Abstract
Coastal towns along the coast of Africa are among the most vulnerable to climate change impacts such as flooding and sea level rise. Yet, because coastal conditions in many parts of the region are poorly understood, knowledge on which population groups are at the most risk is less known, particularly in the Greater Accra Metropolitan Area (GAMA) of Ghana, where the capital city Accra is located. Without adequate information about the risk levels and why, the implementation of locally appropriate adaptation plans may be less effective. This study enriches our understanding of the levels of flood risks along the coast of GAMA and contributes knowledge to improve understanding of place-specific adaptation plans. The study uses data from a 300-household survey, stakeholder meetings, and interviews with local community leaders to construct an integrated vulnerability index. The index includes seven components made up of: dwelling type; house and house environment; household socioeconomic characteristics; experience and perception of flood risk; household and community flood adaptation strategies; house location, and physical characteristics. Our findings show that exposure to floods, particularly from local flash floods is relatively high in all communities. However, significant differences in sensitivity and adaptive capacity of the communities were observed due to differences in location, socioeconomic characteristics, and perception of risks to flooding and sea level rise. The complexity of factors involved in the determination of local-level vulnerability requires that the implementation of adaptation strategies needs to involve cross-sectorial partnerships, involving local communities, in building a comprehensive multi-risk adaptation strategy.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Change history
26 July 2017
An erratum to this article has been published.
Notes
We use mitigation to refer to actions that addresses the cause of climate change or flooding, whereas we use adaptation to refer to actions that address the impact of climate change or flooding.
References
Aboagye D (2012) The political ecology of environmental hazards in Accra, Ghana. J Environ Earth Sci 2(10):2224–32161
Amoako C, Boamah EF (2014) The three-dimensional causes of flooding in Accra, Ghana. Int J Urb Sustain Dev. doi:10.1080/19463138.2014.984720
Antwi EK, Boakye-Danquah J, Owusu AB, Loh SK, Mensah R, Boafo YA, Apronti PT (2015) Community vulnerability assessment index for flood prone savannah agro-ecological zone: a case study of Wa West District, Ghana. Weather Clim Ext 10:56–69. doi:10.1016/j.wace.2015.10.008
Appeaning AK (2014) Coastal vulnerability index to sea level rise in Ghana. Coast Marine Res 2(1):1–7. doi:10.12966/cmr.01.01.2014
Appeaning AK, Adeyemi M (2013) Assessing the impact of sea-level rise on a vulnerable coastal community in Accra, Ghana. J Disas Risk Stud 5:1
Bates BC, Kundzewicz ZW, Wu S, Palutikof JP (eds) (2008) Climate change and water, technical paper of the intergovernmental panel on climate change. IPCC Secretariat, Geneva
Birkmann J (2006) Indicators and criteria for measuring vulnerability: theoretical bases and requirements. In: Birkmann J (ed) Measuring vulnerability to natural hazards: towards disaster resilient societies, vol 55. United Nations University Press, Tokyo, p 77
Blaikie P, Cannon T, Davis I, Wisner B (2014) At risk: natural hazards, people’s vulnerability and disasters. Routledge, London
Bokpe SJ (2015) Annual floods in Accra: an engineering failure. Daily Graphic. http://www.graphic.com.gh/news/general-news/44408-annual-floods-in-accra-an-engineering-failure.html, 10 June 2015
Burrough PA, McDonnell RA (1998) Principles of geographical information systems. Oxford University Press, Oxford
Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Koli RK, Kwon WT et al (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change, 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 847–940
