is continuously exposed to sea erosion and has to cope with sudden and disastrous events, such as tsunami tidal wave. The 26 December 2004 the earthquake in the Sumatra Island created a massive tsunami tidal wave, which devastated the Andaman Coast. Phuket suffered from disastrous loss of lives, assets and natural resources. 13,065 people died or disappeared during the event; 402 residences were totally destroyed; 550 partially. The utility and facility systems of the island were heavily damaged. In total the overall damages cost more than 13, million Bahts (Strategy for Provincial Development Unit, Phuket Governor s Office and National Economic and Social Development Board). Strategic plan has been developed to curb the potential impacts of such disasters. Phuket is also very much exposed to irreversible damages on its coral reefs due to high concentration of carbon dioxide emissions in the atmosphere that tends to increase the sea temperature. Reef-building corals are a part of a rich ecosystem that provides resources for the coastal populations. They also serve as buffer against strong waves that erode coastlines during storms. Currently the coral cover is declining at the rate of one to two per cent annually due to destructive fishing, tourism, sedimentation caused by coastal development, eutrophication due to untreated water run-off, dredging and climate change. According to Phuket Marine Biological Centre (PMBC), Phuket coastline is seriously endangered by all these interlinked dynamics. According to the Thailand Meteorological Department, the southern part of Thailand is relatively exposed to high risk of tropical storms and typhoon. On top of high-speed winds that can damage the infrastructure, heavy rainfall due to the topography of the area can lead to flooding and contribute to destabilize the slopes. In fact one of the disasters Phuket has to increasingly cope with is landslide occurrence. Uncontrolled human settlements help weaken the slopes and heavy rainfalls help trigger landslides in the zone. The tropical climate participates thereby to the instability of the slopes and as climate change interacts with rainfall events, triggering more intense and more frequent rain amount, landslides are meant to occur and affect more people more frequently. Surrounded by mountains Patong area is especially prone to landslide as about 20% of the area has high to moderate susceptibility to landslide. The area is heavily prone to risk; first the populations living in the toe of the mountain are located within the landslide prone area, while the populations living in the plain area are exposed to flood risk. Adaptation project towards landslide risk mitigation has started to be implemented in the zone. 4.5 Samut Sakhon Population : 176,423 Economy Role in the province : Fishery, Industry : Trade, fishery and agricultural center 36

51 Major Climate change issues : Flood, Land subsidence, Salt intrusion, Air pollution, Water shortage, Coastal erosion Location Muang Samut Sakhon is located at latitude N and longitude E at the mouth of the Tha Chin River, which flows into the Gulf of Thailand as one of the distributaries of the Chao Praya River. The municipality is situated 30 kilometers from Bangkok and shares its western provincial border with Samut Songkhram; its northern one with Nakhon Pathom; and Eastern one with Bangkok. Muang Samut Sakhon covers three subdistricts, namely Tha Calom, Krokkrak and Maha Chai, with respectively 9,865 5,262 and 40,250inhabitants. Figure Map of Samut Sakhon Provice (Source: GISTDA) Resources The economy of Samut Sakhon mostly relies on fishery, as the city is one of the major fishing ports in the zone. The production of brine salt also provides substantial incomes to the region, thanks to the coastal location of the municipality. Industrial development has increased drastically for the past decade. Currently 4,000 industries are settled in the zone. The associated pumping of groundwater resources has led to land subsidence and the constant degradation of the aquifer. 37

52 4.5.3 Climate With respect to the climate of Samut Sakhorn, it is situated in the central Thailand. The Central region's climate is influenced by the southwest monsoon winds and sea breezes. The mountains of the north and the northern part of the Central region reduce the northeast monsoon winds' influence. Similarly the annual average temperature is 28 0 C, the average highest temperature being 330C, and the average lowest temperature being 20 0 C. Muang Samut Sakhon has 3 seasons, the rainy season, from June to October, when the southwest monsoon winds and depression storms exert their influence, winter, from November to January, when the northeast monsoon winds exert their reduced influence and thus is not as cold as the winter of the North or Northeast, and summer, from February to May, which is less hot than the summer of the North or Northeast due to the influence of the ocean and the trade winds from the ocean between February and April. The average rainfall of the city is 1,120 mm/year Climate hazard and extreme events The city lies only 1 to 2 meters above the mean sea level. Flood is thus a frequent issue the municipality has to cope with, even if the municipal record doesn t reveal much on the topic. Nevertheless coastlines are facing more and more recurrently coastal erosion and rising sea levels causing land subsidence and human migration. The causes are mostly man-made, such as sand mining, construction of industrial estates along the coastline, sedimentation coming from coastal development and groundwater drainage. During the last decade, the erosion process is faster than forecasted. Bangkok, Samut Songkhram, Samut Sakhon, Samut Prakan and Chachoengsao provinces are suffering severe erosion according to Master Plan on Coastal Erosion Management for the Upper Gulf of Thailand, published in September by the Thammasat University Research and Consultancy Institute, which studied the coastline covering 100km of shoreline from the mouth of the Mae Klong river in Samut Songkhram to the mouth of the Bang Pakong river in Chachoengsao. Some 2,667 hectares of this coastline was washed away in the 54 years from 1952 to The problem is severe and the rate of erosion is increasing. Local communities are suffering economic damage estimated at more than 100 million baht a year, according to the institute's report. Another simulation indicates that without intervention, in 20 years coastlines will retreat inland by 1.3 km as they are eroded away (DMRC report). The intrusion of salt water into productive land areas and drinking water supply is a substantial risk in the area as the agricultural production such as rice straw and coconut would be destroyed, affecting then durably the local livelihood. 38

53 4.6 Comparative assessment of Air and Water Quality in Five cities Environmental degradation is a serious issue to be addressed as it is observed to be deteriorating over time. Air pollution and water pollution are directly affected the human beings causing prolonged illnesses in the reciprocating system and vector borne diseases such as dengue fever and malaria. The air quality is progressively worsening in the urban areas. The concentration of ozone has particularly increased since the year Although the Particulate Matter (PM10) concentration is varying a lot, some days have been recorded above standards over the past 10 years. In Chiang Rai, the number of days with exceeding standards for ozone indicator is increasing, in spite that the measurement stations were established only a few years ago. The direct consequence of high rate of low-level ozone is the formation of smog. Furthermore, the number of days with PM10 exceeding standard is also increasing, deepening the risk of respiratory diseases such as lung cancer. (See Figure Figure 4.16). Figure Particulate matters.pm10 concentration in urban areas from 1997 to 2008 (Source: Thailand Pollution Control Dept.) 39

54 Figure O3 Low-Ozone concentration in urban areas from 1997 to 2009 (Source: Thailand Pollution Control Dept.) Figure SO2- Sulfur Dioxide concentration in urban areas from 1997 to 2009 (Source: Thailand Pollution Control Dept.) The urbanization trend of Hat Yai is rapid since the past decades. Due to the increasing demand on development and settlement, urban areas have encroached into hazard prone areas. In the direct surroundings of the municipality, the constant human settlement expansion in four township municipalities is quite noticeable. The environmental degradation characterized by high peak of air and water pollution is deepening. The high concentration of Particulate matters PM10, from man-made origin such as the burning of fossil fuels, power plants and industrial process, deteriorates the quality of air in the city, increasing health hazards. In July 2002 and in February 2003 several consecutive days were categorized as unhealthful air quality period, with some days considered as very unhealthful. 40

55 For Samut Sakhon, in relation to industrial development, the pollution rate concerning water and air quality has been in the increase. Several days per year the air quality index shows high values, highlighting the unhealthful state of the air. The year 2003 especially the month of November recorded more than a week with unhealthful air quality. Industries also generate wastewater, around 68,000 m 3 per day, which highly contribute to pollute the water and groundwater bodies. Furthermore Samut Sakhon generates 700 tones of solid waste per day, of which 400 tones comes from within the municipality and the other 300 from the outside. 41

56 5 Climate scenario and observed trends in 5 cities Climate change is manifested by a rapid rise in temperatures all over the world. Only 30 years ago scientists were warning that global warming would change precipitation patterns significantly, with heavy rainfall in some areas while others would be very dry. Extreme weather conditions such as storms, floods, droughts and heat waves would become more intense and more frequent, and sea levels would rise, the scientists warned. These changes can already be observed, according to the report East Asia Environment Monitor 2007: Adapting to Climate Change, published by the World Bank. "In the last few years there have been widespread changes in extreme temperatures, droughts have become longer and more intense, the frequency of heavy precipitation has increased over most land areas, and arctic sea ice has shrunk by 2.7 per cent per decade, resulting in a rise in sea level that is now beginning to submerge small island countries like Kiribati and Nauru in the South Pacific," the report said. Thailand has 2,880km of coastline along 136 districts in 23 provinces, thus it is extremely vulnerable to sea level rises due to climate change. A one-meter rise will not only sink Bangkok and low-lying areas, resulting in destruction of infrastructure, loss of beaches and irreversible damage to coastal ecosystems like mangrove forests and coral reefs, but also cause land subsidence and coastal erosion. In recent times due to increase of urban population in Thailand in conjunction with the impact of climate change, the cities are becoming more vulnerable towards disasters. Now, the cities are responsible for managing their growth and prepare the community for consequences of climate change and vulnerabilities. As the five sites of Thailand chosen for this project are under the influence of various disasters such as flooding, heavy rainfall spell, drought, storm surge, tsunami, sea level rise etc., it will be essential to analyze the past data over these five sites of Thailand. This will facilitate to identify options for integrating climate change adaptations in the governance process considering pre identified indicators for modifications to built environment. These urban areas experience frequent occurrences of hydro-meteorological disaster events with direct and indirect losses of social and economic nature. Preliminary studies in the Phase 1 concerning the changes in climate trends will be useful for city governing bodies and provincial authorities to initiate productive actions leading to long term solutions, local level adaptation options and identifying gaps. Under the study, the following activities were carried out. Assessment of the status of impacts of climate change in five selected cities Evaluation of data availability for study on previous events and trends as well as for study of potential exposures to future climate change scenarios Identification of source agencies and data providers, availability of essential data Search for information gaps, outlining the areas for further qualitative and quantitative assessment 42

57 Identification of the sources of most useful information for developing strategy for facing future challenges on climate change impacts Collect information on relevant studies carried out previously by national or international agencies 5.1 Change of precipitation pattern Chiang Rai Change in annual mean temperatures and annual rainfall From the 29 year monthly mean temperature and precipitation data, it is found that the annual mean temperature and annual total rainfall over Chiang Rai shows increasing trend (Figure 5.1). The annual normal mean temperature is found to be 25 0 C during this period and annual normal mean rainfall is found to be cm with a standard deviation of 13.8%. With respect to these values the number of cases with more (less) than normal mean temperature and normal rainfall during first 14 years and second 15 years are given in Table 5.1. The lowest rainfall recorded during the El Nino year of 1987 and highest rainfall during Tota l R a infa ll (c m ) Annual Total Rain Annual Mean T Linear (Annual Total Rain) Linear (Annual Mean T) Mean Temperature (deg C) Year Figure 5.1. Annual mean temperature & yearly total rainfall over Chiang Rai (Source: Thailand Meteorological Dept. and Analysis)

