Evidence of Climate Change and Seasonal Agricultural Drought in Kakamega South Sub-County, Kakamega County, Kenya





Climate Change, Seasonal Agricultural Drought, Kenya


Changes in climate have led to shifts in weather patterns outside the normal range of variation over a given time period, attributed to either human action or natural causes. This has led to reduced precipitation, which consequently results in reduced water availability for farming in some seasons, hence the seasonal agricultural drought. This has greatly impacted smallholder farmers, lowering their agricultural productivity. This study was undertaken in Kakamega South Sub-County in Kakamega County to determine the impact of the seasonal agricultural drought. The discrete choice model and capability theory were used in this study. Both qualitative and quantitative research designs were used. Both primary and secondary data sources were utilized, and they included questionnaires, interview schedules, focused group discussions (FGDs), and field Secondary data sources, including rainfall and temperature data, were collected from the meteorological station for a period of 35 years (1985–2020). Using Krejce and Morgan tables, a sample size of 377 households was obtained using simple random sampling from a target population of 26,940. The data was analyzed using the Statistical Package of Social Sciences (SPSS) version 23. The results of this study established that there was evidence of climate change and seasonal agricultural drought in Kakamega South sub-county as rainfall is positively correlated with humidity (r = 0.834, p< 0.05). Humidity is negatively correlated with annual maize production (r = -0.869, p< 0.05) and annual average temperature (r = -0.813, p< 0.05). The study recommended that in order to adapt to the effects of climate change that are a result of seasonal agricultural drought, there was a need to improve the sustainability of crop production in the Kakamega South Sub-County by supplementing rain-fed farming with drip irrigation, rainwater gathering, and greenhouse techniques.


Dixon, J., Gulliver. A., & Gibbon, D. (2001). Farming Systems and Poverty: Improving Farmers' Livelihoods in a Changing World. Experimental Agriculture, 39, 109-110.

Fischer, G., Shah, M.M., & van Velthuizen, H.T. (2002). Climate Change and Agricultural Vulnerability. IIASA, Laxenburg, Austria

Hassan, R. & Nhemachena, C. (2008). Determinants of African farmers' strategies for Adapting to climate change: multinomial choice analysis. African Journal of Agricultural and Resource Economics, 2(1), 83-104.

IPCC. (2001). Climate change 2001: Impacts, adaptation and vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J. J. McCarthy, O. F. Canziani, N. A. Leary, D. J. Dokken, & K. S. White (Eds.). Cambridge University Press.

IPCC. (2007). Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK.

IWMI. (2000). World water supply and demand in 2025, In Rijsberman, F.R. (Ed.), World Water ScenarioAnalyses. World Water Council, Marseille.

Kavulya, J. M. (2007). How to write research and term papers. Guidelines for Selecting Topics, Conducting Research,Writing and Referencing Sources. Nairobi, Jomo Kenyatta Foundation.

KNBS (Kenya National Bureau of Statistics). (2019). Statistical abstracts. Government Printers.

Krejcie, R.V., & Morgan, D.W. (1970) Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610. https://doi.org/10.1177/001316447003000308 DOI: https://doi.org/10.1177/001316447003000308

Mugenda O. M., & Mugenda, A. G. (2003). Research methods: Quantitative and Qualitative Approaches. Nairobi: Acts Press.

Mulinya, C., Ang'awa, F., & Tonui,, W. K. (2015). Small scale farmers and resilience adaptive strategies to climate change in Kakamega County (Journal Articles, School of Agriculture and Food Science, Jaramogi Oginga Odinga University of Science and Technology).

McFadden, D. (1973). Conditional Logit Analysis of Qualitative Choice Be. In: Zarembka, P., Ed., Frontiers in Econometrics, Academic Press, New York, 105-142.

Ngaira, J. K. W. (2004). Basic facts in contemporary climatology. Kisumu: Lake Publishers and Enterprises.

O’Brien, K., Sygna, L., Leichenko, R., Adger, W.N., Barnett, J., Mitchell, T., Schipper, L., Tanner, T., Vogel, C., & Mortreux, C. (2008). Disaster Risk Reduction, Climate Change Adaptation and Human Security: A Commissioned. Report for the Norwegian Ministry of Foreign Affairs by the Global Environmental Change and Human Security (GECHS) Project.

Ribot, J. (2010). Vulnerability does not fall from the sky: Toward multiscale, pro-poor climate policy. In: Mearns R, Norton A (Eds) Social Dimensions of Climate Change: Equity and Vulnerability in a Warming World. Washington, DC: The World Bank, 47-74.

Dryzek, J. S., Norgaard, R.B., & Schlosberg, D. (2012). The Oxford Handbook of Climate Change and Society 2011. Online edn, Oxford Academic, 6 Jan. 2012). https://doi.org/10.1093/oxfordhb/9780199566600.001.0001 DOI: https://doi.org/10.1093/oxfordhb/9780199566600.001.0001

Kandji, S. T. (2006). Drought in Kenya: Climatic, Economic and Socio-Political Factors. New Standpoints. https://apps.worldagroforestry.org/downloads/Publications/PDFS/NL06291.pdf

De Wit, M., & Stankiewicz, J. (2006). Changes in water supply across Africa with predicted climate change. Science, 311, 1917-1921. https://doi.org/10.1126/science.1119929 DOI: https://doi.org/10.1126/science.1119929

ICID. (2001). Strategy for Implementation of ICID's concerns emanating from the sector vision on water for food and rural development. International Commission on Irrigation and Drainage.




How to Cite

Chelangat, W., & Mulinya, C. (2023). Evidence of Climate Change and Seasonal Agricultural Drought in Kakamega South Sub-County, Kakamega County, Kenya. African Journal of Empirical Research, 4(2), 699–709. https://doi.org/10.51867/ajernet.4.2.70