Abstract:
In the ASAL part of West Pokot County the growing season for agricultural activities occurs during the peak rainfall season, during March, April and May (MAM) season. This study thus sought to quantify MAM rainfall variability and its associated impacts on the livelihoods of smallholder farmers in Senetwo location where the study was conducted. This was achieved by analyzing daily rainfall data from 1983 to 2013 and household survey. Using data from a survey of 125 farm households, the most common adaptation strategies used by most households include: use of soil and water conservation techniques (67.2%), changing planting dates (67.2%), use of commercial fertilizers (66.2%) and use of fast growing crop varieties (82.4%). Despite these initiatives, Senetwo location is largely characterized by limited use of climate forecast information (22%), limited support from the government and Non-Governmental Organizations (NGOs) (15.2%), low involvement in off-farm activities (16.8%) and low literacy levels (50% with at least primary education). Multivariate Logit regression model revealed that access to agricultural extension service (0.302; p≤0.01), large farms (0.341; p≤0.1), access to climate change information (0.326; p≤0.05), access to credit (0.311; p≤0.01) and perceived change in temperature (0.117; p≤0.1) have positive and significant impact on adaptation to climate variability. Annual rainfall trend between 1983 to 2013 show that in the MAM season rainfall has increased in Senetwo location with mean rainfall increasing from 203.2mm during the 1983 to 1992 decade to 346.1mm during the 2003 to 2013 period; a condition suitable for the good subsistence agricultural performance. On the contrary, the smallholder farmers of the location occasionally suffer heavy economic and resources loss due to unprecedented adverse variability in weather conditions. In conclusion, the livelihoods of smallholder farmers in Senetwo have been negatively impacted on by the alteration of rainfall performance, thus the current coping strategies are inadequate. However, there is need to invest and support weather observing infrastructure locally and continuously collect data so as to be able to generate accurate weather prediction models that can be customized, improved and utilized by smallholder farmers in ASALs elsewhere.
