The Role of Indigenous Knowledge in Climate-Smart Agriculture: A Case Study of Weather Forecasting in Uganda
Abstract
Climate change is exacerbating rainfall unpredictability across Sub-Saharan Africa, threatening the livelihoods of millions of smallholder farmers who depend on rain-fed agriculture. While modern climate services are often promoted as the primary adaptation strategy, they frequently prove unreliable at the local level and inaccessible to resource-poor farmers. This study investigates the role of indigenous knowledge (IK) in weather forecasting among smallholder farmers in Uganda's Bukedi sub-region, drawing on qualitative data from 30 in-depth interviews, 10 focus group discussions (80 participants), and six weeks of participant observation across five villages. The findings reveal that weather forecasting is the most universally practiced IK category, reported in 100% of focus groups, with farmers employing a sophisticated typology of at least eleven distinct indicators spanning biological, meteorological, celestial, botanical and edaphic categories. Four core indicators, migratory birds, bird calls/behavior, dark clouds, wind direction, and tree flowering, were reported in all five villages, representing a foundational knowledge system. Farmers consistently expressed a preference for traditional forecasting over modern radio forecasts, citing superior local accuracy, accessibility, and cost-effectiveness. This paper challenges the prevailing epistemic hierarchy that privileges scientific knowledge over local knowledge, arguing that IK-based weather forecasting represents a vital, locally adapted, and cost-free climate adaptation strategy that merits systematic integration into agricultural policy and extension services. The findings contribute to the growing literature on climate-smart agriculture by demonstrating how indigenous knowledge systems can enhance resilience at the community level.
Keywords: Indigenous knowledge, weather forecasting, climate adaptation, smallholder farmers, Uganda, climate-smart agriculture
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