58 Table 5.1. Annual mean temperature and rainfall comparison during two periods over Chiang Rai; and (Source: Thailand Meteorological Dept. and Analysis) Periods Annual mean temperature Annual total rainfall More than mean (25 0 C) Less than mean (25 0 C) More than Mean (169.4 cm) Less than mean (169.4 cm) (14) (15) Table 1 indicates that the rapid increasing trend of the number of years with more than annual mean temperature and a similar rapid decrease of years with less than annual mean. Regarding the rain fall, no significant difference is noted between higher and lower rainfall years in the period 1994 to Changes in rainfall intensity and rainy days From the amount of daily rainfall data different type of rainfall days are identified viz., rainy days (if rain amount > 0.1 mm), light rain days (if the amount is from 0.1 to 10 mm), moderate rain days (if the amount is from 10.1 to 35 mm) and heavy (if the amount is from 35.1 to 90 mm) and very heavy rain days (if the amount is >90 mm). This is the same classification used by Thailand Meteorological Department (TMD). The time series of seasonal frequency (April-May, Oct-Nov and June-September; JJAS) of these data during past 29 years over Chiang Rai is shown infigure 5.2, Figure 5.3, and Figure 5.4 respectively. It is seen from Figure 5.2 that slight increasing trend of rainy days (Figure 5.2a) and days with heavy or very heavy rainfall days (Rain > 35 mm/day) are reported during April-May (Figure 5.2d) Increasing frequency of heavy or very heavy rainfall events can cause more flooding and also more threat to disaster. During October-November except heavy to very heavy rainfall events (Figure 5.3d) all other shows decreasing trend, whereas during October- November it shows slight increasing trend. During the monsoon season from June to September, the frequency of heavy to very heavy rainfall event is increasing with peak value reported during It may be mentioned that 2006, flood condition was very worst during August (Figure 5.4d). 44

59 Figure 5.2. Frequency of rainy days & different rainy days over Chiang Rai in Apr-May (Source: Thailand Meteorological Dept. and Analysis) 45

60 Figure 5.3. Frequency of rainy days & different rainy days over Chiang Rai in Oct-Nov (Source: Thailand Meteorological Dept. and Analysis) 46

61 Figure 5.4. Frequency of rainy days & different rainy days over Chiang Rai in JJAS (Source: Thailand Meteorological Dept. and Analysis) 47

62 5.1.2 Udon Thani Change in annual mean temperatures and annual rainfall From the 29 year monthly mean temperature and precipitation data, it is found that the annual mean temperature and annual total rainfall over Udon Thani shows increasing trend (Figure 5.5). Figure 5.5 indicates that the year 1998 was the warmest year over Udon Thani during this period. The annual normal mean temperature is found to be 27 0 C during this period and annual normal mean rainfall is found to be 142 cm with a standard deviation of mm (19.1%). Thus, the mean temperature is about 2 degree higher than that of Chiang Rai and the mean rainfall is less than that of Chiang Rai value, however, the standard deviation of rainfall is slightly higher. With respect to these values the number of cases with more (less) than normal mean temperature and more (less) than normal rainfall during first 14 years and second 15 years are given in Table 5.2. The lowest rainfall recorded during Total Rainfall (cm) Annual Total Rain Annual Mean T Linear (Annual Total Rain) Linear (Annual Mean T) Mean Temperature (deg C) Year Figure 5.5. Annual mean temperature & yearly total rainfall over Udon Thani (Source: Thailand Meteorological Dept. and Analysis) Table 5.2. Annual mean temperature and rainfall comparison during two periods over Udon Thani; and (Source: Thailand Meteorological Dept. and Analysis) Periods Annual mean temperature Annual total rainfall More than 27 0 C Less than 27 0 C More than 142 cm Less than 142 cm (14) (15) Table 5.2 indicates that the increasing trend of annual mean temperature has caused many variations of higher mean temperature during recent years compared to earlier period. 48

63 Similarly, in case of rainfall also there is a slight increasing trend of total rainfall more number of years with higher than the normal rainfall during recent year (1994 to 2008) Changes in rainfall intensity and rainy days The linear trend analysis of rainy days and higher than heavy rainfall days indicates increasing trend during April-May (Figure 5.6). It is also seen from Figure 5.7 and Figure 5.8 that the frequency of heavy rainfall events is increasing during October-November as well as during June-September. Figure 5.6. Frequency of rainy days & higher than heavy rainfall days over Udon Thani during April- May(Source: Thailand Meteorological Dept. and Analysis) 49

64 The rainy days also increasing during monsoon season from June to September (Figure 5.8a), whereas it is slightly decreasing during Oct-Nov (Figure 5.7a). The increase of heavy to very heavy rainfall events during all the three seasons indicates increasing potential of flood. Figure 5.7. Frequency of rainy days & higher than heavy rainfall days but for Oct-Nov over Udon Thani (Source: Thailand Meteorological Dept. and Analysis) 50

65 Figure 5.8. Frequency of rainy days & higher than heavy rainfall days for June-September over Udon Thani (Source: Thailand Meteorological Dept. and Analysis) Hat Yai Change in annual mean temperatures and annual rainfall From the 29 year monthly mean temperature and precipitation data, it is found that the annual rainfall over Hat Yai shows increasing trend (Figure 5.9). Figure 5.9 indicates that the year 1998 was the warmest year over Hat Yai during this period. The annual normal mean temperature is found to be C during this period, which is higher than that of Chiang Rai and almost close to that of Phuket. The annual mean temperature is almost flat with slight increasing tendency. The annual normal mean rainfall is found to be 171cm with a standard deviation of 18.7%. With respect to these values the number of cases with more (less) than normal mean temperature and normal rainfall during first 14 years and second 15 years are given in Table 5.3. The lowest rainfall recorded during 1990 and highest rainfall recorded during 2000, which was one of the flood year faced by Hat Yai. 51

66 Total Rainfall (cm) Annual Total Rain (cm) Annual Mean T Linear (Annual Total Rain (cm)) Linear (Annual Mean T) Mean Temperature (deg C) Year Figure 5.9. Annual mean temperature & yearly total rainfall over Hat Yai (Source: Thailand Meteorological Dept. and Analysis) Table 5.3. Annual mean temperature and rainfall comparison during two periods over Hat Yai; and (Source: Thailand Meteorological Dept. and Analysis) Periods (14) (15) Annual mean temperature More than (mean) C Less than (mean) C Annual total rainfall More than (mean)171 cm Less than (mean)171 cm Table 5.3 indicates that the slight increasing trend of number of years of more than annual mean temperature and a decrease of years with less than annual mean temperature, In case of rainfall, because of the increasing trend of the total rainfall, the number of years with more than normal rainfall during the recent period (1994 to 2008) is 10, which is twice that of number of years with less than normal values Changes in rainfall intensity and rainy days Since the peak rainfall months over Hat Yai are from Oct to Dec, the monthly rainfall during these months is plotted in Figure It is seen that there are individual peaks reported particularly, during October and November, during many years. However, the trends are not 52

67 increasing. The peak rainfall during November 2000 as shown in Figure 5.10 is one of the reason of severe flood over Hat Yai OCT NOV DEC Linear (NOV) y = x R 2 = Total Rainfall (mm) Year Figure Monthly rainfall over Hat Yai during the peak monsoon months of October- December during the period from (Source: Thailand Meteorological Dept. and Analysis) With respect to the change in frequency of rainy days and the heavy to very heavy rainfall days the seasonal frequency during three seasons viz., April-May, October-November and June-September is shown in Figure 5.11, Figure 5.12, and Figure 5.13 respectively. It is seen from Figure 5.11 that the frequency of rainy days and that of heavy to very heavy rainfall days are in decreasing trend during April-May. During Oct-Nov the frequency of heavy to very heavy rainfall events are increasing (Figure 5.12b) with slight decrease of rainy days (Figure 5.12a). During the monsoon season, almost both the frequency of rainy days and the heavy to very heavy rainfall days almost flat (Figure 5.13). 53

68 Figure Frequency of rainy days & heavy rainy days over Hat Yai in Apr-May (Source: Thailand Meteorological Dept. and Analysis) 54

69 Figure Frequency of rainy days & heavy rainy days over Hat Yai in Oct-Nov (Source: Thailand Meteorological Dept. and Analysis) 55

70 Figure Frequency of rainy days & heavy rainy days over Hat Yai in June-September (Source: Thailand Meteorological Dept. and Analysis) Phuket Change in annual mean temperatures and annual rainfall From the 29 year monthly mean temperature and precipitation data, it is found that the annual mean temperature over Phuket shows increasing trend (Figure 5.14) whereas the mean rainfall shows decreasing trend. Figure 5.14 indicates that the year 1998 was the warmest year over Phuket during this period. The annual normal mean temperature is found to be C during this period, which is higher than that of Chiang Rai and Udon Thani. The annual normal mean rainfall is found to be 222 cm with a standard deviation of 17%. With respect to these values the number of cases with more (less) than normal mean temperature and more (less) than normal rainfall during first 14 years and second 15 years are given in Table 5.4. The lowest rainfall was recorded during 1992 and highest rainfall was recorded during

71 Total Rainfall (cm) Annual Total Rain Annual Mean T Linear (Annual Total Rain) Linear (Annual Mean T) Mean Temperature (deg C) Year Figure Annual mean temperature & yearly total rainfall over Phuket (Source: Thailand Meteorological Dept. and Analysis) Table 5.4. Annual mean temperature and rainfall comparison during two periods over Phuket; and (Source: Thailand Meteorological Dept. and Analysis) Periods Annual mean temperature Annual total rainfall More than C Less than C More than 222 cm Less than 222 cm (14) (15) Table 5.4 indicates that the increasing trend of the number of years with more than annual mean temperature and a decrease of years with less than annual mean temperature. In case of rainfall, just the opposite has happened because of the decreasing trend of number of years of more than annual total rainfall. The number of years with less than normal rainfall during recent year (1994 to 2008) is increased. The increasing mean temperature is also indicating climate change Changes in rainfall intensity and rainy days The linear trend analysis of rainy days over Phuket during April-May shows decreasing trend and higher than heavy rainfall days is almost flat (slight decreasing tendency) with isolated peaks during 1985 and 2007 (Figure 5.15). It is also seen from Figure 5.16 and Figure 5.17 that the frequency of heavy rainfall events is increasing during June-September and slight increasing trend during October-November (Figure 5.16b & Figure 5.17b). The frequency of 57

72 rainy days is increasing during monsoon season from June to September (Figure 5.17a) and during Oct-Nov it is slightly decreasing (Figure 5.16a). Figure Frequency of rainy days & higher than heavy rainfall days over Phuket during April-May (Source: Thailand Meteorological Dept. and Analysis) 58

73 Figure Frequency of rainy days & higher than heavy rainfall days for October-November (Phuket) (Source: Thailand Meteorological Dept. and Analysis) 59

74 Figure Frequency of rainy days & higher than heavy rainfall days for June-September (Phuket) (Source: Thailand Meteorological Dept. and Analysis) Samut Sakhon The daily rainfall data over Samut Sakhon during the period of shows a decreasing tendency of rainy days and extreme days (Figure 5.18). 60

75 Figure Frequency of annual rainy days and other rain days over Samut Sakhon (Source: Thailand Meteorological Dept. and Analysis) 61

76 5.2 Change in temperature pattern Chiang Rai The monthly variation of Tmax, Tmin and mean T during hot weather season (March to May) and cold weather season (Dec to Feb) is shown in Figure 5.19 and Figure 5.20 respectively for Chiang Rai. Figure Monthly mean temperature variation during hot weather season (March to May) from 1980 to 2008 over Chiang Rai. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for April is plotted (Source: Thailand Meteorological Dept. and Analysis) 62

77 Figure Monthly mean temperature variation during cold weather season (December to February) from 1980 to 2008 over Chiang Rai. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for December is plotted (Source: Thailand Meteorological Dept. and Analysis) 63

