Natural Hazards

, Volume 77, Issue 2, pp 787–804 | Cite as

Geophysical, socio-demographic characteristics and perception of flood vulnerability in Accra, Ghana

  • Samuel Nii Ardey CodjoeEmail author
  • Samuel Afuduo
Original Paper


Empirical studies of residential flood vulnerability have generally concentrated on either the geophysical characteristics or the socio-economic characteristics of a given region, rather than a combination of the two. In addition, studies using subjective assessments of flood vulnerability are not very common. However, due to the fact that people’s perceptions influence their risk behaviour, and therefore their vulnerability, understanding perceptions about a phenomenon is very significant for the design of effective communication as well as mitigation, coping, and adaptation strategies. This study uses a digital map (to calculate mean elevation, slope, proximity to lagoon, sea, and drain length by area) and the EDULINK Round II Household Survey (for socio-demographic characteristics of households) for the analysis. Perception of flood vulnerability is derived from responses from heads of households to the question, “Do you perceive your household to be vulnerable to floods?” The responses are either in the affirmative or negative. Results show that even when a subjective assessment of vulnerability is undertaken, it is geophysical characteristics that have significant associations with perceptions of flood vulnerability.


Floods Vulnerability Perceptions Geophysical Socio-demographic Accra 



We are grateful to the International Development Research Centre of Canada for providing funding for this study through the Climate Change Adaptation Research Training Capacity for Development (CCARTCD) Project with Component Number: 106548-001.