Codjoe SNA, Afuduo S (2015) Geophysical, socio-demographic characteristics and perception of flood vulnerability in Accra, Ghana. Nat Hazards 77(2):787–804. doi:10.1007/s11069-015-1624-y
Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Q 84(2):242–261. doi:10.1111/1540-6237.8402002
Cutter SL, Barnes L, Berry M, Burton C, Evans E, Tate E, Webb J (2008) A place-based model for understanding community resilience to natural disasters. Glob Environ Chang 18(4):598–606. doi:10.1016/j.gloenvcha.2008.07.013
Douglas I, Alam K, Maghenda M, Mcdonnell Y, McLean L, Campbell J (2008) Unjust waters: climate change, flooding and the urban poor in Africa. Environ Urban 20(1):187–205. doi:10.1177/0956247808089156
Eakin H, Bojorquez-Tapia LA (2008) Insights into the composition of household vulnerability from multicriteria decision analysis. Glob Environ Chang 18(1):112–127. doi:10.1016/j.gloenvcha.2007.09.001
Ebi KL, Kovats RS, Menne B (2006) An approach for assessing human health vulnerability and public health interventions to adapt to climate change. Environ Health Perspect 114:1930–1934
Few R (2003) Flooding, vulnerability and coping strategies: local responses to a global threat. Prog Dev Stud 3(1):43–58. doi:10.1191/1464993403ps049ra
Fritzsche K, Schneiderbauer S, Bubeck P, Kienberger S, Buth M, Zebisch M, Kahlenborn W (2014) The vulnerability sourcebook: concept and guidelines for standardised vulnerability assessments. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Bonn and Eschborn
Gruntfest E, Handmer J (eds) (2001) Coping with flash floods. In: Proceedings of the NATO advanced study. http://um.ase.ro/No13/2.pdf
Hahn MB, Riederer AM, Foster SO (2009) The Livelihood Vulnerability Index: a pragmatic approach to assessing risks from climate variability and change—a case study in Mozambique. Glob Environ Chang 19(1):74–88. doi:10.1016/j.gloenvcha.2008.11.002
Heyman BN, Davis C, Krumpe PF (1991) An assessment of worldwide disaster vulnerability. SN, 6 June 1991. SL US
IPCC (2001) Climate change 2001: impacts, adaptation, and vulnerability. Contribution of working group II to the third assessment report. Cambridge University Press, Cambridge
IPCC (2007) Working group I (The Physical Science Basis): Chapter 10 (Global Climate Projections) (Meehl et al. 2007). Regional sea‐level projections are estimated by applying regional adjustments to projected global mean sea‐level rise from 14 AR4 models
Intergovernmental Panel on Climate Change (2014) Climate Change 2014 – Impacts, Adaptation and Vulnerability: Regional Aspects. Cambridge University Press
Karley NK (2009) Flooding and physical planning in urban areas in West Africa: situational analysis of Accra. Theore Empiri Res Urban Manag 4(13):25–41
Mårtensson U, Eklundh L, Gyamfi-Aidoo J, Tetteh E (1999) Ghana: Country at a glance (G-CAG) data description and instructions for the use of the G-CAG (final report). University of Ghana, Accra
McGranahan G, Balk D, Anderson B (2007) The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones. Environ Urban 19(1):17–37. doi:10.1177/0956247807076960
Messner F, Meyer V (2006) Flood damage, vulnerability and risk perception–challenges for flood damage research. Flood risk management: hazards, vulnerability and mitigation measures. Springer, Nato Science Series, 149–167. https://www.econstor.eu/bitstream/10419/45258/1/489068715.pdf
Müller A, Reiter J, Weiland U (2011) Assessment of urban vulnerability towards floods using an indicator-based approach—a case study for Santiago de Chile. Nat Hazards Earth Syst Sci 11:8
Munji CA, Bele MY, Nkwatoh AF, Idinoba ME, Somorin OA, Sonwa DJ (2013) Vulnerability to coastal flooding and response strategies: the case of settlements in Cameroon mangrove forests. Environ Dev 5:54–72. doi:10.1016/j.envdev.2012.10.002