78 It is seen from Figure 5.19 and Figure 5.20 that the maximum temperature in summer (March to May) is decreasing but the minimum temperature in summer is increasing. On the other hand during the winter season all the three temperatures (Tmax, Tmin and mean T) are indicating increasing trend. Thus, summer nights and winters are becoming more warmer and (a clear indication of climate change) in recent time. The same pattern is also reflected with highest Tmax in summer (April) and lowest Tmin in winter (Dec) as shown in Figure Extreme Tmax (Apr) Apr (Ext. Tmax) Dec (Ext. Tmin) Linear (Apr (Ext. Tmax)) Linear (Dec (Ext. Tmin)) Extreme Tmin (Dec) Year Figure Monthly mean extreme maximum temperature (highest Tmax) variation during April and monthly mean extreme minimum temperature (lowest Tmin) during December over Chiang Rai (Source: Thailand Meteorological Dept. and Analysis) Udon Thani The trend of Tmax, Tmin and mean T during summer and winter is shown in Figure 5.22 and Figure 5.23 respectively. The trend in Tmax during summmer (Mar-May) and Tmin during winter (Dec-Feb) shows increasing trend over Udan Thani as shown in Figure 5.22a and Figure 5.23b respectively. It is also seen from Figure 5.23a and Figure 5.23c that the Tmax during winter and also the mean temperature during winter is increasing. Thus, summer days and winters days & nights are becoming more warmer and (a clear indication of climate change) in recent time and have the potential of increasing heat wave frequency. The same pattern is also reflected with highest Tmax in summer (April) and lowest Tmin in winter (Dec) 64

79 Figure Monthly mean temperature variation during hot weather season (March to May) from 1980 to 2008 over Udon Thani. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for April is plotted (Source: Thailand Meteorological Dept. and Analysis) 65

80 Figure Monthly mean temperature variation during cold weather season (December to February) from 1980 to 2008 over Udon Thani. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for December is plotted (Source: Thailand Meteorological Dept. and Analysis) 66

81 5.2.3 Hat Yai With respect to maximum temperature and minimum temperature it is seen that the summer maximum temperature is not in increasing trend (Figure 5.24), whereas the minimum temperature in summer is increasing (Figure 5.24). During winter, significant increasing trend of minimum temperature is reported (Figure 5.25) and relatively little increasing trend in maximum temperature. Thus, the nights are becoming warmer both in summer and winter. It is also seen from Figure 5.26 that the number of days with more that 35 0 C during summer months (Mar to May) although shows many peaks during the period from 1980 to 2008 (like 1983, 1992, 1995, 1998 and 2005), the frequency is not showing increasing trend. It is also seen from Figure 5.26 that during the warmest year 1998, the whole April days were with > 5 0 C Max Temperature Tmax(Apr) Tmin (Apr) Linear (Tmax(Apr)) Linear (Tmin (Apr)) Min Temperature (Tmin) Year Figure Monthly temperature variations (Tmax, Tmin) from 1980 to 2008 during winter season (Apr) over Hat Yai (Source: Thailand Meteorological Dept. and Analysis) 67

82 Max Temperature Tmax(Jan) Tmin (Jan) Linear (Tmax(Jan)) Linear (Tmin (Jan)) Min Temperature (Tmin) Year Figure Monthly temperature variations (Tmax, Tmin) from 1980 to 2008 during winter season (Jan) over Hat Yai (Source: Thailand Meteorological Dept. and Analysis) C g e 25 d > s y a 15 d f o 10 o N 5 MAR APR MAY Linear (APR) Year Figure Number of days with Tmax more that 35 0 C during hot weather season from March to May over Hat Yai. The linear trend for April is plotted in the figure (Source: Thailand Meteorological Dept. and Analysis) Phuket The trend in Tmin and mean Temperature show increasing trend during summer (Mar-May) over Phuket as shown in Figure 5.27b and Figure 5.27c. 68

83 Figure Monthly mean temperature variation during hot weather season (March to May) from 1980 to 2008 over Phuket. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for April is plotted (Source: Thailand Meteorological Dept. and Analysis) 69

84 In winter, all the three temperatures are increasing with maximum increase of Tmin (Figure 5.28) with rate of increase of minimum temperature is much higher (Figure 5.28b) than that of increase of Tmax and mean T (Figure 5.28a and Figure 5.28c). Figure Monthly mean temperature variation during cold weather season (December to February) from 1980 to 2008 over Phuket. (a) Maximum temperature, (b) Minimum Temperature and (c) Mean Temperature. The linear trend line for January is plotted (Source: Thailand Meteorological Dept. and Analysis) 70

85 Thus, this shows the summer and winters nights are becoming more warmer and (clear indication of climate change) and has contributed to increase of mean T as shown in Figure The similar pattern is also reflected with highest Tmax in summer (April) and lowest Tmin in winter (Dec). 5.3 Sea level rise and storm surges The Fourth Assessment Report (AR4) of the United Nations Intergovernmental Panel on Climate Change (IPCC), is the fourth in a series of reports intended to assess scientific, technical and socio-economic information concerning climate change, its potential effects, and options for adaptation and mitigation. The report is the largest and most detailed summary of the climate change situation ever undertaken, involving thousands of authors from dozens of countries, and states in its summary, "Warming of the climate system is unequivocal." "Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations." The Special Report on Emissions Scenarios (SRES) was a report prepared by the Intergovernmental Panel on Climate Change (IPCC) for the Third Assessment Report (TAR) in 2001, on future emission scenarios to be used for driving global circulation models to develop climate change scenarios. It was used to replace the IS92 scenarios used for the IPCC Second Assessment Report of The SRES Scenarios were also used for the Fourth Assessment Report (AR4) in 2007, and have been subject to discussion about whether emissions growth since 2000 makes these scenarios obsolete. 71

86 Table 5.5. SRES scenario (Source: United Nations IPCC) The four SRES scenario families of the Fourth Assessment Report vs. projected global average surface warming until 2100 more economic focus more environmental focus Globalisation (homogeneous world) A1 rapid economic growth (groups: A1T; A1B; A1Fl) C B1 global environmental sustainability C Regionalisation (heterogeneous world) A2 regionally oriented economic development C B2 local environmental sustainability C Current sea level rise has occurred at a mean rate of 1.8 mm per year for the past century, and more recently at rates estimated near 2.8 ± 0.4 to 3.1 ± 0.7mm per year ( ). Current sea level rise is due partly to human-induced global warming, which will increase sea level over the coming century and longer periods. Increasing temperatures result in sea level rise by the thermal expansion of water and through the addition of water to the oceans from the melting of continental ice sheets. Thermal expansion, which is well-quantified, is currently the primary contributor to sea level rise and is expected to be the primary contributor over the course of the next century. Glacial contributions to sea-level rise are less important, and are more difficult to predict and quantify. Values for predicted sea level rise over the course of the next century typically range from 90 to 880 mm, with a central value of 480 mm. Based on an analog to the deglaciation of North America at 9,000 years before present, some scientists predict sea level rise of 1.3 meters in the next century. However, models of glacial flow in the smaller present-day ice sheets show that a probable maximum value for sea level rise in the next century is 80 centimeters, based on limitations on how quickly ice can flow below the equilibrium line altitude and to the sea Future sea level rise In 2007, the Intergovernmental Panel on Climate Change's Fourth Assessment Report predicted that by 2100, global warming will lead to a sea level rise of 19 to 58 cm, depending on which of six possible world scenarios comes to pass. These sea level rises could lead to difficulties for shore-based communities in the next centuries: for example, many major cities such as London and New Orleans already need storm-surge defenses, and would need more if sea level rose, though they also face issues 72

87 such as sinking land. Sea level rise could also displace many shore-based populations: for example it is estimated that a sea level rise of just 20 cm could create 740,000 homeless people in Nigeria. Future sea level rise, like the recent rise, is not expected to be globally uniform (details below). Some regions show a sea-level rise substantially more than the global average (in many cases of more than twice the average), and others a sea level fall. However, models disagree as to the likely pattern of sea level change Effects of sea level rise Based on the projected increases stated above, the IPCC TAR WG II report notes that current and future climate change would be expected to have a number of impacts, particularly on coastal systems. Such impacts may include increased coastal erosion, higher storm-surge flooding, inhibition of primary production processes, more extensive coastal inundation, changes in surface water quality and groundwater characteristics, increased loss of property and coastal habitats, increased flood risk and potential loss of life, loss of nonmonetary cultural resources and values, impacts on agriculture and aquaculture through decline in soil and water quality, and loss of tourism, recreation, and transportation functions. There is an implication that many of these impacts will be detrimental especially for the three-quarters of the world's poor who depend on agriculture systems. The report does, however, note that owing to the great diversity of coastal environments; regional and local differences in projected relative sea level and climate changes; and differences in the resilience and adaptive capacity of ecosystems, sectors, and countries, the impacts will be highly variable in time and space. Statistical data on the human impact of sea level rise is scarce. A study in the April, 2007 issue of Environment and Urbanization reports that 634 million people live in coastal areas within 30 feet (9.1 m) of sea level. The study also reported that about two thirds of the world's cities with over five million people are located in these low-lying coastal areas. The IPCC report of 2007 estimated that accelerated melting of the Himalayan ice caps and the resulting rise in sea levels would likely increase the severity of flooding in the short-term during the rainy season and greatly magnify the impact of tidal storm surges during the cyclone season. A sea-level rise of just 40 cm in the Bay of Bengal would put 11 percent of the country's coastal land underwater, creating 7 to 10 million climate refugees. IPCC assessments suggest that deltas and small island states are particularly vulnerable to sea level rise caused by both thermal expansion and ocean volume. Relative sea level rise (mostly caused by subsidence) is currently causing substantial loss of lands in some deltas. Sea level changes have not yet been conclusively proven to have directly resulted in environmental, humanitarian, or economic losses to small island states, but the IPCC and other bodies have found this a serious risk scenario in coming decades. Coastal wetland ecosystems, such as salt marshes and mangroves are particularly vulnerable to rising sea level because they are generally within a few feet of sea level (IPCC, 2007). Wetlands provide habitat for many species, play a key role in nutrient uptake, serve as the 73

88 basis for many communities economic livelihoods, provide recreational opportunities, and protect local areas from flooding. As the sea rises, the outer boundary of these wetlands will erode, and new wetlands will form inland as previously dry areas are flooded by the higher water levels. The amount of newly created wetlands, however, could be much smaller than the lost area of wetlands - especially in developed areas protected with bulkheads, dikes, and other structures that keep new wetlands from forming inland. The IPCC suggests that by 2080, sea level rise could convert as much as 33 percent of the world s coastal wetlands to open water. (IPCC, 2007). Tidal wetlands are generally found between sea level and the highest tide over the monthly lunar cycle. As a result, areas with small tide ranges are the most vulnerable. An EPA Report to Congress estimated that a two foot rise in sea level could eliminate percent of U.S. wetlands, with more than half the loss taking place in Louisiana (EPA, 1989). 74

89 6 Disaster impacts and extreme natural hazard events Urban environment is subjected to a variety of extreme events that could be a result of climate change although it is difficult to prove. In order to establish a correlation between the disaster events and long term climate variability, it is useful to study past events and prioritize the types of extreme weather events in terms of resultant impact due to occurrence, degree of intensities observed, frequency etc. This will give an indication of the prevailing vulnerabilities of the Urban area/city to long term climate change impact and subsequently helpful in selecting appropriate adaptation options and course of actions to reduce such impacts. Flood has been identified as one of the most pressing issues in Thailand, with which every year each and every pre-selected city has to cope up with. Subsequently inundation, water logging within urban areas, saline intrusion in coastal areas, landslides in hill slopes etc trigger high and costly damages to the built environment. Moreover, erosion directly linked with water flow can lead to the total or partial destruction of buildings, infrastructure, utility services etc. If the buildings do not get collapsed, the foundations will be weakened to such an extent that a failure may occur to such constructions in future even due to minor flood events. The human losses and the resulting costs are thus substantial as seen in Table 6.1, and the time for a city to recover from the interruption to its infrastructure facilities, utility systems, commercial and business establishments induce an even heavier burden and further economic losses. The other indirect consequences also are considerable which are not easy to quantify and value in monetary terms such as inconvenience to urban population, destructions to social fabric, impacts to environment and natural resources etc. The erosion process enhanced by sea level rise, on the coastal lines especially over the lowelevation coastal zones, induces the same risk. Thailand has 2,880 kilometers of coastline, thus it is extremely vulnerable to sea level rises induced by climate change. A one meter rise will not only sink Bangkok and low-lying areas but also cause land subsidence and coastal erosion; resulting in destruction of infrastructure, loss of beaches and irreversible damage to coastal ecosystems. The associated issue of saline intrusion within water bodies would be also substantial. The map from the Center for International Earth Science Information Network at Columbia University (Figure 6.1) highlights the 10 meters Low Elevation Coastal Zone in Thailand with high rate of human settlements. The two pre selected coastal cities; Samut Sakhon and Phuket, both combine high population density with low elevation coastal zone, leading thereby to high exposure to sea level rise. Adaptation measures can be planned to reduce the coastline exposure if the level of vulnerability can be estimated properly. 75