  1. Afeku K (2005) Urbanization and flooding in Accra, Ghana. Unpublished Master’s Thesis. Department of Geography, Miami UniversityGoogle Scholar
  2. Albert RG, Elloso J, Lilia V, Andrei PR (2007) Toward measuring household vulnerability to income poverty in the Philippines. Philipp J Dev 35(1):23–53Google Scholar
  3. Andjelkovic I (2001) Guidelines on non-structural measures in urban flood management. UNESCO, IHP-V Tech Doc Hydrol. No. 50, UNESCO, ParisGoogle Scholar
  4. Baker EJ (1991) Hurricane evacuation behavior. Int J Mass Emerg 9:287–310Google Scholar
  5. Bankoff G, Frerks G, Hilhorst D (eds) (2004) Mapping vulnerability: disasters development and people. Earthscan, LondonGoogle Scholar
  6. Benson C (2004) Macro-economic concepts of vulnerability: dynamics complexity and public policy. In: Bankoff G, Frerks G, Hilhorst D (eds) mapping vulnerability: disasters development and people. Earthscan, LondonGoogle Scholar
  7. Botzen JW, Aerts JH, van den Bergh JM (2009) Dependence of flood risk perceptions on socioeconomic and objective risk factors. Water Resour Res 45:104–140CrossRefGoogle Scholar
  8. Brooks N, Adger WN, Kelly PM (2005) The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Glob Environ Change 15:151–163CrossRefGoogle Scholar
  9. Brouwer R, Sonia A, Luke B, Enamul H (2007) Socioeconomic vulnerability and adaptation to environmental risk: a case study of climate change and flooding in Bangladesh. Risk Anal 27(2):313–326CrossRefGoogle Scholar
  10. Bruijn KMD (2004) Resilience indicators for flood risk management systems of lowland rivers. Int J River Basin Manag 2(3):199–210CrossRefGoogle Scholar
  11. Campana NA, Tucci CEM (2001) Predicting floods from urban development scenarios: case study of Diluvio Basin, Porto Alegere Brazil. Urban Water 3:113–124CrossRefGoogle Scholar
  12. Chakraborty J, Tobin GA, Burrell E, Montz BE (2005) Population evacuation: assessing spatial variability in geophysical risk and social vulnerability to natural hazards. Nat Hazards Rev 1(23):23–33CrossRefGoogle Scholar
  13. Chan NW, Parker DJ (1996) Response to dynamic flood hazard factors in Peninsular Malaysia. Geogr J 162(3):313–325CrossRefGoogle Scholar
  14. Christiansen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Kolli RK, Kwon WT, Laprise R, Magaña Rueda V, Mearns L, Menéndez CG, Räisänen J, Rinke A, Sarr A, Whetton P (2007) pp. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Regional climate projections: 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 847–940Google Scholar
  15. Codjoe SNA, Owusu G, Burkett V (2013) Perception, experience and indigenous knowledge of climate change and variability: the case of Accra, a sub-Saharan African city. Reg Environ Change. doi: 10.1007/s10113-013-0500-0 Google Scholar
  16. Dewan AM, Islam MM, Kumamoto T, Nishigaki M (2007) Evaluating flood hazard for land-use planning in greater Dhaka of Bangladesh using remote sensing and GIS techniques. Water Resour Manag 21:1601–1612CrossRefGoogle Scholar
  17. Fekete A (2009) Validation of a social vulnerability index in context to river-floods in Germany. Nat Hazards Earth Syst Sci 9(2):393–403CrossRefGoogle Scholar
  18. Few R (2003) Flooding, vulnerability and coping strategies: local responses to a global threat. Prog Dev Stud 3(1):43–58CrossRefGoogle Scholar
  19. Forkuo EK (2011) Flood hazard mapping using Aster image data with GIS. Int J Geomat Geosci 1(4):932–950Google Scholar
  20. Fosu C, Forkuo EK, Asare MY (2012) River inundation and hazard mapping—a case study of Susan River—Kumasi. Proceedings of Global Geospatial Conference, Québec City, Canada, pp 14–17Google Scholar
  21. Ghana Statistical Service (2012) 2010 population and housing census. Summary report of final results. Sakora Press, AccraGoogle Scholar
  22. Haddad BM (2005) Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit. Glob Environ Change 15:165–176CrossRefGoogle Scholar
  23. Heitz C, Spaeter S, Auzet AV, Glatron S (2009) Local stakeholders’ perception of muddy flood risk and implications for management approaches: a case study in Alsace (France). Land Use Policy 26(2):443–451CrossRefGoogle Scholar
  24. Helweg-Larsen M (1999) The lack of optimism biases in response to the 1994 Northridge. Earthquake: the role of personal experience. Basic Appl Soc Psychol 21:119–129CrossRefGoogle Scholar
  25. Henry R, Fayorsey C (2002) Coping with pregnancy: experiences of adolescents in Ga Mashie, Accra. ORC Macro, Calverton, MarylandGoogle Scholar
  26. Ho MC, Shaw D, Lin SY, Chiu YC (2008) How do disaster characteristics influence risk perception? Risk Anal 28(3):635–643CrossRefGoogle Scholar
  27. Hughes R (1982) The effects of flooding upon buildings in developing countries. Disasters 6(3):183–194CrossRefGoogle Scholar
