A study was conducted to investigate the intra-seasonal climate variability and change in semi-arid eastern Kenya and also assessed the ability of the households to discern trends in climate and how the perceived trends converge with actual long term weather observations. The study utilised long term climatic data and data collected through interviews of 200 households using a structured questionnaire. The survey data was analysed through descriptive statistics using the Statistical Package for Social Sciences (SPSS) version 12.0. The results of long term climatic data indicated high year-to-year variation in seasonal rainfall with 49.0% and 58% negative anomalies observed in the long and short rainfall seasons respectively. No discernible increasing or decreasing trend in the long- seasonal rainfall was observed over the period of study. However, Long-term temperature data showed high year-to-year variation in annual mean maximum and minimum temperatures with maximum temperature increasing during the period. Long term rainfall data (51 years) showed that 31.4 and 35.3% of the long rains would be classified as good and failed seasons respectively, with the remaining percentage classified as moderate seasons. For the short rains, 15.7 and 43.1 % would be classified as good and failed seasons respectively, with the remaining percentage classified as moderate seasons. Farmers interviewed were able to recollect the past seasons fairly accurately especially the ‘good’ and ‘failed’ seasons which corroborated well with the meteorological records. Indigenous knowledge on weather forecasting was reported by 81% of farmers to be helpful in farming decision making especialy on the types of crops to be planted. A better understanding of farmers’ perceptions of climate change, ongoing adaptation measures, and the decision-making process would important to inform policies aimed at promoting sustainable adaptation of the agricultural sector.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price includes VAT (USA)
Tax calculation will be finalised during checkout.
Agrawal A (1995) Dismantling the divide between indigenous and scientific knowledge. Dev Chang 26:413–439
Beddington JR, Asaduzzaman M, Clark ME, Fernandez Bremauntz A, Guillou MD, Howlett DJB, Jahn MM, Lin E, Mamo T, Negra C, Nobre CA, Scholes RJ, Van Bo N, Wakhungu J (2012) What next for agriculture after Durban? Science 335:289–290
Boko M, Niang I, Nyong A, Vogel C, Githeko A, Medany M, Osman-Elasha B, Tabo R, Yanda P (2007) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Africa. Climate change 2007: impacts, adaptation and vulnerability. Cambridge University Press, Cambridge, pp 433–467
Bryan E, Ringler C, Okoba B, Roncoli C, Silvestri S and Herrero M, 2011. Coping with Climate Variability and Adapting to Climate Change in Kenya: Household and Community Strategies and Determinants. Report to the World Bank for the project “Adaptation of Smallholder Agriculture to Climate Change in Kenya”, February 2011. Pp. 54
Chambers R, Pacey A, Thrupp LA (1989) Farmer first: Farmer innovation and agricultural research. Intermediate Technology Publications, London
Christensen, J.H, Hewitson B, Busuioc A, Chen, X.G, Held, I, Jones, R, Kolli, R K, Kwon, W-T, Laprise, R, Rueda, V M, Mearns, L, Menéndez, C G, Räisänen, J, Rinke, A, Sarr, A, Whetton-Christiansen, J H, Hewitson A, Busuioc, A, and others, 2007, Regional climate projections, chap. 11., in Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., and Miller, H.L. (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, UK, p. 849–940, http://www.ipcc.ch/publications and data/ar4/wg1/en/ch11.html.
Cooper PJM, Dimes J, Rao KPC, Shapiro B, Shiferaw B, Twomlow S (2008) Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: an essential first step in adapting to future climate change. Agric Ecosyst Environ 126:24–35
de Jager A, Karuiku I, Matiri FM, Odendo M, Wanyama JH (1998) Monitoring nutrient flows and economic perfomance in African farming systems (NUTMON). IV. Linking nutrient balances and economic performance in three districts in Kenya. Agricul Ecosys Environ 71:81–92
Eriksen SH, Brown K, Kelly PM (2005) The dynamics of vulnerability: locating coping strategies in Kenya and Tanzania. Geogr J 171:287–305
Government of Kenya 2008. The Kenya Vision 2030. Ministry of Planning and National Development. A Competitive and Prosperous Kenya. Nairobi, Kenya
Herrero, M., C. Ringler, J. van de Steeg1, P. Thornton, T. Zhu, E. Bryan, A. Omolo, J. Koo, A. Notenbaert. 2010. Kenya: Climate variability and climate change and their impacts on the agricultural sector, ILRI report to the World Bank for the project “Adaptation to Climate Change of Smallholder Agriculture in Kenya,” July 2010
IPPC Report (2001) Climate change 2001: the scientific basis. Contribution of the working group 1 to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK, p 881
Jaetzold R., Schmidt H., Hornetz B., Shisanya C. 2006. Farm Management Handbook of Kenya Vol II: Natural Conditions and Farm Management Information 2nd Edition Part C, East Kenya, Subpart C1 Eastern Province, pp. 573.
Nyong A; .Adesina F; Osman Æ B. 2007 The value of indigenous knowledge in climate change mitigation and adaptation strategies in the African Sahe.l Mitigation Adaptation Strategies for Global Change 12: 787–797
Ogutu JO, Piepho HP, Dublin HT, Bhola N, Reid RS (2007) El Niño-southern oscillation, rainfall, temperature, and normalized difference vegetation index fluctuations in the Mara-Serengeti ecosystem. Afr J Ecol 46:132–143
Oliver JE (1980) Monthly precipitation distribution: a comparative index. Prof Geogr 32:300–309
Pretty, J., Guijt, I., Scoones, I. and Thompson, J. (1999). Regenerating agriculture: the agroecology of low-internal input and community-based development. In Sustainable Development, 125–145 (Eds J. Kirkby, P. O’Keefe and L. Timberlake) London: Earthscan.
Richards P (1985). Indigenous Agricultural Revolution: Ecology and Food Production in West Africa. London: Hutchinson
Sattler C, Nagel UJ (2010) Factors affecting farmers’ acceptance of conservation measures – a case study from north-eastern Germany. Land Use Policy 27:70–77
Speranza CI, Kiteme B, Wiesmann U (2008) Droughts and famines: the underlying factors and the causal links among agro-pastoral households in semi-arid Makueni district, Kenya. Glob Environ Chang 18:220–233
SPSS Inc. 2003. Statistical Package for Social Sciences (SPSS) version 12.0.
Thomas D, Twyman C, Osbahr H, Hewitson B (2007) Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa. Clim Chang 83:301–322
The authors are grateful to the Rockefeller Foundation (RF) for funding the study. We also thank households’ members who participated in the survey.
About this article
Cite this article
Gichangi, E.M., Gatheru, M., Njiru, E.N. et al. Assessment of climate variability and change in semi-arid eastern Kenya. Climatic Change 130, 287–297 (2015). https://doi.org/10.1007/s10584-015-1341-2
- Indigenous Knowledge
- Short Rain
- Past Season
- Standardise Anomaly
- Spatial Variation Pattern