90 Figure 6.1. Map of LECZ of Thailand (Source: CIESIN, Columbia University) 76

91 6.1 Natural disaster events and impacts within the target provinces Muang Udon Thani Muang Udon Thani is no exception concerning climate change effects. The District has to cope with climate unpredictability comprising of seasonal as well as un-seasonal intense weather events. In July 2000 the highest record of rain for the whole province fell over the whole area including the city and led to massive floods, causing two fatalities and the interruption of all activities for several days. In August 2001 torrential monsoon rainfalls for more than two weeks triggered many fatalities and displaced thousands of people. These massive climatic events, meant to occur more frequently, unhinge the normal course of activities and can foster new type of vulnerabilities and increase the existing one, if undertaking of adaptation initiatives is delayed. Table 6.1. Worst cases of flood events in provinces (Source: DDPM main office) Details Udon Thani Chiang Rai Phuket Songkhla Samut Sakhon Year No. of people affected 126,520 45,620 18, , No. of households 42,500 12,562 3,177 69, affected No. of buildings ,790 affected Area agriculture 72, ,736 affected (Rai) Loss (Baht) 90,562, ,560,400 40,425, ,205,460 30,960,000 Every one to two years Udon Thani is issuing warnings for tropical storms, which originate over the South China Sea, during the months of May to October Table 6.1. Cyclones in the area trigger unusual wind currents of which speed may comprise between 63km/h and 118 km/h and high levels of rainfall. Large-scale industries of the region which include sugar mills, agro-based industries are frequently getting affected. Between January and July 2009, 2 tropical storms have been reported by the Department of Disaster Prevention and Mitigation (DDPM) of Udon Thani. 1,404 people and an overall of 434 households have been affected, leading to an economic loss of 4,236,290 Baht. Muang Udon Thani also is vulnerable to annual events of droughts and the districts main livelihood within the district is connected with agriculture sector. Drought events not only create losses to farmer families but also force them to leave the area for employment opportunities available in Cities. 77

92 Table 6.2. Drought data from 2004 to 2009 (Source DDPM main office) Province Event Years Details Hat Yai Udon Thani Chiang Rai Phuket (Song Khla) Drought 2004 No. of people affected 289,621 80,366 81,598 19,813 No. of Household affected 64,508 33,334 22,991 4,466 Area agriculture affected (Rai) 51,468 Loss (Baht) 8,704,127 12,880, No. of people affected 275, ,900 52, No. of Household affected 879,620 69,460 5, Area agriculture affected (Rai) 284,806 86, Loss (Baht) 69,733,616 4,643, No. of people affected 779, , No. of Household affected 193, , Area agriculture affected (Rai) 65,964 Loss (Baht) 10,460, No. of people affected 779, ,746 1,974 23,650 No. of Household affected 196, , ,782 Area agriculture affected (Rai) 55,719 9,949 Loss (Baht) 9,871, , No. of people affected 671, ,668 No. of Household affected 189, ,568 Area agriculture affected (Rai) 9,006 Loss (Baht) 5,214,474 Jan - No. of people affected 764,470 No. of Household July affected 199,236 Area agriculture 2009 affected (Rai) Loss (Baht) Samut Sakhon 78

93 Years Table 6.3. Tropical storm data (Source: Thailand Meteorological Dept) Details No. of event Type Name Date of event Udon Thani Chiang Rai Phuket Hat Yai (Song Khla) Samut Sakhon 1977 Tropical storm CARLA (7710) 9/5/ Tropical 1978 storm SHIRLEY (7805) 1/7/ Tropical storm BESS (7810) 8/12/ Depression - 10/4/ Tropical storm VERNON (8401) 11/6/ Typhoon CECIL (8521) 16/10/ Typhoon WAYNE (8614) 6/9/ Typhoon BETTY (8709) 17/08/ Tropical storm CECEL (8904) 26/05/ Typhoon DAN (8926) 14/10/ Typhoon FRED (9111) 17/08/ Depression - 20/09/ Tropical storm LEWIS (9303) 13/07/ Tropical storm WINONA (9312) 30/08/ Depression - 29/11/ Typhoon MANNY (9327) 15/12/ Tropical storm AMY (9410) 31/07/ Typhoon KONI (0308) 23/07/ Typhoon CHANTHU (0405) 13/06/ Tropical 2005 storm VICENTE (0516) 19/09/ Typhoon DAMREY (0518) 28/09/

94 Figure 6.2. Damages and destruction in Muang Udon Thani due to disaster (Source: DDPM provincial office, Municipality) 80

95 6.1.2 Muang Chiang Rai During the monsoon periods, heavy rainfall trigger every year flooding of various intensity within Muang Chiang Rai. The capacity of the river and associated canal network is not sufficient to cope up with the sudden inflow of water due to intense rainfall. The water level thereby rises rapidly, leading to flooding and erosion. In July 2000 massive floods occurred and overwhelmed the city, destroying the surrounding agricultural fields and farm land, affecting livelihoods and leading to business interruption for several days. In 2006, flash floods occurred and affected the built-up areas and environment as well as the utility facility network within the city. Transportation system was blocked and tourist activities ceased to be active for several days. Loss of crop and economic breakdown led to migration wave of rural population to Bangkok and other cities. Water run-off is constantly increasing due to inadequate land-use planning coupled up with increasing climate variability. Landslide and mudslide are becoming substantial issues to urban as well as rural population. Muang Chiang Rai has to face over the past decade several significant destructions due to slope destabilization during extreme weather events. The topography of the Muang Chiang Rai area associated with heavy rainfall events and unplanned human settlements increase the landslide risk. Reported damages and losses to livelihoods, infrastructure and property due to landslide disaster events over the past shows rapid trend in increase. In fact, each year several events of landslide occur in the high gradient zone of topography. For instance, in 2005, seven events have been reported in Chiang Rai province, affecting a total area of 800 square meters; and in 2007, four landslide events occurred, affecting 300 square meters. Tropical storms are highly frequent in Muang Chiang Rai. Since the beginning of the eighties, the cyclone frequency trends have been accelerated. Strong winds, comprised between 63 km/h and 118 km/h and associated heavy rainfall events are often reported during cyclone period. When storms bring ice rain the situation becomes devastating as it was reported in year 2008 which has created loss of farm land and heavy destructions to shelter in several communities. Drought is also a main concern of the province. In April 2008, a period of extreme drought hit the province. The water level of the Mekong River was very low, impeding the boat tours and creating difficulties to work force usually commuting from rural areas. According to TNA, 314,000 families in 18 districts have been heavily affected by water shortages. The lack of options for irrigation of agricultural areas has led to the loss of harvest and crops. In fact, more than 68,000 rai (27,700 acres) of agricultural lands have had severe impact due to drought. The provincial authorities have declared the 18 districts of Chiang Rai as a drought ravaged area in order to provide relief measures. Environmental degradation is also of concern to Muang Chiang Rai due to reported levels of water pollution as much as air pollution. Many communities within Muang Chiang Rai use the Mekong river water for domestic purposes such as dinking, cooking etc. The pollution level of the river as well as more frequent events of drought, influence the concentration of bacteria in river water in a considerable way, and currently have significant impact on daily life of lot of people as they are heavily dependent on Mekong river being the only source of 81

96 water. Health hazard is thus increasing, especially to the water related diseases. The concerned pollutants in the Kok River running through the city are Dissolved Oxygen (DO) and Total Coliform Bacteria (TCB). The city, resulted due to expansion of its commercial activities, is one of the sources of pollution. As per the records City area is also a place where the rate of TCB increase is highest within Muang Chiang Rai. On the other hand up stream sources of Mekong River and its drainage network, highly contribute to the pollution state in Muang Chiang Rai. Spills from ships, industrial waste, domestic sewage, drainage water from solid waste deposits and landfills are some of the sources of pollution of Mekong River and believed to be added in upstream areas such as China.The municipality which is located downstream also contribute to further increase in pollutant levels through the Kok River which is a part of the catchment. Concerning air quality, with higher number of days exceeding standards of ozone indicator, show an increasing trend, even with limited data as the station used for measurements is only three years old. The direct consequence of high rate of low-level of ozone is the formation of smog. Furthermore, the number of days of PM10 exceeding standards is also increasing within Muang Chiang Rai and this trend has a possibility for deepening the risk of respiratory diseases development such as lung cancer. 82

97 Figure 6.3. Damages and destruction in Chiang Rai province (Source: DDPM provincial office, Municipality) 83

98 6.1.3 Muang Hat Yai Due to its geographical location associated with unplanned urbanization and deforestation in upstream areas, Muang Hat Yai including the Municipality area has become extremely vulnerable to extreme weather events. With its population density, increased volume of paved areas, commercial activities, the municipality area has all the characteristics that can magnify the impacts of any type of flooding event big or small. There are settlements which are concentrated around canal network and such settlements occupy the reservation areas. This has decreased substantially the carriage way capacity, possibility of its expansion, maintenance and in certain places even the continuity of such drainage canals. The population expansion was caused by the migration of population from rural areas due to employment opportunities and also due to availability of other urban facilities such as better education compared to other southern provinces of Thailand. To a certain degree this also can be a result of conflict situation and unrest within the neighboring provinces. Increased influx of tourists from Malaysia has created additional opportunities and further development of commerce and business sector. Increasing trend has been observed in past years in the growth of sectors such as fishery, agriculture and Agro-based industries. High demand for land due to increased urbanization has created vulnerable situation for extreme weather events within Muang Hat Yai. Hat Yai Municipality which has undergone more urbanization than other parts of Muang Hat Yai is prone to flooding, inundation and water logging due to its increased run off and depleted drainage system combined with heavy annual rainfall events. Rapid unplanned urbanization aggravates the situation further. In fact the river U Ta Phao and Klong Toie are responsible for triggering regular flash floods during the monsoon seasons. Serious flooding events occurred in 1988 and again in 2000 (Figure 6.4). Triggered by torrential rains, the flooding of November 2000 has been described as one of the worst natural disasters in the history of urban Thailand (Charlchai et. al., 2004). Flood depths of two to three meters height caused 40 fatalities, thousands of injuries and severe damages to property, livelihood, and lifelines, affecting drastically the economy of the city. More recently, in 2006 flooding also affected more than 200,000 people and paralyzed the city for several days. During the period the total amount of loss reached 23,194,466 Baht. In addition the severely affected sectors within the municipality are transportation, infrastructure, utility services and agriculture (around 3,792 Rai of agricultural lands have been damaged) within Muang Hat Yai drought is also a substantial problem. The total affected from drought is around 2,137 people i.e. 613 households between 2005 and The urbanization trend of Muang Hat Yai is rapid during the past decade. Due to ever increasing demand for land for development, shelter and settlement, hazard prone areas have been encroached by urban expansion. In the direct surroundings of the municipality, the urban settlements are rapidly expanding into four neighboring townships and municipalities. The environmental degradation characterized by high peak of air and water pollution is deepening. The high concentration of Particulate matters PM10, from the sources of manmade origin such as burning of fossil fuels, waste discharges from power plants and industrial process, add and contribute to deterioration of the quality of air within the city, increasing the potential for health hazards. In July 2002 and in February 2003 several 84