NASA (2004) The shuttle radar topography mission (SRTM). http://www.jpl.nasa.gov/srtm/
Nyarko BK (2000) Flood risk zoning of Ghana: Accra experience. International Archives of Photogrammetry and Remote Sensing, vol xxxiii, part B7. Amsterdam
OECD (2008) Handbook on constructing composite indicators: methodology and user guide. Technical report. OECD, Paris. Retrieved 25 Jan 2017 http://www.oecd.org/std/42495745.pdf
Oteng-Ababio M, Owusu K, Appeaning KA (2011) The vulnerable state of the Ghana coast: the case of Faana-Bortianor. Jam J Dis Risk St 1(3):429–442
Owusu G (2012) A GIS-based estimation of soil loss in the Densu basin in Ghana West African. J Appl Ecol 20(2):41–51
Owusu G (2014) Re-engineering DEM to extract geomorphologic parameters for flood prediction in Ghana. J Geomatics 8:153–163
Owusu G, Owusu-Barima A, Amankwaa EF, Eshun F (2017) Analyses of freshwater stress with a couple ground and surface water model in the Pra Basin, Ghana. App Water Sci 7(1):137–153
Piya L, Maharjan KL, Joshi NP (2012) Vulnerability of rural households to climate change and extremes: analysis of Chepang households in the mid-hills of Nepal. In: Selected paper prepared for presentation at the international association of agricultural economics (IAAE) triennial conference, Foz do Iguacu, Brazil, pp 18–24
Piya L, Maharjan KL, Joshi NP (2013) Determinants of adaptation practices to climate change by Chepang households in the rural Mid-Hills of Nepal. Reg Environ Chang 13(2):437–447. doi:10.1007/s10113-012-0359-5
Schmidt-Thome P, Greiving S (2013) European climate vulnerabilities and adaptation: a spatial planning perspective. Wiley, London
Schneiderbauer S (2007) Risk and Vulnerability to Natural Disasters from Broad View to Focused Perspective. Doctoral dissertation, Freie Universität Berlin
Schneiderbauer S, Ehrlich D (2006) Social levels and hazard (In)-dependence in determining vulnerability. In: J. Birkmann (ed), Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient Societies. United Nations University Press, Tokyo
Tachie-Obeng E, Hewitson B, Gyasi EA, Abekoe M, Owusu G (2014) Downscaled climate change projections for Wa District in the Savanna Zone of Ghana. J Disaster Res 9(4):422–431
The Daily Graphic (2015) Flood disaster profile of Ghana since 1968. http://www.graphic.com.gh/news/general-news/44243-flood-disaster-profile-of-ghana.html, 05 June 2015
Tiepolo M (2014) Flood risk reduction and climate change in large cities south of the Sahara. In: Macchi S, Tiepolo M (eds) Climate change vulnerability in southern African Cities. Springer, Berlin, pp 19–36
Twumasi YA, Asomani-Boateng R (2002) Mapping seasonal hazards for flood management in Accra, Ghana using GIS. In: IEEE international geoscience and remote sensing symposium, 2002. IGARSS’02. IEEE, vol 5, pp 2874–2876
UN Habitat (2014) The state of African Cities 2014: re-imagining sustainable urban transitions. United Nations Human Settlements Programme, Nairobi
Velasquez G, Tanhueco R (2005) Known risk. In: United Nations ‘World Conference on Disaster Reduction’, Chapter: Incorporating social issues in disaster risk assessment
Vincent K (2004) Creating an index of social vulnerability to climate change for Africa. Tyndall Center for Climate Change Research. Working paper 56:41
Weddfelt E, Vaccari M, Tudor T (2016) The development of environmental visions and strategies at the municipal level: case studies from the county of Östergötland in Sweden. J Environ Manag 179:76–82. doi:10.1016/j.jenvman.2016.04.050
Wisner B, Blaikie P, Cannon T, Davis I (2004) At risk: natural hazards, people’s vulnerability and disasters, vol 2. Psychology Press, Hove
Woodroffe CD (2003) Coasts: form, process and evolution. Cambridge University Press, Cambridge
World Bank (2011) Vulnerability, risk reduction, and adaptation to climate change: Ghana. World Bank, Washington
Acknowledgements
Funding was provided by Danida Fellowship Centre.
