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• W2082761320 abstract "Inter-annual climate variability is a major source of production risks in rainfed agriculture in semi-arid areas of Zimbabwe. Despite advances in seasonal forecasting since the late 1990s, there is hardly any evidence of explicit use of forecasts by vulnerable smallholder farmers to manage climate-related risk in agriculture. Forecasts are presented in the language of probabilities, but are often not perceived as such, partly because of differences in end users' needs and their decision-making behaviour. The project used the Indian Ocean Dipole (IOD) index and El Niño–Southern Oscillation (ENSO) to develop a tailored seasonal forecast model termed the ‘binary’ or ‘drought/no drought’. The binary forecast model addresses farmers most important question: what is the probability of drought (SPI ≤−1) occurring in the crop growing season? The ‘binary’ forecast system allowed the development of climate risk management strategies specifically tailored to farmers' needs. From this study, it can be concluded that rainfed agriculture production systems are most concerned about the risk of drought. A tailored forecast system that provides information on the probability of drought occurring in a given season can therefore lead to proactive drought risk management among smallholder farmers and policy-makers." @default.
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• W2082761320 date "2013-04-01" @default.
• W2082761320 modified "2023-09-25" @default.
• W2082761320 title "Tailoring seasonal climate forecasts for climate risk management in rainfed farming systems of southeast Zimbabwe" @default.
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• W2082761320 doi "https://doi.org/10.1080/17565529.2013.801823" @default.
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