99 consecutive days were reported as periods of worsening of air quality, with some days considered to be exceeding the limits established by Thai environmental authorities. Related to health issues, Songkhla province had to cope up with a peak of malaria cases in year This may be a result of combination of complex situations firstly due to flooding and secondly due to deterioration of overall health services quantitatively as well as qualitatively and difficulties in having timely access to medical facilities in the area owing to terrorism widespread in the three neighboring provinces. Figure 6.4. Damages and destruction in Hat Yai (Source: Municipality) 85

100 6.1.4 Muang Phuket The coastline of the island of Phuket is continuously exposed to sea erosion and in recent past has to cope up with sudden devastating events, such as tsunami tidal wave of the 26 December 2004 which has had occurred as a result of a massive earthquake in the Sumatra Island. The impact created by the massive tsunami tidal wave, was the highest reported devastation due to a natural disaster in the Andaman Coast. Muang Phuket suffered heavy losses to assets and its natural resources. 13,065 people died or disappeared during the event; 402 residences were totally destroyed; 550 partially. Among the dead were many foreign tourists who came to Phuket to spend the Christmas and yearend holidays. The utility facilities and coastal infrastructure of the island were heavily damaged. In total the overall damages cost more than 13,000 million Baht (Strategy for Provincial Development Unit, Phuket Governor s Office and National Economic and Social Development Board). Subsequently a Strategic plan has been developed to curb the potential impacts of such disasters by the authorities. The event created much needed awareness on natural disaster events, associated risk and city governments as well as the provincial authorities have undertaken various measures to address the needs for risk reduction. This sort of immediate interventions were needed to boost up the confidence of the important economic sectors such as tourism, commerce, hotel industry etc which are the main source of income of the Muang Phuket area. Among the measures are new land use planning regulations to reduce risk within the coastal zone, special building and enterprise development guidelines for coastal areas, setting up effective response mechanisms such as training of 1 st responders, installation of tsunami early warning towers, etc. There were several simulation exercises to evaluate the effectiveness of such measures and overall all such measures created much needed public awareness and received political acceptance which can be easily extended to other types of natural hazards prevailing in Muang Phuket area. Coastal zone of the Muang Phuket is also very much exposed to irreversible damages on its coral reefs due to high concentration of carbon dioxide emissions in the atmosphere that tends to influence in increase of sea temperature. Reef-building corals are a significant component of the rich ecosystem that provides considerable resources to coastal population. They also serve as a buffer against strong waves that erode coastlines during storms. Currently the coral cover development is declining at a rate of one to two per cent annually due to destructive measures such as fishing, tourism, sedimentation caused by discharge of material as a result of development activities in the coastal area, eutrophication (is a depletion of oxygen in water) due to untreated water run-off, dredging and probably also due to climate change. According to the Phuket Marine Biological Centre (PMBC), coastline of Muang Phuket is seriously endangered due to all these interlinked dynamics associated with coastal zone development. According to the Thailand Meteorological Department, the southern part of Thailand has a relatively high exposure to tropical storms and typhoon. The risk is potentially growing as many tropical storms and typhoons are getting reported from Pacific Islands. In such occurrence of tropical storms and typhoon in addition to high-speed winds, a depression zone 86

101 created can create heavy rainfall, flooding and incidents of destabilization of slopes due to the topography of the area. Direct or indirect result of tropical storms and typhoon and associated natural hazard will be destructions to property, damages to infrastructure and other assets. In fact, in the recent past, one of the regular hazard events prevail in Muang Phuket area to be landslide occurrences. Due to tsunami event now more population try to move on to higher slopes realizing the danger in costal zone and as this tendency grows more and more causes of landslides also are getting reported. The map (Figure 6.5) shows the location of previous landslide events within the area. It is obvious that disturbance created due to uncontrolled development and urban settlements on the hill slopes triggered by heavy rainfalls is responsible for increase in occurrence of landslides events in the area. Figure 6.5. Landslide events map in Phuket province (Source:GERD Kasetsart University, ADPC RECLAIM II ) 87

102 Surrounded by mountains in the Patong municipality area within Muang Phuket, a considerable segment is highly vulnerable to multi-hazards; first the populations living in the mountain slopes and in the toe of the mountain are at risk due to landslides, while the population living in the plain area are exposed to flash flood events and discharge of high sedimentation loads from mountains. Within Patong municipality about 20% of the area has high to moderate susceptibility to landslides. The tropical climate variations participate thereby in creating instability of the slopes and as climate change influence to have more high intensity rainfall events, more intense and frequent events of landslides are meant to occur and affect a larger segment of population more frequently. Figure 6.6. Damages and destruction in Phuket (Source: RECLAIM II, Municipality) 88

103 6.1.5 Muang Samut Sakhon The city lies only about 1 to 2 meters above the mean sea level. Flood is thus a frequent issue the municipality has to cope with, even though the municipal records don t reveal much on the topic. Nevertheless coastlines are facing more and more recurrent events of coastal erosion and rising sea levels causing land subsidence. The natural events result in human migration to other parts of the country in particular to Bangkok. The causes for occurrence of such hazard phenomena can be attributed mostly to man-made interventions, such as sand mining, construction of industrial estates along the coastline, sedimentation coming from coastal development and groundwater extraction. During the last decade, the erosion process is faster than forecasted. Bangkok, Samut Songkhram, Samut Sakhon, Samut Prakan and Chachoengsao provinces are suffering severe erosion according to Master Plan on Coastal Erosion Management for the Upper Gulf of Thailand, published in September by the Thammasat University Research and Consultancy Institute, which studied the coastline covering 100km of shoreline from the mouth of the Mae Klong river in Samut Songkhram to the mouth of the Bang Pakong river in Chachoengsao. Some 2,667 hectares of this coastline was washed away in the 54 years from 1952 to The problem is severe and the rate of erosion is increasing. Local communities are suffering economic damage estimated at more than 100 million baht a year, according to the institute's report. Another simulation indicates that without intervention, in 20 years coastlines will retreat inland by 1.3km as they are eroded away (DMRC report). The intrusion of salt water into productive land areas and depletion of drinking water supply is a substantial risk in the area as the agricultural production such as rice straw and coconut plantations would be destroyed, affecting then durably the local livelihoods. 89

104 Figure 6.7. Damages and destruction in Samut Sakhon (Source: Municipality) 90

105 6.2 Natural Disaster Impacts in Muang district areas recorded by DDPM Table 6.4. Summary of flood disaster in Muang district areas (Source: DDPM provincial office) Detail Chiang Rai Udon Thani Phuket Hat Yai Samut Sakhon Year Number of Disaster Affected Area (Tambon) Nang Lae, Pa O Mae Khaw Tom, Chiang Rai Pa O Don Chai, Rim Kok, Rim Kok, All tambons in Rasada, Karon, Rasada, All tambons Tung Tom Sao, Nom Noi, Chalung, Ta Kam, Pa Tong Ta Kam, Pa Tong Krok Krak, Bang Ya Prak, Don Chai, San Sai, Doi Lan, Nang Lae, Municipality, Tha Tha Sai, Nang Mae Khaw Mae Khaw municipality Vichit, Rawai Kokaew in Tha Kam, Ko Hong, Tung Yai, Kuan Chalung, Ku Tao, Tung Chalung, Ku Tao, Tung Panteay Norasing, Kalong, Tha Sai, Mae Yao, Rim Kok, Pa O Don Sud, Tha Sai, Pa O Lae, Mae Yao, Tom, Nang Tom, Pa O area municipality Lang, Klong Hae, Klong U Ta Phao, Pa Yai, Klong U Thapao, Yai, Klong U Thapao, Ta Chalom, Nakok, Bang Mae Khaw Chai, Huai Chompu, Don Chai, Rob Mae Khaw Tom, Lae, Ban Don Chai area Tong, Ku Tao, Ban Pru, Hat Yai Tung Tamsao Tung Tamsao Krajao, Kra Sa Kao,Samut Tom,Chiang Rai Municipality Mae Kon, Tha Sai, Ban Doo, Tha Sud, Weing, Rim Kok, Mae Khaw Tom, Ban Doo, Mae Kon, Tha Sud, Doo, Doi Hang, Pa O Municipality Sakhon Municipality Affected People 31,306 15,196 10,503 39,154 1,929 N/A 126,520 N/A N/A 225,005 70, N/A 337 Affected Household 9,596 6,425 4,123 15,710 2, ,500 N/A N/A 69,564 16, N/A 91 Losses (THB) 106,350,000 2,917,200 3,303,600 3,323,733 N/A 1,060,000 90,562,500 64,400 1,504, ,205,460 20,468,974 N/A 23,194,466 30,960,000 Table 6.5. Summary of strong wind disaster in Muang district areas (Source: DDPM provincial office) Detail Chiang Rai Udon Thani Phuket Hat Yai Samut Sakhon Year 2009(Jan Sep) Number of Disaster Affected Area (Tambon) Huai Chompu, Ban Doo, Doi Lan, Doi Hang, Mae Ban Chan, Hong Hai, Non Sueng Ban Nong Na Kom, Ban Tad, Nong Hai, Tad, Mu Mon, Chiang Yeun, Na Dee, Na Dee, Nong Phai, Chiang Pin, Mu Ban Tad Ban Luam, Chiang Yeun, Na Kwang, Talad Yai, Rasada Talad Yai, Rasada Kuan Lung, Klong Hae, Ta Pong, Ko Hong, Klong Hae, Klong Hae, Tung Tom Sao, Ku Klong Hae, Hat Yai, Ku Tao Tha Sai, Krok Krak, Bang Ya Bang Pla, Ban Ko,Tha Sai, Na Dee, Bang Ya Prak, Samut Sakhon Bang Ya Prak Na Kok, Kok Kam Khaw Tom, Huai Sak, Pa O Don Chai,Tha Sai, Tha Sud, Mae Yao, Rim Kok Kok Sa Ard, Chiang Pin, Nong Na Kom, Nong Han, Ban Tad, Nikhom Song Kroe, Mag Kang, Na Ka Mon, Na Ka, Ban Khao, Kud Sa, Nikhom Song Kroe, Ban Luam Ban Chan, Na Ka Klong U Tha Phao Tung Tom Sao, Chalung Tao, Nom Noi Prak, Ta Chalom,Bang Krajao, Samut Sakhon Municipality Municipality, Kra Sa Kao, Panteay Norasing, Ka Long, Bang Kra Chao, Kok Kam, Bang Nom Jeed, Mahachai, Tha Chin Affected People N/A N/A N/A N/A 19 people Affected Household N/A N/A N/A N/A Losses (THB) 11,500 2,198, ,382 8, , , ,500 N/A 161,462 42,344 57, ,074 30, ,000 Table 6.6. Summary of fire disaster in Muang district areas (Source: DDPM provincial office) Detail Chiang Rai Udon Thani Phuket Hat Yai Samut Sakhon Year Number of Disaster Event Affected Area (Tambon) Rob Weing Rob Weing, Weing Rob Weing, Rim Kok Mag Kang, Mu Mon, Kud sa, Kok Sa Ard, Chiang Yeun, Na Kud Sa, Kok Sa Ard, Municipality area Karon, Chalong, Talad Talad Nuae, Chalung, Tung Tom Sao, Ko Hong, Hat Yai, Ban Pru, Hat Yai, Hat Yai, Ku Mahachai, Bang Mahachai, Tha Sai, Bang Mahachai, Kok Kam, Bang Mahachai, Kok Na Dee, Tha Nong Phai, Kok Sa Ard, Kwang, Na Ka, NiKhom Song Kroe, Chiang Pin, Chiang Yai, Rasada, Vichit, Rawai Nom Noi, Ta Pong, Hat Klong Hae, Klong U Ko Hong, Klong Tao nom Jeed, Tha Kra Chao, Ban Bo, Bang Nom Jeed, Tha Sai, Na Krabue, Na Dee, Bang Sai, Ban Luam, Kud Sa, Na Non Sung, Ban Khao, Ban Chan, Ban Yeun, Na Ka, Na Dee, Kokaew Yai, Kuan Lung, Klong Tha Phao Hae, Nom Noi Chalom, Bang Ya To Rat, Panteay Dee, Tha Chin, Ban Ko, Ya Prak, Bang To Rat, Mahachai, Ka, Chiang Pin, Chiang Yeun, Nikhom Song Kroe, Non Sung, Ban Khao, Ban Chan, Ban Tad, Sam Praw, Nong Khon Kwang, Nong Na Kom, Nong Hai Luem, Sam Praw, Nong Khon Kwang, Nong Na Kom, Nong Bua, Nong Samrong, Nong Hai, Mag Kang, Mu Mon Sam Praw, Nong Na Kom, Nong Bua, Mag Kang Hae, Kuan Ru, Ko Hong Prak, Ban Ko, Na Dee, Kok Kam Norasing, Kok Krabue, Kok Kam, Na Dee, Bang Ya Prak, Tha Chin, Bang Nom Jeed, Tha Chalom Bang Ya Prak, Bang Kra Chao, Bang To Rat Bang Ko, Tha Sai, Bang Kra Chao Kok Kam, Bang To Rat Affected People N/A N/A N/A N/A N/A N/A Affected Household N/A N/A N/A N/A N/A N/A N/A Losses (THB) 503, , ,000 14,701,310 3,945,372 2,363,101 1,385, ,450 63,300 N/A 85, , ,200 8,640,000 12,625,000 11,515,000 8,225,000 10,610,000 91

