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An Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EVI ModelAn Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EV
 

An Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EVI ModelAn Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EV

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An Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EVI Model

An Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EVI Model

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    An Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EVI ModelAn Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EV An Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EVI ModelAn Assessment of the level of vulnerability to climate change risks in a developing and unplanned tropical city using the EV Presentation Transcript

    • An Assessment of the Level of Vulnerability to Climate Change Risks in a Developing and Unplanned Tropical City Using the EVI model
      Tyubee, B. T.1; Gyuse, T. T.1; Basalirwa, C. P. K.2; Majaliwa, J. G. M.3
      1Department of Geography, Benue State University, Makurdi, Nigeria.
      2Department of Geography, Makerere University, Kampala, Uganda.
      3Institute of Environment and Natural Resources, Makerere University, Kampala, Uganda.
      Davos Congress Center, May 30-June 4,2010
      1
      Tyubee B. T., Ph.D Candidate & START Alumnus
    • Overview
      • Cities and climate change
      • The study objectives
      • The study area
      • Methodology
      • Findings
      • Conclusion
      • Acknowledgements
      • Some useful references
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Cities and Climate Change
      • Cities are engines of economic growth and centers of innovation for the global economy and the hinterland of their respective nations (Sherbinin et al., 2007).
      • There is rapid increase in the proportion of people of people living in cities worldwide. The attraction of cities, the hallmark of their growth, lies in the opportunities that they create through network of people, economic jobs and services (Newman, 2006).
      • There is bidirectional relationship between cities and climate change.
      • Cities can impact local, regional and global climate due to urban heat island, land use/cover and sources of ghg emission.
      • Cities are also the most vulnerable systems to climate change impact due principally to the high concentration of people and associated infrastructure and services (Lindley et al., 2006).
      Davos Congress Center, May 30-June 4,2010
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      • The increased exposure due to the densities of people, infrastructure and services on one hand and increased climate change-induced risks and hazards on the other hand will result in greater number of disasters in cities with huge socio-economic and environmental losses.
      • The vulnerability concept is widely used in studies on risks and natural hazards (Graaf et al., 2007) and has been applied to investigate the response of and impact on systems exposed to perturbations or stressors (Sherbinin et al., 2007).
      • Vulnerability of cities to external stressors is also crucial in decision-and policy-making (Villa and McLeod, 2002) and key to the design of disaster preparedness and management plans, the vital components of an adaptation strategy (Sherbinin et al., 2007).
      • In low- and medium-income nations, such as those in Africa, the vulnerability of cities to climate change risks and hazards would be aggravated by weak economies and fragile infrastructure and services (Satterwaite et al., 2007) and unregulated land use.
      Davos Congress Center, May 30-June 4,2010
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    • The study objectives
      • To demonstrate the effectiveness of utilizing the Environmental Vulnerability Index (EVI) model in measuring and quantifying vulnerability of cities to climate change impacts.
      • The measure the vulnerability of Makurdi, a developing and unplanned city in Nigeria, to climate change at three levels: indicators (i.e. risk factors), sub-components and sub-indices and city.
      • To investigate the temporal patterns of the vulnerability level for two 5-year periods (1997 – 2001 and 2002 – 2006).
      • To identify the critical areas of concern in the city in developing adaptation strategies for risk reduction and increased resilience.
      • To identify the key factors responsible for the level of vulnerability to external shocks in Makurdi.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • The Study Area
      • Makurdi, capital of Benue State of Nigeria, lies between latitudes 7o35׀and 7o53׀N and longitudes 8o24׀and 8o42׀E. Greater Makurdi Area covers a area of 800 km2.
      • The city is bisected by River Benue into northern and southern parts and comprised of eleven administrative regions: 6 urban, 3 sub-urban and 2 rural.
      • The city is located entirely in the flood plains of River Benue with low-lying elevation below 300m.
      • The city started as a river port, without a planning ordinance, in 1920s with few thousand people. The population however grew to 239 889 people in 1991 to 300 096 people in 2006 (census results) representing an increase in population density from 300 to 375 persons/km2.
      Davos Congress Center, May 30-June 4,2010
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      • Within the same period also (1991-2006), built up area has increase from 105km2 to 251km2 (139%); vegetation cover has decreased in area from 544km2 to 424km2 (22%) and area covered by wetland has also decreased from 44km2 to 37km2 (16%).
