Spatio-temporal Climate Change And Its Effects On Household Livelihoods In The Lake Victoria Basin Of Kenya



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University of Nairobi Research Archive


The general public view is that changes in climate are indeed occurring globally. Recent studies have established an unprecedent variations in climate change events with the Lake Victoria Basin of Kenya, which are attributed to climate change. This study sought to determine the climate change and its effects on rural household livelihoods in the Lake Victoria Basin of Kenya. The study guided by the following objectives: to assess the spatial and temporal variations in the Lake Victoria Basin of Kenya using rainfall and temperature indices, to analyze the effects of the current climate change on rural household livelihood in the Basin, to establish climate change adaptation strategies employed by the rural household in the Lake Victoria Basin of Kenya and, to determine the future climate change scenarios over the Lake Victoria Basin of Kenya. The hypotheses for this study were: the rainfall and temperature indices over the Lake Victoria Basin of Kenya have not significantly varied, the rural household livelihoods in the Lake Victoria Basin of Kenya have not been significantly affected by changes in climate, the rural households over the Lake Victoria Basin of Kenya have not employed significant adaptation strategies that address their livelihoods and, the future climate scenarios over the Lake Victoria Basin of Kenya do not vary from the present climate scenario. A multi-stage sample survey research design consisting quantitative and qualitative approach was adopted for this study. Both secondary and primary data, for climate and household data respectively, were used to achieve the objectives. The climate data were sourced from 14 weather and gridded data stations while, household data were sourced from 359 households sourced from a field sample survey using a multi-stage stratified random sampling technique. The datasets were subjected to various statistical analysis techniques preceded by quality control and homogeneity test. Climate data was subjected to time series analysis to determine climate trends, seasonality and hydrologic characteristic in the Lake Victoria Basin of Kenya. On the other hand, the household data was subjected to both basic and inferential statistical analysis that included logistic regression model analysis using statistical tools available in SPSS IBM 21. The study revealed a decline in the normal wetness conditions due to increased episodes of extreme low rainfall events. Furthermore, the long rains, Mar-May seasonal rains, have declined while short rains, Oct-Dec seasonal rains, have increased. The number of rainy days has also declined in the both rainy seasons. The means of minimum and maximum temperatures have significantly increased between 0.5ºC - 0.7ºC and 0.7ºC and 1ºC in the basin’s highlands and lowlands respectively. The models project a declining trend for both long and short seasonal rainfall. A decrease in both long (Mar-May) and short (Oct-Dec) rains are projected under low (RCP4.5) and high (RCP 8.5) emission scenario. The rainfall onsets and cessations are also projected to vary significantly in both the near and far future. The climate change effects that affected the rural livelihoods emanated mainly from frequent and prolonged severe droughts which resulted into a decline in subsistence production, increased water stress, increased cases of human and crop disease, low fish count and, damage to household properties. The result further revealed that majority of households adopted short term mechanisms to cope with climate change. The study recommends a need for the policy makers to address emerging extreme climate events through a policy framework. The study also recommends a comprehensive climate change action plan at national, county, and local levels which is more focused on rural households. Climate-Smart Agriculture and Integrated Water Use and Management are among the projects recommended for the Lake Victoria Basin of Kenya.