106 Table 6.7. Summary of landslide disaster in Muang district areas (Source: DDPM provincial office) Detail Chiang Rai Year 2008 Number of Disaster Event 1 Affected Area (Tambon) Wat Prakhew Affected People 16 Affected Household 4 Losses (THB) Table 6.8. Summary of drought disaster in Muang district areas (Source: DDPM provincial office) Detail Phuket Hat Yai Year Number of Disaster Affected Area (Tambon) Ka ron Ta Kam, Pa Tong, Ko Hong, Kuan Lung, Kuan Lung, Chalung, Tung Tamsao Chalung, Ku Tao, Tung Yai, Nomnoi, Tung Tamsao Affected People N/A 122, Affected Household N/A 38, Losses (THB) N/A 2,776,000 N/A 6.3 Actions taken to reduce impacts of climate hazard extreme events Aftermath of disaster events the municipalities have taken many positive measures to undertake actions o reduce future risk. Most of such initiatives are Projects funded by jointly by Municipality Governments and Royal Thai Government. Such actions include: Major infrastructure Development projects (dams, embankments, Storm water discharging canal network improvements etc) Maintenance schemes (regular maintenance of drainage, cleaning of canals, ) Reconstruction and Rehabilitation projects (Reconstruction of damaged roads, embankments etc) Introduction of new planning regulations Capacity building programs,(ddpm in association with Cities conduct capacity building programs for city officials, community leaders NGOs etc) Simulations(DDPM conduct simulation exercises such as Tsunami drills, fire drills, accident risk management simulations etc) Public awareness programs. All such programs can be considered as the capacity of the cities to undertake future projects on Climate resilience. It is also important to note the high political will of the decision making bodies and city councils etc. 92

107 Table 6.9. Existing and previous major projects relevant to climate change and disaster risk reduction in Udon Thani (Source: Udon Thani Municipality) Project/ Program Year Implementing Agency Budget (million THB) Funding Source Construction of the canal, gate, pump station, underground pipe line Wetland waste water treatment palnt (Klong Suay Nam Sai Project ) Construction of additional underground canal and pipe line to Nong Prachak lake Municipality & Khon Khen University Municipality & Khon Khen University N/A 163 Municipality & central government Municipality 2009 Municipality N/A Municipality Table Existing and previous major projects relevant to climate change and disaster risk reduction in Chiang Rai (Source: Chiang Rai Municipality) Project/ Program Year Implementing Agency Budget (million THB) Funding Source Construction of Sluice gate & diverting canal of Mae Kon river Construction of canal, pipe line & flood pumping system Waste classification plant Municipality N/A Municipality 2007 Municipality N/A Municipality Pullution Control Department 321 Pullution Control Department 93

108 Table Existing and previous major projects relevant to climate change and disaster risk reduction in Hat Yai (Source: Hat Yai Municipality) Project/ Program Year Implementing Agency Budget (million THB) Funding Source Klong Rian Reservior Municipality Municipality Klong Plee Reservior Municipality Municipality Embankment of U Tha Phao canal Municipality Municipality 2004 Culvert construction Municipality 1.30 Municipality Drainage pipe construction Municipality Municipality Pumping station matainance 2005 Water control building construction Pumping station matainance Drainage pipe construction 2006 Water control building construction Drainage system (7 projects) 2007 Drainage pipe construction 2009 Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Municipality Table Existing and previous major projects relevant to climate change and disaster risk reduction in Phuket (Source: Phuket Municipality) Project/ Program Year Implementing Agency Budget (million THB) Funding Source Drainage canal reparing Municipality 0.25 Municipality Construction of drainage canal & road maintainance 2009 Municipality Municipality Construction of drainage pipe Municipality Municipality Dam & reserviors maintainace Municipality Municipality 94

109 Figure 6.8. Projects relevant to climate change and disaster risk reduction (Source: Provincial office, Municipality, field survey) 95

110 Figure 6.9. Flood protection scheme in Muang districts (Source: Municipality) 96

111 Figure Landslide early warning measures developed by ADPC and Kaasetsart universities in Phuket (Source: ADPC RECLAIM II) 97

112 Figure Tsunami warning system in Phuket (Source: field survey and National Disaster Warning Center) 98

113 Figure Community level training and capacity building program organized by municipality and DDPM in Hat Yai and Phuket (Source: Municipality) 99

114 Figure Community level training and capacity building program organized by municipality and DDPM in Udon Thani and Chiang Rai (Source: Municipality) 100

115 Figure Community and municipality capacity building program organized by municipality, DDPM, and ADPC in Phuket (Source: Municipality and ADPC RECLAIM II) 101

116 Figure Various publication relevant to disaster capacity building development 102

117 7 Air and water quality observations 7.1 Air Quality Variations Air pollution is the introduction of chemicals, particulate matter, or biological materials that cause harm or discomfort to humans or other living organisms, or damages the natural environment, into the atmosphere. An air pollutant is known as a substance in the air that can cause harm to humans and the environment. Pollutants can be in the form of solid particles, liquid droplets, or gases. In addition, they can be natural or man-made. Pollutants can be classified as either primary or secondary. Usually, primary pollutants are substances directly emitted from a process, such as ash from a volcanic eruption, the carbon monoxide gas from a motor vehicle exhaust or sulfur dioxide released from factories. Secondary pollutants are not emitted directly. Rather, they form in the air when primary pollutants react or interact. An important example of a secondary pollutant is ground level ozone - one of the many secondary pollutants that make up photochemical smog. Major primary pollutants produced by human activity include: Sulfur oxides (SO x ) - especially sulfur dioxide, a chemical compound with the formula SO 2. SO 2 is produced by volcanoes and in various industrial processes. Since coal and petroleum often contain sulfur compounds, their combustion generates sulfur dioxide. Further oxidation of SO 2, usually in the presence of a catalyst such as NO 2, forms H 2 SO 4, and thus acid rain. This is one of the causes for concern over the environmental impact of the use of these fuels as power sources. Nitrogen oxides (NO x ) - especially nitrogen dioxide are emitted from high temperature combustion. Can be seen as the brown haze dome above or plume downwind of cities. Nitrogen dioxide is the chemical compound with the formula NO 2. It is one of the several nitrogen oxides. This reddish-brown toxic gas has a characteristic sharp, biting odor. NO 2 is one of the most prominent air pollutants. Carbon monoxide - is a colorless, odorless, non-irritating but very poisonous gas. It is a product by incomplete combustion of fuel such as natural gas, coal or wood. Vehicular exhaust is a major source of carbon monoxide. Carbon dioxide (CO 2 ) - a greenhouse gas emitted from combustion but is also a gas vital to living organisms. It is a natural gas in the atmosphere. Particulate matter - Particulates alternatively referred to as particulate matter (PM) or fine particles, are tiny particles of solid or liquid suspended in a gas. In contrast, aerosol refers to particles and the gas together. Sources of particulate matter can be manmade or natural. Some particulates occur naturally, originating from volcanoes, dust storms, forest and grassland fires, living vegetation, and sea spray. Human activities, such as 103

118 the burning of fossil fuels in vehicles, power plants and various industrial processes also generate significant amounts of aerosols. Averaged over the globe, anthropogenic aerosols those made by human activities currently account for about 10 percent of the total amount of aerosols in our atmosphere. Increased levels of fine particles in the air are linked to health hazards such as heart disease, altered lung function, lung cancer. Table 7.1. Availability of pollution (Source: Thailand Pollution Control Dept.) O 3 CO SO 2 (ppb; 10-9 ) (ppm; 10-6 ) (ppb; 10-9 ) ppb ppm ppb City PM 10 ( μg/m 3 ) Chiang Rai Udon Thani Phuket Hat Yai (Songkhla) Samut Sakhon (except ) NO 2 (ppb; 10-9 ) ppb (except 1998, 1999) Different pollution parameters as per the availability are plotted in Figure 7.1. It is seen from Figure 7.1a that over Chiang Rai, the average PM 10 value increase during 2009 by 88% from last year value and it is also higher than standard value of 50( μg/m 3 ). Similarly the maximum PM 10 value also increased from 77.8 (μg/m 3 )in previous year to 286.4( μg/m 3 ) in this year and is again higher than the corresponding standard value of 100( μg/m 3 ). Over Phuket, Hat Yai and Samut Sakhon though the values were higher than the standard value of 50 during earlier years it is less than the standard value during recent 2 to 3 years. Regarding the ozone (O 3 ) in recent years it average concentration is increasing over all stations (Chiang Rai, Phuket, Hat Yai and Samut Sakhon) as shown in Figure 7.1b. 104

119 Figure 7.1. Pm 10 and O 3 concentration (Source: Thailand Pollution Control Dept.) Regarding the Carbon Monoxide (CO) it increases from 0.6 ppm to 0.8 ppm over Chiang Rai in last one year (Figure 7.2a), which is increase of 33%. Similarly over Hat Yai there is tendency of increasing CO concentration in last three years although less than that of Chiang Rai. Another point is that the average concentration of CO over Samut Sakhon is higher than corresponding values over Hat Yai during the entire period from 1997 to 2009 except the year 2002 and 2009 (Figure 7.2a). Regarding the average SO 2 concentration the values are much higher for Samut Sakhon compared to Hat Yai and Phuket values (Figure 7.2b). Still the values for all the three stations are less than that of standard value of 50 ppb during the period from 1997 to 2009 (Fig. 38d). Similarly the average NO concentration over Samut Sakhon is higher than that of corresponding values over Hat Yai during the entire period from 1997 to 2009 (Figure 7.2c). 105

