Integrating Local Farmers Knowledge Systems in Rainfall Prediction and Available Weather Forecasts to Mitigate Climate Variability: Perspectives from Western Kenya

This chapter examines relevant studies and examples on integrating farmer's traditional knowledge systems in rainfall prediction with available weather forecasts to mitigate impact of changing climate among rainfall dependent farmers in Western Kenya. The chapter combines the results of a study conducted in Western Kenya among maize and wheat growing farmers in Uasin Gishu County and perspectives from other related studies within the Eastern and Southern part of Africa. The chapter details how farmers have navigated the impact of changing climate on the farming enterprise that is largely dependent on rainfall. The findings reveal that farmers in western Kenya have experienced crop losses during planting and harvesting seasons due to prevailing variations in weather patterns. This is corroborated by over 340 (87.8%) of farmers in Uasin Gishu county of Kenya who agreed so and further stated that they had experienced changes in rainfall patterns and even the timing for maize and wheat growing had become uncertain and contrary to what they have known over time in the recent years. Similarly, like other findings in the reviewed studies in this chapter, the Kenyan farmers (84.9%) agreed strongly that they applied their local indigenous knowledge and experience gained over time to predict rainfall onset and cessation dates thus making key farming decisions. Relying heavily on traditional weather forecasting by farmers is catastrophic now due to changes on the environment associated to environmental degradation; ecosystem disturbance and changing climate which have seen important traditional predictor indicators disappear or lost completely from the environment. Although over 90% of the Kenyan farmers in average belief in use of weather forecast information, integration of this information is not effective because of its adaptability, format and timing challenges. The same is true for farmers in some countries within the region. Importantly, provision of context-specific and downscaled weather forecast information to support farmer's resilience is crucial. Most studies and programmes reviewed in this chapter agree that there is synergy in integrating local knowledge systems and available weather forecast information for better weather prediction. It is critical that policymakers, practitioners or key stakeholders and forecasters (both from the meteorological services and indigenous groups) converge and agree on weather prediction if they are to support farmers in managing climate risk or uncertainties.