Author information
Authors and Affiliations
Corresponding author
Additional information
The original version of this article was revised: The first author’s name was incorrectly given as William Kojo Paul Yankson instead of Paul William Kojo Yankson.
An erratum to this article is available at https://doi.org/10.1007/s11069-017-3006-0.
Appendices
Appendix 1
Descriptive statistics for exposure
Sub-category | All communities | Communities | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean | Min | Max | STD | AS | AK | OK | LD | LK | TW | KK | GS | |
Average number of flood events in Accra for the past 10 years | 23.00 | 23 | 23 | 0.00 | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 |
Proportion of people who experience flooding every year | 36.16 | 12 | 63.3 | 18.87 | 63.3 | 44 | 52 | 12 | 22 | 24 | 20 | 52 |
Proportion of people who had experienced flooding other than rainfall flooding over the past 10 years | 34.25 | 12 | 58 | 18.38 | 58 | 44 | 52 | 12 | 12 | 24 | 24 | 48 |
Proportion of people who have experienced flooding from rainfall/runoff around their house over the past 10 years | 37.00 | 12 | 70 | 22.01 | 70 | 48 | 56 | 16 | 18 | 24 | 12 | 52 |
Proportion of households with risk such as injury or death or property damage because flooding from rainfall/run off | 26.25 | 4 | 46 | 14.20 | 46 | 38 | 28 | 4 | 24 | 20 | 12 | 38 |
Proportion of households with risk such as injury or death because of flooding other than rainfall flooding over the past 10 years | 33.50 | 8 | 62 | 20.11 | 62 | 38 | 36 | 8 | 22 | 24 | 16 | 62 |
Mean standard deviation of monthly average of average maximum daily temperature (years 2005–2015) | 0.40 | 0.4 | 0.4 | 0.00 | 0.4 | 0.4 | 0.4 | 0.4 | 0.4 | 0.4 | 0.4 | 0.4 |
Mean standard deviation of monthly average of average minimum daily temperature (years 2005–2015) | 0.50 | 0.5 | 0.5 | 0.00 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
Mean standard deviation of monthly average precipitation (years 2005–2015) | 47.30 | 47.3 | 47.3 | 0.00 | 47.3 | 47.3 | 47.3 | 47.3 | 47.3 | 47.3 | 47.3 | 47.3 |
Proportion of households who have observed sea level rise | 58.00 | 36 | 84 | 17.10 | 80 | 60 | 36 | 44 | 56 | 84 | 44 | 60 |
Appendix 2
Descriptive statistics for sensitivity
Sub-categories | All communities | Communities | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean | Min | Max | STD | AS | AK | OK | LD | LK | TW | KK | GS | |
Proportion of households without in-house/compound piped water access | 52.63 | 10.00 | 84 | 32.13 | 83 | 10.00 | 12.00 | 24 | 58 | 84 | 76 | 74 |
Proportion of households without toilet facilities at home | 61.50 | 12.00 | 96 | 32.33 | 90 | 12.00 | 16.00 | 52 | 84 | 96 | 68 | 74 |
Proportion of population unemployed | 14.25 | 4.00 | 28 | 7.36 | 14 | 4.00 | 20.00 | 28 | 16 | 12 | 8 | 12 |
Proportion of the population in informal employment | 81.75 | 64.00 | 94 | 8.71 | 78 | 94.00 | 80.00 | 64 | 84 | 84 | 88 | 82 |
Proportion who are not owners of a house | 60.00 | 40.00 | 82 | 12.96 | 82 | 64.00 | 52.00 | 52 | 58 | 40 | 60 | 72 |
Proportion of the population that reported damage to property from flooding in the community over the past 10 years | 33.50 | 8.00 | 62 | 20.11 | 62 | 38.00 | 36.00 | 8 | 22 | 24 | 16 | 62 |