120 Figure 7.2. CO, SO 2 and NO 2 concentration (Source: Thailand Pollution Control Dept.) 106

121 7.2 Water quality indicators / Water Pollution Concerning water pollution, only data for three cities is available (Chiang Rai, Songkhla, Samut Sakhon). In Thailand, the waterbodies pollution has been classified into 5 categories: 1 Less polluted 2 Good quality 3 Moderate 4 Low 5 Highly polluted Many communities use the Mekong river water for domestic purposes such as dinking and cooking. The pollution level of the river as well as the current more frequent events of drought, influence the decrease of water quality of river.compared to the contents in normal water, the level of high concentration of bacteria within the same amount of river water, can affect a larger population. Current level of health hazard thus may increase, especially in terms of water related diseases with the use of polluted river water. The concerned pollutants contain in the Kok River which is running through the city are Dissolved Oxygen (DO) and Total Coliform Bacteria (TCB). The city due to expansion of its urban activities has become one of the sources of the pollution and is also the place where the rate of TCB is highest. Meanwhile the Mekong aquifer as a network of pollutant sources highly contributes to the pollution state of settlements in and around the Mekong River. Chiang Rai municipality which is located downstream is one of them. One type of sources can be the spills from ships and industrial pollutants coming from China through the Mekong River. In addition wastes from domestic sewage, landfills and unplanned solid waste deposits contribute to the pollution of the Mekong River and subsequently also contribute to the increasing trends in pollution of the Kok River. As reported in the PCD document, the pollution types found in each city is summarized in Table

122 City Chiang Rai Songkhla Samut Sakhon Table 7.2. Summarize of the pollution types (Source: Thailand Pollution Control Dept.) Name Issue % above Pollution Remarks of river standard class Ko River Ing River Songkhl a Lake Tadjin River Source of pollution FCB 23% 2 Amphoe Muang (Chiang Rai) FCB 7% 2 TCB NH3 FCB BOD NH3 FCB TCB DO 50% 28% 20% - 62% 47% 46% 53% Amphoe Muang (Samut Sakhon) Highest concentration of pollution Amphoe Muang Amphoe Muang (Songkhla) Amphoe Muang / Kratuban 50% of FCB in 2008 Water quality is decreasing high concentratio n of pollution (type 4) Stable Trend: Analyses done areas close to river at Amphoe Muang Thus, the data indicates that the pollution level of water is moderate to low quality over Songkhla, which can be considered to be same as Hat Yai. Over Samut Sakhon it is found to be of low quality. On the other hand over Chiang Rai it is relatively high. 108

123 8 Assessment of sector based vulnerability In any country cities are considered to be the engines of economic growth and centers of innovation. The foundation of economic prosperity and prominence for most of the provincial cities selected for the study obviously lie in their long standing relationship with the other parts of the province and with other major cities of the country. The long standing relationship with other parts of its own province obviously is connected with the services offered by various sectors and benefits as they are dependent on the lead urban center of the province. The relationship with other main cities is due to favorable conditions offered by the respective provincial cities in terms of their unique economic growth, production patterns, services etc which has also created inter-dependency. If vulnerability is understood as the degree to which whole urban system or its sectors likely to experience damages and losses due to exposure to various external stresses its worthwhile to examine the attributes alone to evaluate the impacts on such systems and their capacity in responding to such stresses created by the potential Climate Change hazards. The city of Hat Yai being a city located near border between Malaysia with Thailand has facilitated trade between the countries and contributed to economic prosperity not only of the neighboring provinces but also of the country. Chiang Rai and Udon Thani located in the Northern provinces, traditionally rich in agriculture; mainly serve as conduits for comers as a supply base of agricultural products to Agro-based industrial regions and consumers. Phuket is a tourism hub and being a province with one of the highest per capita incomes in the country has a major contribution to country s wealth, culture, etc. Samut Sakhon has recorded a phenomenal achievements being an important center of growth due to its strategic location which has direct link to capital city of Bangkok. The fact that so many people are attracted to such provincial cities annually due to vary valid reasons mentioned above, and that these cities continue to grow, underscores the importance of assessing the physical vulnerability of such cities to external stresses expected due to climate hazards. With the conceptual understanding of vulnerability, it becomes clear that the ability of City Authorities to develop strategies to attenuate stresses or cope with the consequences depend on their understanding of such vulnerabilities exist in different sectors they are mandated to handle within their jurisdiction. It is necessary to assess who and what are at risk and how specific stresses evolve in to provide more and more exposure of such sectors to such risks. Vulnerability can be assessed in terms of level of exposure to stresses created by climate change, adequacy or capacity of the given sector to cope, alternate measures available at short notice to help rapid recovery from such stresses. Housing and human settlements, infrastructure, industry, trade and commerce, utility services, education, health and sanitation, urban planning etc are such key sectors that can be vulnerable to such stresses due to climate change. The limited performance of these sectors during and after flooding and other climate hazard occurrences increase the vulnerability of city dwellers and such vulnerability various according to the level of exposure and their economic and social status. Obviously poor suffer the most and their vulnerability is much higher. Loss of life, livelihoods, impacts upon human health, loss and damages to assets and capital are observed to be the key vulnerability indicators. 109

124 8.1 Vulnerability of housing and human settlements. The spatial distribution of existing urban settlements within the built up area is not the result of a careful planning process to guide urban expansion into safer areas. The migration of population from rural area is one of the reasons for population growth. Hence the physical growth of urban areas on one hand is influenced by the fact where the lower income groups can get settled. Many of the migrant population are within this group and they can not afford to get land in safer areas where they can build houses. The other factor is the selection of localities by individuals for expansion of their economic activities or set up new private enterprises. Concentration of such commercial establishments mainly depends on the facilities available to them. The urban poor need to have easy access to such areas and they tend to concentrate around such areas of economic activities. They always try to find locations where they can easily settle down. They can easily find localities such as reservation areas around canals, transportation routes, and low laying areas left for water retention or around water bodies which are highly vulnerable to flooding. At times the reason for water logging and poor drainage within urban built up areas is such unauthorized settlements. Such settlements also lack basic facilities, services and consist of substandard housing and infrastructure. Those poor communities who used to live in substandard housing are usually vulnerable to flooding and other climate hazards in particular those who are concentrated in high risk areas. They will lose economic assets, personal belongings and limited valuables they posses during extreme events. Such urban poor tend to have limited adoptive capacities and more dependent on climate sensitive resources such as local food supplies, water, etc as well are dependent on daily wages earned through livelihoods again at risk due to climate hazards. Where extreme weather events become more intense and more frequent the economic and social costs of those events will increase. Impacts to poor households living in substandard housing in high risk areas from due to such events are quite considerable. Traditionally population in South East Asian countries especially in Thailand, Laos, and Cambodia used unique structural and architectural designs and cultural practices as a way of adaptation to weather related natural events such as construction of elevated houses on stills. This was to prevent destructions mainly due to flooding as well as to have protection from wild animals. In addition this has created open areas and additional working space for the family during summer dry periods to get benefited from natural cooling provided by the environment. Also they used to collect water using traditional rainwater harvesting methods and stored water in large containers. The present day urban society tends to have least respect for such cultural and traditional practices. The assessment for human settlement and housing sector has been carried out in target cities keeping in mind the above mentioned facts. The below given table shows the distribution of buildings within the city limits based on the maps obtained from the National Housing Authority. 110

125 Table 8.1. Building occupancy type (Source: Municipality) building type % of building in city Phuket Hatyai Chiang Rai Udon Thani Residential Commercial Industrial Mixed use Transportation & utilities Government Office & Public Service Others Table 8.2. Building in flood prone area (Source: ADPC TUDPM, DDPM provincial office, Municipality, Calculation by ADPC) building type % building within flood plone area Phuket Hatyai Chiang Rai Udon Thani Residential Commercial Industrial Mixed use Transportation & utilities Government Office & Public Service Others Figure 8.1. Inundation map of Chiang Rai (Source: DDPM Chiang Rai province, Municipality, Field survey) 111

126 Figure 8.2. Inundation map of Hat Yai (Source: ADPC TUDMP, Municipality, Field survey) Figure 8.3. Inundation map of Phuket (Source: Municipality, Field survey) 112

127 Figure 8.4. Pictures of occupancy types in Chiang Rai (Source: Field survey) Figure 8.5. Pictures of occupancy types in Udon Thani (Source: Field survey) 113

128 Figure 8.6. Pictures of occupancy types in Hat Yai (Source: Field survey) Figure 8.7. Pictures of occupancy types in Phuket (Source: Field survey) 114

129 Figure 8.8. Pictures of occupancy types in Samut Sakhon (Source: Field survey) Figure 8.9. Vulnerable buildings in Udon Thani (Source: Field survey) Figure Vulnerable buildings in Chiang Rai (Source: Field survey) 115

130 Figure Vulnerable buildings in Hat Yai (Source: Field survey) Figure Vulnerable buildings in Phuket (Source: Field survey) Floods are the main extreme weather event which is common to all 05 selected cities for the study. Monsoon flooding is very common in Hat Yai, Udon Thani and Chiang Rai districts and cities and urban built up area in all three districts suffered heavy damages in the recent past. More intense and frequent flood events during last 5 years have been observed in Hat Yai Udon Thani and Chiang Rai. Substandard and low-cost housing settlements suffered a lot from such flood events. In addition the urban population had suffered due to damages and looses to household items such as furniture, TV, Radio and also to vehicles. Overall all 5 cities face water logging problem in areas with poor drainage. Housing and settlements in low-laying areas often get affected and largely impact on substandard housing located along canals, reservation areas, low-laying areas are quite considerable. Other common type of hazard which has created substantial impact in terms of frequent damage and asset loss is fire events again common in Udon Thani, Chiang Rai and Hat Yai. Several districts in Chiang Rai province had severe impact due to ice rains, gale and gusty wind storm occurred during last few years and substantial impacts have been observed due to ice rain in year Due to such events some of the rural housing, farm land suffered heavily as owners had to replace totally or partially damaged roofing material. Housing located in mountain slopes in Phuket and Chiang Rai provinces also had to face total destructions due to land sliding. 116

131 8.2 Health and Sanitation Climate change will affect the health of urban population and adapting to climate change in cities is now an additional concern for local governments and health authorities. The greatest concern about the impacts of climate change upon human health regards changes in freshwater resources, food supplies, increase in extreme weather events and its indirect impacts to population such as outbreak of water-borne diseases which are usually associated with contamination due to flooding. Survival of important bacterial pathogens is related to temperature on one hand and on the other hand extreme rainfall can affect the transport of disease organisms into water supply. In addition it is common to have mosquito-borne disease such as malaria, dengue as the higher temperatures reduce the development time of pathogens in vectors and increase potential transmissions to humans. Vector species require specific climatic conditions (temperature, humidity) to be sufficiently abundant to maintain transmission. The urban heat island effect which is also common in more developed areas of tropical countries like Thailand is caused by day time heat being retained by the fabric of buildings and by a reduction in cooling effect of vegetation cover result in creation of heat stresses to urban population. This also has an effect in raising the night time temperature. Children under the age limit of five are often the victims of sanitation related illnesses and diarrheal disease, primarily because of their less developed immunity and because of their play behavior can bring them into contact with pathogens. Diarrheal disease also results in higher levels of malnutrition and increased vulnerability to other illness. Climate related health issues are visible in selected cities for the study with low to high increase variations. The freshwater flooding leads to increased risks of human leptospirosis, particularly, in affected lands with dwellings and farmland and where the water stagnates for several days. The high ratio highlights the lack of sufficient drainage and water supplies causing the water to remain for several days and thus enabling the bacteria to develop. Similarly, dengue fever and malaria outbreaks are very common after flood situations. Songkhla province had to cope in 2007 with a peak of malaria cases. This may be rooted in the combination of flooding events that undermined the medical facilities in the area quantitatively than qualitatively. 117

132 Figure Ratio of malaria cases per 100,000 of population (Source: Department of disease control, Ministry of Public Health) Concerning health issues, Chiang Rai province has to deal regularly with a relatively high ratio of number of leptospirosis cases per 100,000 of population compared with other four cities. Data shows that Udon Thani province has to face relatively high ratio of number of leptospirosis cases per 100,000 of population, which tends to increase over the period Figure Ratio of leptospirosis cases per 100,000 of population (Source: Department of disease control, Ministry of Public Health) 118