      • The city experienced a tropical wet and dry climate. Annual rainfall ranges from 800mm to 1700mm, and mean monthly temperature range from 26oC (December) to 31oC (March/April).
      • The increase in urban population has resulted in increased pressure on wetlands, water resources and biodiversity, and the emergence of slums in the city.
      • The location of the city in a high risk area coupled with the population increase and its associated land use /land cover change, and unregulated land use will aggravate the exposure of people, infrastructure and the ecology to external stressors.
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    • Fig 1: Site and Location of Makurdi
      Location
      Administrative units: A (North bank I); B (North Bank II); C (Wailomayo); D (Mission); E (Ankpa/Wadata) and F (Clerk/Market).
      Davos Congress Center, May 30-June 4,2010
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    • Fig. 2: Activities around River Benue
      Market gardening
      Sand Harvesting
      Davos Congress Center, May 30-June 4,2010
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    • Fig. 3: North and South Banks
      Administrative hub and high-income residential housing in the South Bank
      Low- and medium-income residential housing in the North Bank showing the Golf Course in the foreground
      Davos Congress Center, May 30-June 4,2010
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    • Fig. 4: Parts of the city
      The links to North and South Banks
      The AngwanJukunSlum: more are coming up
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    • Fig. 5: The pressure on wetlands
      Reclamation of wetlands for housing construction
      Abundant wetlands in the city
      Davos Congress Center, May 30-June 4,2010
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    • Methodology
      • The Environmental Vulnerability Index (EVI) was developed by the South Pacific Applied Geosciences Commission (SOPAC) (Kaly et al., 1999).
      • The EVI was refined in three phases: Phase I (1989-1999), Phase II (1999-2000) and Phase III (2000-2004).
      • The model was designed primarily to measure the vulnerability of Small Island Developing States (SIDS) but was later utilized for the study of vulnerability of nations to external risks and hazards (Barnett, Lambert and Fry, 2008).
      • Unlike most vulnerability indices, the EVI is concerned with the vulnerability of natural systems as risk entities or responders, which helps in highlighting areas of concern within the risk responder in risk reduction and prevention and enhancing resilience.
      Davos Congress Center, May 30-June 4,2010
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      • In EVI, vulnerability is defined as the extent to which a natural system is prone to damage and degradation, and vulnerability is expressed as a function of exposure (hazards), resilience (resistance) and environmental integrity or degradation (damage).
      • The vulnerability is measured using indicators, which express properties or proxies of the responders that are related their intrinsic and extrinsic vulnerability.
      • These indicators are carefully selected on the basis of their global application, ease of data collection and ease of comprehension (Villa and McLeod, 2002).
      • The data on the indicators are converted into a 1-7 vulnerability scale. In order to obtain approximate linearity of response for each indicator, different response classes are designed to map indicators raw data on the vulnerability scale.
      Davos Congress Center, May 30-June 4,2010
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      • The system’s vulnerability is calculated by aggregating scores at three levels: indicator, sub-category and sub-index and the city.
      • In this study, the EVI is has been modified. This is because it is impossible to locate non-human affected terrestrial systems and in many natural environments where the EVI model has been applied, the distinct division between society and nature that is assumed in the model does not exist (Barnett, Lambert and Fry, 2008).
      • The modified EVI model thus incorporate both social and environmental factors considering a city as a socio-ecological system.
      • Social factors included in the study are urbanization, health care services, personal income, insurance policy, etc, based on literature of social vulnerability.
      • Non-applicable indicators such as earthquake, storm surges, volcanoes, hurricanes, etc were excluded in the study and new indicators such as extreme rainfall, mean elevation and stream density were included.
      Davos Congress Center, May 30-June 4,2010
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      • A total of 29 indicators (58% of the total indicators) were used in the study based on the availability of data. These comprised 18 exposure (REI), 6 resilience (IRI) and 5 degradation (EDI) indicators which were categorized into7 meteorological (Met), 4 city characteristics (CC), 5 ecosystems and 13 anthropogenic indicators.
      • The data on the indicators were collected for a two 5-year periods (1997-2001 and 2002-2006) and were derived from diverse sources including Landsat imageries, meteorological stations, topographical maps, government ministries and agencies and insurance companies.
      • For the purpose of the study, the 1-7 vulnerability scale ranges from 1 (very resilient), 2 (resilient), 3 (at risk), 4 (vulnerable), 5 (significantly vulnerable), 6 (very vulnerable) and 7 (extremely vulnerable).
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Findings: Indicators’ vulnerability scores
