The Complacency of Flood Victims, Socio Economic Factors, and Effects and Vulnerabilities of Floods in Lower Kano Plains, Kisumu County, Kenya
The behavior and thinking of disaster victims should be analyzed and understood even as experts continue to deescalate the destructive effects of such occurrences. Why people choose to live and reside in ecologically fragile environments like flood plains or steep slopes prone to mudslides or avalanches is a complex phenomenon that social scientists need to demystify. This study was conducted in the Nyando sub-catchment, Kano Plains in Kisumu County, Kenya. The study’s objectives were to understand the reason for complacency of flood victims and to determine the effects and vulnerability of flood events in Kano Plains. Both qualitative and quantitative methodologies were used. Stratified sampling technique was used to select the three flood prone areas in Kano, namely, Nyando, Miwani and Lower Nyakach as study sites. Simple random sampling technique was used to select 100 households for the survey while Purposive sampling was used to select the key informants. Methods of data collection were; questionnaires, key informant interviews, focus group discussions (FGDs) and desk reviews. Descriptive statistics was used to analyze the questionnaires, and the qualitative data from key informants was analyzed using content analysis method. FGDs recordings were transcribed and analyzed thematically using NVIVO software. The main research findings were that socio economic factors such us household income, household size and culture plays an important role in determining the choice of site to reside, thus the complacency, and that loss of farmland (17.98%), houses and property (69.66%) were considered the most serious effects of floods. The study therefore concludes that socio economic determinants such as household income, household size and type of housing have a significant role in determining household vulnerability to floods.
Actuarial Journal, 1946(1), 85-94.
Cramér, H. (1946). A contribution to the theory of statistical estimation. Scandinavian
Echendu, A. J. (2020). The impact of flooding on Nigeria’s sustainable development goals (SDGs). Ecosystem Health and Sustainability, 6(1), 1791735.
Floodlist (2016). UN- 1995 to 2015, Flood disasters affected 2.3 billion and killed 157,000 by Richard Davies. Retrieved February 2018. Available: http://floodlist.com/dealing-withfloods/flood-disaster-figures-1995-2015
Hall, J., Arheimer, B., Borga, M., Brázdil, R., Claps, P., Kiss, A., & Llasat, M. C. (2014). Understanding flood regime changes in Europe: A state of the art assessment.
Kabir, H., & Hossen, N. (2019). Impacts of flood and its possible solution in Bangladesh. Disaster Adv, 12(10), 48-57.
Keller, E.A. (2001). Environmental Geology, 8th edition. Upper Saddle River, New
Kenya National Bureau of Statistics (KNBS) (2019). Kenya Population and Housing Census.
Komolafe, A. A., Adegboyega, S. A. A., & Akinluyi, F. O. (2015). A review of flood risk Analysis in Nigeria. American journal of environmental sciences, 11(3), 157.
Masese, A., Neyole, E., & Ombachi, N. (2016). Loss and Damage from Flooding in Lower Nyando Basin, Kisumu County, Kenya. International Journal of Social Science and Humanities Research, 4(3), 9-22.
Musungu K, Motala S. (2012). Participatory multi-criteria evaluation and GIS: An application in flood risk analysis. FIG Young Surveyors Conference-Workshop, Rome, Italy. 2012;4-5.6
National Environmental Management Authority [NEMA] (2004). Strategy for Flood Management in Lake Victoria Basin, Kenya.
Nethengwe, N. S. (2007). Intergrating Participatory GIS and Political Ecology to study flood
vulnerability in the Limpopo Province of South Africa. West Virginia: West Virginia
Nyakundi, H., Mwanzo, I., & Yitambe, A. (2010). Community perceptions and response to flood
risks in Nyando District, Western Kenya. Jàmbá: Journal of Disaster Risk Studies, 3(1),
Okayo J., Odera P. and Omuterema S. (2015). Socio-economic characteristics of the community that determine ability to uptake precautionary measures to mitigate flood disaster in Kano Plains, Kisumu County, Kenya. Springer 2015
Olang L. O., Kundu P.M., Ouma G. and Fürst J. (2009). Impacts of land cover change scenarios on storm runoff generation: A basis for management of the Nyando basin, Kenya 2011, Wiley Online Library
Onyango L, Brent, and Meinzen, R., (2005). Hydronomics and terranomics in the Nyando basin of Western Kenya, Dick International Workshop on African Water Laws: Plural Legislative Frameworks for Rural Water Management in Africa, 26-28 January 2005, Gauteng, South Africa. Proceedings of a meeting held in Johannesburg, South Africa, 26-28 January 2005. Pretoria: IWMI. p. 229-245
Opere A. (2013). Floods in Kenya. Department of Meteorology, University of Nairobi, Kenya
Pearson, K. (1900). On the criterion that a given system of deviations from the probable
in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 50(302), 157-175.
SERA PROJECT (Strengthening Emergency Response Abilities), (2002).
Vulnerability Profile: Darra Woreda (district), North Shewa Zone, Oromiya Region, Ethiopia. Disaster Prevention and Preparedness Commission (DPPC); United States Agency for International Development.
Speis, P. D., Andreadakis, E., Diakakis, M., Daidassi, E., & Sarigiannis, G. (2019). Psychosocial vulnerability and demographic characteristics in extreme flash floods: The case of Mandra 2017 flood in Greece. International Journal of Disaster Risk Reduction, 41, 101285.
Urama K. C. & Ozor N. (2010). Impacts of climate change on water resources in Africa: the role
of adaptation, African Technology Policy Studies Network (ATPS).
Vella, J. (2012). Flooding in Kenya Causes Lost Harvests. Available at: http://www.futuredirections.org.au 10th August 2020.
World Meteorological Organization & UNEP (2004). “Coping with Impacts of Climate Variability and Climate Change in Water Management”, Inter Governmental Panel on Climate Change.
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