133 According to the Ministry of Health, the number of dengue hemorrhagic fever cases has drastically increased in Phuket. The ratio of number of cases per 100,000 of population is four times higher in 2008 than in 2003, as shown in the Figure Related to health issue, Samut Sakhon has to face increasing number of Dengue Hemorrhagic Fever cases. The ratio of number of cases per 100,000 of population has almost double between 2003 and Among the cities selected for the study the cities such as Udon Thani, Chiang Rai may have urban heat Island effect higher than coastal cities such as Phuket, Samut Sakhon and the mean monthly temperature in urban heat islands can create considerable intensity during dray season. Unfortunately this data is not yet available for the study. Figure Ratio of dengue hemorrhagic fever (DHF) cases per 100,000 of population (Source: Department of disease control, Ministry of Public Health) Table 8.3. Ratio of disease per 100,000 population of Hat Yai municipality (Source: Municipality) No. of ratio per No. of ratio per No. of ratio per No. of ratio per Population Population Population Population Disease Cases 100,000 Cases 100,000 Cases 100,000 Cases 100,000 Malaria 155, , , , DHF 155, , , , Table 8.4. Ratio of disease per 100,000 population of Udon Thani municipality (Source: Municipality) 2009 (Jan Oct) Disease No. of Cases ratio per 100,000 DHF Diarrhea 3, Influenza Pneomonia

134 Table 8.5. Ratio of disease per 100,000 population of Phuket municipality (Source: Municipality) Disease No. of Cases ratio per 100,000 No. of Cases ratio per 100,000 Diarrhea 5,324 2, ,900 5, DHF Influenza Malaria Figure Hospitals and health public awareness program (Source: Field survey) 8.3 Education sector Being the provincial and district capital of the respective area the cities selected for the study has created many establishments for education from primary level to higher education. The education infrastructure available within the cities usually is of high quality and damages due to natural events are not very common. Minor impacts usually are recorded during flood events and cyclone or high wind situations but such damages are quickly getting attended. Hence the physical vulnerability of such establishments to natural or extreme weather events is not very high. The students face difficulties to attend to classes during flood season due to inundation of approach roads, inaccessibility of roads, and transportation difficulties. Few schools located in areas prone to floods even had few occasions of inundation due to their location in low-laying areas. 120

135 Figure School building in Muang district (Source: Field survey) Figure Flooded school in Hat Yai (Source: Municipality) On the other hand the Education infrastructure can be considered as a capacity in terms their capacity to use as evacuation centers. There are few school programs organized by the Dept. of Disaster Prevention and Mitigation (DDPM) in all the cities to provide much needed awareness on natural disaster prevention and preparedness aspects. They conduct periodic drills and simulations, fire fighting programs, in addition to class room lectures to create awareness. The programs are very well organized with the assistance of city authorities and authorities of education department and subject matter included in the programs provide knowledge as well as hands-on experience. 121

136 Figure Disaster capacity building program in school (Source: DDPM Udon Thani municipality) The Institutions of Higher Education can be used as centers for technical assistance to cities and again it should be considered as a capacity. Such assistance is being provided to City of Hat Yai by the Princess Songkhla University in Hat Yai. Such assistance can be through technical assessment after disaster events, conduct of risk assessment, design of engineering measures, research on causative factors, local adaptation measures etc. Cities also can get assistance in developing contingency plans, preparedness plans, hazard zonation mapping etc. Table 8.6. List of universities in target cities (Source: Commission of Higher Education) City University Hat Yai Hat Yai University Prince of Songkla University (PSU) Phuket Phuket Rajabhat University (PKRU) Udon Thani Udon Thani Rajabhat University (UDRU) Santapol College (SP) Chiang Rai Rajabhat University (CRU) Chiang Rai Rajamangala University of Technology Lanna (RMUTL) Mae Fah Luang University (MFLU) Chiang Rai College (CRC) Samut Sakhon Samut Sakhon Community College 122

137 8.4 Infrastructure During the last decade the cities in Thailand have increased significantly infrastructure investment and all the cities selected for the study have invested on road network, storm water drainage, flood protection etc. Since most of such projects do not have provisions to consider the risk of flooding during initial stages, such newly built infrastructure also contributed to flooding to some extent in subsequent years. Then the cities have executed flood risk reduction programs which included improving the facilities for flood prevention and storm water drainage. This is applicable to all the cities under the study to a considerable degree. Usually these infrastructure systems have a typical service period of around 100 years or less. In many cities and small urban centers the main problem associated with such infrastructure development is the lack of provisions for integrating the needs of long term climate change impacts(such as all weather roads, sewers, drainage, etc) and lack of capacity to address the same after undertaking such projects with large investments. Figure Inundation area due to flood (Source: ADPC TUDMP, ADPC RECLAIM II, Municipality) More importantly once they built following certain standards it is difficult to replace or improve if destroyed due to extreme weather events as they have no or limited provisions for such improvements due to design conditions. This is one of the central issues with regards to vulnerability of infrastructure because most designs of infrastructure facilities do not take in to consideration the long term impacts other than the usual return periods of events such as floods. When designing such structures the designers follow the permissible criteria given in the design codes that have been established before the climate change discussions came in to effect. Therefore it is difficult to focus on adjustments to infrastructure which can withstand any future extreme weather events. In addition another important factor added to the factor of vulnerability is the fact that the limited local capacity of cities to design implement and 123

138 maintain the necessary adaptation measures. While funding infrastructure projects by cities usually consideration is given to optimization of cost and benefits and when the importance of integration of climate change is not understood by authorities it will be difficult to expect additional allocations for such adjustments. Deficiencies in infrastructure and utility services including storm water drainage and surface drainage systems also created due to no or lack of proper maintenance. Figure Damaged infrastructure due to disaster in Muang district (Source: DDPM, Municipality) 124

139 Figure Flood protection systems in Udon Thani (Source: Municipality) 125

140 Figure Flood protection systems in Chiang Rai (Source: Field survey) 126

141 Figure Flood protection systems in Hat Yai (Source: Field survey) Figure Coastal erosion protection system in Samut Sakhon (Source: Municipality, Field survey) 127

142 Extreme events such as floods, drainage congestion and water logging due to excessive rainfall often cause very serious damage to roads, highways, bridges, culverts etc in Chiang Rai, Udon Thani, Hat Yai provinces as serious flood events have been observed in 2000 in Hat Yai, 2005 in Udon Thani, 2008 in Chiang Rai. In addition water logging due to continuous rainfall is a near regular occurrence in the rainy season in Udon Thani, Chiang Rai, Hat Yai cities. The effect of water logging and flooding to inter city transportation as well as between cities also is considerable and it also causes inconvenience to city dwellers that used to commute to work stations, offices, factories etc. Figure Example of flood protection scheme in Udon Thani (Source: Municipality) 128

143 Figure Example of flood protection scheme in Hat Yai (Source: Municipality) 129

144 8.5 Utility services Another sector severely getting affected by climate related extreme weather events is the utility sector. Water supplies, sanitation, solid waste management, sewage management, electricity, telecommunications all suffer damages as a result of flooding and water logging. Water becomes contaminated in the supply lines due to submerge conditions and leakage. The drainage system gets blocked due to clogging and obstructions created by floating elements, waste material, plastic bags. Roadside waste bins and containers are usually submerged during floods and door to door solid waste collection and disposal services become impossible in many parts of the cities which has tendency to get flooding and water logging. The heavy winds and cyclones create problems to overhead lines for power and electricity supply and fallen trees over lines create more dangerous situations as people also can get affected due to electrocution. In short all utility services grind to a halt during flood events. When water supply is interrupted due to flood events the local government authorities will also have additional workload to transport water using tankers or trucks. The vulnerability of utility services is higher in the cities which are having highest threat from extreme weather events. This was observed in Hat Yai in floods in year 2001, in Udon Thani in year 2008 and Chiang Rai in year 2008 Table 8.7. Location of water supply source and sanitary landfill in Muang district (Source: Municipality) Munng District Water Supply Source Sanitary landfill Udon Thani Huay Lueang Dam Huay It Chiang Rai Mae Kok River Huay Sak Hat Yai U Ta Phao canal Kuan Lung Phuket Bang Wad Dam Saphan Hin 130

145 Figure Utilities in Muang district (Source: Municipality, Field survey) 131

146 8.6 Industrial/commercial sector. Business and economic activities in cities can come to a virtual standstill as a result of heavy rainfall if it causes heavy flooding, water logging so on. Mostly small, medium and large scale industries and factories are affected by similar events when they are located within the cities which are prone to flooding. The cities under the study have such an industrial and commerce base due to concentration of factories such as garments, textiles, cold storage, agro-based industries, furniture etc. In addition cities such as Phuket, Hat Yai and Chiang Rai are famous tourist destinations and are rich in tourism infrastructure and hotels. Most of the factories and business establishments usually are compelled to restrict operations or stop operations due to the fact that floods and water logging can create disruptions to services such as electricity and water. If they do not posses alternate facilities such as standby generators or water supply schemes such disruptions can last for weeks which can cause heavy losses. On the other hand due to transportation difficulties most of the workers also will have difficulties to report for work. Most factories have skilled and unskilled workforces who live in substandard housing located in areas vulnerable to floods. In such cases they will have the priority to relocate in to safer areas with families rather then reporting for work. So vulnerable conditions prevailing in cities connected with infrastructure and utility services to climate change also can inflict losses due to non-functioning or limitations in coping with extreme weather events. Figure Commercial areas in Muang district (Source: Field survey) 132

147 Figure Vulnerable commercial and tourism facilities (Source: ADPC RECLAIM II, Municipality) 8.7 Urban Planning Urban planning is one of the instruments that can be adopted to protect the populations within their jurisdiction from risks arising from probable future climate change scenarios. Vulnerability in relation to urban planning interventions is due to two reasons. One is the lack of capacity of the city government in terms of their powers and resources at their disposal to offer better conditions for living for the vulnerable groups. The other is connected with the lack of accountability of the city administration to the urban population to respond to their needs. Often the city administration does not take in to consideration the real needs of those who are most vulnerable and they do not have any representation in dealings connected to city administration. The urban development and planning policies often increase the vulnerability of poor people rather than reduce them. For example most urban local councils practice unrealistic standers for delineating the allowable limits for the minimum plot size for housing or allocating land for poor and middle income groups. Such plots become not affordable to the vulnerable segment. Many of such regulations have been formulated long years ago when cities were inhabited by lesser number of population. The mechanism they use for enforcement also often open to corrupt practices.the land use planning can be used as a strategy for urban expansion in to safer areas by avoiding the sites most at risk from climate related extreme weather events. It can ensure plot layouts and infrastructure standers for new developments to cope with extreme weather events. Land use planning measures which meet the requirements 133

148 of long term climate change imp acts can also take in to consideration the needs of poor and middle-income groups simultaneously. The city governments can offer housing or land for housing at affordable prices to such groups and arrange to have infrastructure and utility services which are designed to meet the high standards to reduce impacts from extreme events. Where governments have the competence and capacity to allocate safer areas for locally appropriate land users for housing and settlement development through appropriate sub-division regulations, it will improve housing conditions and greatly widens housing possibilities for low income households who are usually vulnerable to extreme climate events. Figure Land use plan of Udon Thani (Source: Municipality) 134

149 Figure Land use plan (Top) and flood inudation map (Bottom) of Chiang Rai (Source: Municipality) 135

150 Figure Land use plan (Top) and flood inundation map of Hat Yai (Source:ADPC TUDMP, Municipality) 136

151 Figure Land use plan (Top) and landslide hazard map (Bottom) of Phuket (Source: ADPC RECLAIM II, Municipality) 137

152 Figure Land use plan of Samut Sakhon (Source: Municipality) 138

153 Figure Urban development in Muang district (Source: Municipality, Field survey) 139