Water Security

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Browsing Water Security by Subject "University Of Embu"

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  • Publication
    Publication
    Indigenous and conventional climate-knowledge for enhanced farmers' adaptation to climate variability in the semi-arid agro-ecologies of Kenya
    (Meru University of Science and Technology, 2021) Mugi-Ngenga, E. W.; Kiboi, M. N.; Mucheru-Muna, M. W.; Mugwe, J. N.; Mairura, F. S.; Mugendi, D. N.; Ngetich, F. K.
    Climate variability is among the main threats to rain-dependent smallholder farming in most sub-Saharan Africa countries. Hence, farmers should make efforts at the local level to utilize indigenous knowledge (IK) combined with conventional knowledge to adapt to climate variability impacts. We assessed; IK used by farmers in climate forecasting, their perceptions of climate variability and adaptation strategies, and their correlation with conventional approaches. We conducted the study in Tharaka South and Kitui Central sub-counties of Kenya. We used the triangulation approach to obtain the quantitative and qualitative data. To select respondents, we used purposive and random sampling strategies combined with the snowballing technique. Observed rainfall and temperature data from 1998 to 2018 were obtained from the Kenya Meteorological Department (KMD). Results showed that there were significant (p<0.05) differences in the use of indigenous indicators such as observation of the behavior of the sky (χ2 = 14.631), moon (χ2 = 7.851), and wind (χ2 = 5.864). The majority of the smallholder farmers (87%) used the change in the behavior of trees as the indigenous indicator in weather forecasting. The most common adaptation strategies (over 80%) used were food storage for future use (88.5%) and change of planting dates (87.5%). The analysis output of conventional data from KMD conformed with the farmers' observations and perception of climate variability over the reference period. Because farmers are still using IK that agrees with conventional knowledge, there is a need to integrate IK with conventional knowledge for use by rain-fed-dependent smallholder farmers in climate forecasting.
  • Publication
    Publication
    Suitability of different data sources in rainfall pattern characterization in the tropical central highlands of Kenya
    (Heliyon, 2020) Nathan, Oduor O.; Felix, Ngetich K.; Milka, Kiboi N.; Anne, Muriuki; Noah, Adamtey; Daniel, Mugendi N.
    Uncertainty in rainfall pattern has put rain-fed agriculture in jeopardy, even for the regions considered high rainfall potential like the Central Highlands of Kenya (CHK). The rainfall pattern in the CHK is spatially and temporally variable in terms of onset and cessation dates, frequency and occurrence of dry spells, and seasonal distribution. Appraisal of the variability is further confounded by the lack of sufficient observational data that can enable accurate characterisation of the rainfall pattern in the region. We, therefore, explored the utilisation of satellite daily rainfall estimates from the National Aeronautics and Space Administration (NASA) for rainfall pattern characterisation in the CHK. Observed daily rainfall data sourced from Kenya meteorological department were used as a reference point. The observation period was from 1997 to 2015. Rainfall in the CHK was highly variable, fairly distributed and with low intensity in all the seasons. Onset dates ranged between mid-February to mid-March and mid-August to mid-October for long rains (LR) and short rains (SR) seasons, respectively. Cessation dates ranged from late May to mid-June and mid-December to late December for the LR and SR, respectively. There was a high probability (93%) of dry spell occurrence. More research needs to be done on efficient use of the available soil moisture and on drought tolerant crop varieties to reduce the impact of drought on crop productivity. Comparison between satellite and observed rain gauge data showed close agreement at monthly scale than at daily scale, with general agreement between the two datasets. Hence, we concluded that, given the availability, accessibility, frequency of estimation and spatial resolution, satellite estimates can complement observed rain gauge data. Stakeholders in the fields of agriculture, natural resource management, environment among others, can utilise the findings of this study in planning to reduce rainfall-related risks and enhance food security.