Proportion of those who reported property damages because of flooding from rainfall/runoff in their household over the past 10 years | 26.25 | 4.00 | 46 | 14.20 | 46 | 38.00 | 28.00 | 4 | 24 | 20 | 12 | 38 |
Proportion of households who reported themselves/family member/neighbor having been forced to move or relocate because of recent flood disaster in the last 10 years | 17.25 | 0.00 | 66 | 23.95 | 66 | 14.00 | 0.00 | 0 | 0 | 20 | 0 | 38 |
Proportion of population who indicated they are likely to be affected by coastal flooding from sea level rise | 32.25 | 8.00 | 76 | 23.67 | 76 | 22.00 | 8.00 | 16 | 20 | 52 | 16 | 48 |
Proportion of population who feel worried about the danger of flooding in their community? | 58.23 | 36.70 | 89.5 | 19.59 | 89.5 | 56.00 | 52.00 | 44 | 36.7 | 52.1 | 48 | 87.5 |
Proportion of population who feel staying in their community is a threat to their safety | 36.89 | 28.50 | 48 | 8.72 | 29.1 | 38.00 | 48.00 | 44 | 28.5 | 30.4 | 48 | 29.1 |
Proportion of the population who reported any form risk because of flooding from rainfall/runoff | 31.75 | 8.00 | 48 | 15.02 | 48 | 42.00 | 44.00 | 8 | 22 | 24 | 20 | 46 |
Proportion of population who ranked roads infrastructure at a high risk to coastal flooding | 24.13 | 8.00 | 48 | 15.03 | 45.7 | 12.80 | 16.70 | 8 | 14 | 48 | 24 | 23.8 |
Proportion of population who ranked beach going infrastructure at a high risk to coastal flooding | 55.49 | 33.30 | 88 | 17.38 | 33.3 | 69.40 | 43.50 | 44 | 56 | 48 | 88 | 61.7 |
Proportion of population who ranked houses at a high risk to coastal flooding | 59.78 | 44.00 | 79.6 | 12.03 | 79.6 | 44.90 | 56.50 | 44 | 58 | 68 | 68 | 59.2 |
Proportion of population who ranked fishing at a high risk to coastal flooding | 61.53 | 37.50 | 83.7 | 16.19 | 52.1 | 71.40 | 43.50 | 37.5 | 60 | 76 | 68 | 83.7 |
Proportion of population who ranked business firms at a high risk to coastal flooding | 13.26 | 8.30 | 28 | 6.68 | 10.6 | 8.30 | 8.30 | 8.3 | 14 | 16.7 | 28 | 11.9 |
Proportion of population who ranked coastal wetlands at a high risk to coastal flooding | 17.38 | 4.00 | 47.6 | 15.33 | 29.8 | 11.80 | 10.50 | 5.3 | 6 | 4 | 24 | 47.6 |
Average slope (%) | 1.75 | 1.00 | 2.7 | 0.57 | 1.58 | 1.50 | 1.38 | 1.6 | 1.7 | 2.5 | 2.7 | 1 |
Average distance to local drain/stream (KM) | 1.66 | 0.53 | 2.3 | 0.67 | 2.05 | 1.15 | 0.53 | 2.25 | 2.1 | 1.9 | 1 | 2.3 |
Average distance to sea (km) | 0.92 | 0.55 | 1.5 | 0.35 | 0.56 | 0.80 | 1.33 | 1.5 | 0.55 | 1 | 0.7 | 0.94 |
Average elevation (m) | 20.18 | 13.30 | 34 | 6.82 | 18 | 15.14 | 13.30 | 16 | 21 | 18 | 26 | 34 |
Appendix 3
Descriptive statistics for adaptive capacity
Sub-category | All communities | Communities | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean | Min | Max | STD | AS | AK | OK | LD | LK | TW | KK | GS | |
Proportion of population who reported good drainage condition in their community | 34.25 | 2 | 64 | 20.63 | 2 | 26 | 48 | 40 | 52 | 64 | 28 | 14 |
Proportion of population who use any flood protection measures, e.g., digging trenches around houses before and during floods | 19.50 | 0 | 46 | 16.10 | 40 | 46 | 16 | 8 | 10 | 0 | 12 | 24 |
