Abstract
Forecasting rainfall at the local scale to inform farm-level decisions is complex and it remains an unresolved problem with dire implications for food security. Here, we examine indigenous knowledge forecasting systems used by smallholder farmers in Maondo Agriculture Camp (MAC) of Sesheke District in the Western Province of Zambia to increase their climate change adaptive capacity at the farm level. We adopted a qualitative approach that uses an exploratory-descriptive design. We then used purposive sampling, a non-probability methodological approach, to choose respondents. We applied semi-structured interviews and questionnaires as data collection tools and examined the data using thematic content analysis. We found that > 50% of small-scale farmers receive forecasts produced by the Zambia Meteorological Department (ZMD) through stakeholders’ meetings. Farmers who do not receive ZMD forecasts depend on indigenous knowledge systems. Results further indicate that farmers in the MAC combine several indicators to predict rainfall. Prominent among them include plants, weather-related parameters, and astrological indicators. A cursory inspection of these rainfall predictors revealed several points specifically highlighting three salient thematic contents, i.e. biological, meteorological, and astrological. Results further showed that both conventional science and indigenous knowledge used to forecast rainfall have strengths and weaknesses. We, therefore, conclude that the integration of the two methods has the potential to significantly improve rainfall forecasts and ultimately agricultural productivity at the farm level.
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Acknowledgements
The first author carried out this study while being supported by the ZMD/UNDP CIEWS Project, their financial support is appreciated. The work embodied herein would not have been possible without Respondents in Maondo Agriculture Camp (MAC) and Mr Sabelo Mwanakalanga Sibanda who assisted with data collection — thank you. Mr Alfred Daka, a lecturer in the School of Agriculture and Natural Resources at Mulungushi University, is also appreciated for providing feedback on the initial draft of this manuscript. The Editor and Reviewers are also appreciated for their comments that further helped to improve this work.
Funding
This research was carried out as part of the Strengthening Climate Information and Early Warning Systems project (CIEWS; Project Number 00086729; https://www.adaptation-undp.org/projects/ldcf-ews-zambia) funded by the United Nations Development Programme (UNDP). The project was led by the Zambia Meteorological Department (ZMD). Overall, the project aimed at enhancing the capacity of ZMD to monitor and forecast extreme weather events and climate change. It also sought to maximise efficient and effective use of hydro-meteorological and environmental information for generating early warnings and informing long-term development plans. It should be noted, however, that neither UNDP nor ZMD were involved in the conception, analytical design, data analyses, interpretation of the data, manuscript writing, or the decision to submit this work for publication.
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The first author developed the theoretical formalism and led the data collection, analyses, and manuscript writing. The second author contributed to the presentation of the storyline and results. Both MM and BL contributed equally to the final version of the manuscript.
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While the first author works for ZMD, we declare that the author was not solely responsible for the interpretation of results embodied in this work and therefore, this has not in any way affected the conclusions herein.
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Mushimbei, M., Libanda, B. Adapting to a changing climate: indigenous biotic rainfall forecasting in Western Zambia. Int J Biometeorol 67, 253–263 (2023). https://doi.org/10.1007/s00484-022-02402-2
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DOI: https://doi.org/10.1007/s00484-022-02402-2