      • The overall indicators’ vulnerabilities (fig.6) showed that the EVI scores range from the least (1) to the highest (7) scores.
      • A total of 17 and 18 indicators, representing 58.6% and 62.1% have EVI scores of at least 5 for both 1997-2001 and 2002-2006 periods.
      • However, the EVI scores tended to be higher in 2002-2006 than 1997-2001 periods.
      • Most of the high vulnerability indicators were from the anthropogenic (A) category and exposure and resilience sub-indices.
      • These high EVI scores were consistent for both periods and highlight key areas of hazards and risk reduction in the city.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Findings: Sub-category, sub-index and City vulnerability scores
      • The pattern of the EVI scores for both subcategory and sub-index and the overall city are presented in figure 7.
      • All the EVI scores were above 4, indicating vulnerability.
      • The highest EVI scores for the two periods are 5.8 and 5.8 (CC), 5.7 and 5.9 (A) (fig. 7A) and 6.2 and 6.2 (IRI) (fig.7B) respcetively.
      • The scores, like indicators’ scores were higher during 2002-2006 than 1997-2001 except for CC and IRI.
      • The high vulnerability scores at both indicators’ and sub-category/sub-index’s levels have given rise to the overall city vulnerability score of 5.2 (1997-2001) and 5.4 (2002-2006) indicating significant vulnerability.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Fig. 6: Indicators’ EVI scores
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Fig. 7: Sub-category, sub-index and overall city vulnerability scores.
      A. Sub-category EVI scores
      B. Sub-index and city EVI scores
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Conclusion
      • Despite the several identified limitations of the EVI model such as its subjectivity, no physical support for the choice of 5-year time horizon, recording of responses, the choice of 1-7 vulnerability scale, etc, the results of the study have shown that to reduce risks and hazards and increase resilience to external climate change stressors, adequate attention should be given to anthropogenic, exposure and resilient factors.
      • These can be achieved through sound environmental and planning legislation, establishment and empowerment of disaster management agency, improving the living standard of the people.
      • The results of the study could have been more robust if more indicators were used.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Acknowledgements
      • The research is part of Doctoral Fellowship research under the African Climate Change Fellowship Program (ACCFP). The ACCFP is supported financially by the Climate Change Adaptation in Africa (CCAA), which is funded by the International Development Research Council (IDRC), Canada and the United Kingdom’s Department for International Development (DFID). The ACCFP was administered by the Global Change System for Analysis, Research and Training (START), USA in collaboration with the Institute of Resource Assessment (IRA), University of Dar es Salaam, Tanzania and the African Academy of Sciences, Kenya.
      • We also thank the Women Environmental Program (WEP), Abuja, Nigeria for the acceptance to co-host the Doctoral Research Fellowship.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Some Useful References
      • Barnett, Jon; Lambert, Simon; Fry Ian (2008). The Hazards of Indicators: Insights from the Environmental Vulnerability Index. Annals of the Association of American Geographers, 98 (1), 102 – 119.
      • Gowrie, Marissa N. (2003). Environmental Vulnerability Index for the Island of Tobago, West Indices. Conservation Ecology: Report, 7 (2), 11p.
      • Graaf, R. E. de; Giesen, van de; Ven, F. H. M. van de (2007). The Closed City as a Strategy to reduce Vulnerability of Urban Areas for Climate Change. WaterScience and Technology, 56 (4), 165 – 173.
      • Kaly, Ursula; Brigugio, Lino; McLeod, Helena; Schmall, Susana; Pratt Craig; Pal Reginald (1999). Environmental Vulnerability Index (EVI) to Summarize Natural Environmental Vulnerability Profiles. SOPAC technical Report number 275. South Pacific Applies Geosciences Commission (SOPAC), Fiji.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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      • Lindley, S. J; Handley, J. F.; Theuray, N; Peet, E; Mcevoy, D (2006). Adaptation Strategies for Climate Change in the Urban Environment: Assessing Climate Change related Risks in UK Urban Areas. Journal of Risk Research, 9(5), 543 – 565.
      • Newman, Paul (2006). The Environmental Impact of Cities. Environmental and Urbanization, 18 (2), 274 – 295.
      • Satterwaite, David; Hug, Saleemud; Reid Hannah; Pelling Mark; Lankao, Patricia Romero (2007). Adaptation to Climate Change in Urban Areas: Possibilities and Constraint in Low- and Medium-income Nations. Human settlement Discussion for the paper 1: Climate Change and Cities, 1249, International Institute for Environmental Development
      • Sherbinin, Alex de; Schiller, Andrew; Pulsiphen, Alex (2007). The Vulnerability of Global Cities to Climate Hazards. Environment and Urbanization, 19 (1), 39 – 64s.
      • Villa, Fernanda; McLeod, Helena (2002). Environment Vulnerability indicators for Environmental Planning and Decision-Making: Guidelines and Applications. Environmental Management, 29(33), 335 - 348
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
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    • Thank you all for the kind attention and for listening.
      Davos Congress Center, May 30-June 4,2010
      Tyubee B. T., Ph.D Candidate & START Alumnus
      25