Proportion of the population that participate in community programs toward flood mitigation/adaptation | 15.75 | 4 | 30 | 9.53 | 30 | 16 | 12 | 4 | 14 | 8 | 12 | 30 |
Proportion of households that receive a warning about the pending natural disasters | 23.40 | 0 | 73 | 22.88 | 73 | 4.5 | 13.3 | 0 | 18.2 | 22.2 | 36 | 20 |
Proportion of population affected by recent floods who received assistance (outside formal government) | 87.20 | 75 | 100 | 10.03 | 100 | 95.5 | 86.7 | 100 | 81.8 | 77.8 | 75 | 80.8 |
Proportion of population affected by recent flood who received assistance (from formal government sources) | 10.79 | 8 | 18 | 3.6 | 14 | 8 | 8 | 8.3 | 10 | 12 | 8 | 18 |
Proportion of male population | 44.25 | 32 | 52 | 6.80 | 48 | 48 | 44 | 36 | 48 | 52 | 32 | 46 |
Proportion of the population living in secured dwelling type | 80.00 | 56 | 92 | 13.18 | 92 | 64 | 84 | 92 | 80 | 56 | 84 | 88 |
Proportion of population using a secured building material | 75.19 | 22 | 96 | 24.58 | 96 | 22 | 76 | 60 | 94 | 89 | 89 | 75.5 |
Proportion of the population living in a house with an outer wall | 36.00 | 4 | 86 | 28.75 | 70 | 8 | 4 | 24 | 40 | 24 | 32 | 86 |
Proportion of the population living in house with a secured floor material | 75.88 | 58 | 88 | 9.95 | 58 | 66 | 76 | 88 | 82 | 80 | 84 | 73 |
Proportion of the population using a secured roofing material | 93.50 | 86 | 100 | 4.99 | 94 | 90 | 100 | 88 | 98 | 96 | 96 | 86 |
Proportion of household with a kitchen attached to the main building | 35.75 | 20 | 60 | 12.44 | 24 | 30 | 20 | 40 | 42 | 32 | 60 | 38 |
Proportion of household with piped water at home | 47.25 | 16 | 90 | 32.27 | 16 | 90 | 88 | 76 | 42 | 16 | 24 | 26 |
Proportion of population with access to electricity | 83.00 | 70 | 96 | 8.82 | 84 | 74 | 96 | 88 | 92 | 80 | 80 | 70 |
Proportion of population who have undertaken maintenance of their outer wall over the past 10 years | 14.75 | 0 | 42 | 16.46 | 36 | 4 | 0 | 4 | 12 | 0 | 20 | 42 |
Proportion of population who have done any maintenance of their building over the past 10 years | 31.99 | 20.8 | 48 | 8.60 | 24.5 | 28.6 | 48 | 32 | 20.8 | 40 | 32 | 30 |
Proportion of population who have undertaken maintenance of their floor over the past 10 years | 10.50 | 4 | 20 | 5.93 | 8 | 6 | 4 | 4 | 12 | 16 | 20 | 14 |
Proportion of population who have undertaken maintenance of their roof wall over the past 10 years | 22.06 | 8 | 28 | 6.72 | 8 | 26 | 24 | 24 | 26.5 | 28 | 16 | 24 |
Proportion who have any form of economic activity attached to the household | 30.75 | 12 | 52 | 13.48 | 12 | 52 | 44 | 40 | 24 | 20 | 24 | 30 |
Proportion of the population that reported knowledge of any civil society in the community involved in flood protection and mitigation | 4.76 | 0 | 16 | 7.08 | 16 | 4.1 | 0 | 0 | 2 | 0 | 0 | 16 |
Rights and permissions
About this article
Cite this article
Yankson, P.W.K., Owusu, A.B., Owusu, G. et al. Assessment of coastal communities’ vulnerability to floods using indicator-based approach: a case study of Greater Accra Metropolitan Area, Ghana. Nat Hazards 89, 661–689 (2017). https://doi.org/10.1007/s11069-017-2985-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-017-2985-1