  28. Kamanou G, Morduch J (2004) Measuring vulnerability to poverty. In: Dercon S (ed) Insurance against poverty. Oxford University Press, Oxford, pp 155–175CrossRefGoogle Scholar
  29. Karley NK (2009) Flooding and physical planning in urban areas in West Africa: situational analysis of Accra, Ghana. Theor Empir Res Urban Manag 13(4):25–41Google Scholar
  30. Kasperson RE, Dow K, Archer E, Caceres D, Downing T, Elmqvist T, Eriksen S, Folke C, Han G, Iyengar K, Vogel C, Wilson K, Ziervogel G (2005) Vulnerable people and places. In: Hassan R, Scholes R, Ash N (eds) Ecosystems and human wellbeing: current state and trends, vol 1. Island Press, Washington, DC, pp 143–164Google Scholar
  31. Kolsky P, Butler D (2002) Performance indicators for urban storm drainage in developing countries. Urban Water 4:137–144CrossRefGoogle Scholar
  32. Lebel YL, Nikitina E, Manuta J (2006) Flood disaster risk management in Asia: an institutional and political perspective. Sci Cult 72(12):2–9Google Scholar
  33. Masiyandima MC, van de Giesen N, Diatta S, Windmeijer PN, Steenhuis TS (2003) The hydrology of inland valleys in the sub-humid zone of West Africa: rainfall-runoff processes in the M’be experimental watershed. Hydrol Process 17:1213–1225CrossRefGoogle Scholar
  34. Mustafa D (1998) Structural causes of vulnerability to flood hazard in Pakistan. Econ Geogr 74(3):289–305CrossRefGoogle Scholar
  35. Nguyen KV, James H (2013) Measuring household resilience to floods: a case study in the Vietnamese Mekong River Delta. Ecol Soc 18(3):13. doi: 10.5751/ES-05427-180313 Google Scholar
  36. Norris FH, Smith T, Kaniasty K (1999) Revisiting the experience behavior hypothesis: the effects of Hurricane Hugo on hazard preparedness and other self-protective acts. Basic Appl Soc Psychol 21:27–47Google Scholar
  37. Nyarko BK (2002) Application of a rational model in GIS for flood risk assessment in Accra, Ghana. J Spat Hydrol 2(1):1–14Google Scholar
  38. O’Brien KL, Eriksen S, Schjolden A, Lygaard L (2004) What’s in a word? Conflicting interpretations of vulnerability in climate change research. CICERO Working Paper 2004:04, OsloGoogle Scholar
  39. Peacock WG, Brody SD, Highfield W (2005) Hurricane risk perceptions among Florida’s single family homeowners. Landsc Urban Plan 73:120–135CrossRefGoogle Scholar
  40. Penning-Rowsell EC (1996) Flood-hazard response in Argentina. Geogr Rev 86(1):72–90CrossRefGoogle Scholar
  41. Schneider SH, Semenov S, Patwardhan A, Burton I, Magadza CHD, Oppenheimer M, Pittock AB, Rahman A, Smith JB, Suarez A, Yamin F (2007) Assessing key vulnerabilities and the risk from climate change. Climate change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of working group II to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 779–810Google Scholar
  42. Schroter D, Cramer W, Leemans R, Prentice IC, Araujo MB, Arnell NW, Bondeau A, Bugmann H, Carter TR, Gracia CA, de la VegaLeinert AC, Erhard M, Ewert F, Glendining M, House JI, Kankaanpaa S, Klein RJT, Lavorel S, Lindner M, Metzger MJ, Meyer J, Mitchell TD, Reginster I, Rounsevell M, Sabate S, Sitch S, Smith B, Smith J, Smith P, Sykes MT, Thonicke K, Thuiller W, Tuck G, Zaehle S, Zierl B (2005) Ecosystem service supply and vulnerability to global change in Europe. Science 310:1333–1337CrossRefGoogle Scholar
  43. Shaw DG, Huang HH, Ho MC (2005) Modeling flood loss and risk perception: the case of typhoon Nari in Taipei. Proceedings of 5th Annual IIASA-DPRI Meeting on integrated disaster risk management: innovations in science and policy 13–18 September, Beijing, ChinaGoogle Scholar
  44. Tsheko R (2003) Rainfall reliability, drought and flood vulnerability in Botswana. Water SA 29(4):389–392Google Scholar
  45. Wassmann R, Nguyen XH, Hoanh CT, Tuong TP (2004) Sea level rise affecting the Vietnamese Mekong delta: water elevation in the flood season and implications for rice production. Clim Change 66(1–2):89–107CrossRefGoogle Scholar
  46. Wong K, Zhao X (2001) Living with floods: victims’ perceptions in Beijiang, Guangdong, China. Area 33(2):190–201CrossRefGoogle Scholar
  47. Xeflide SK, Ophori D (2007) Characterization and frequency analysis of one day annual maximum and two to five consecutive days’ maximum rainfall of Accra Ghana. ARPN J Eng Appl Sci 2(5):27–31. ISSN 1819–6608Google Scholar
  48. Zheng N, Takara K, Tachikawa Y, Kozan O (2008) Vulnerability analysis of regional flood hazard based on MODIS imagery and demographic data in the Huaihe River basin, China. Proceedings of 8th International Conference on Hydro-science and Engineering, Nagoya, JapanGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Regional Institute for Population StudiesUniversity of GhanaLegonGhana

Personalised recommendations