Indigenous knowledge systems for local weather predictions: A case of Mukonchi chiefdom in Zambia select="/dri:document/dri:meta/dri:pageMeta/dri:metadata[@element='title']/node()"/>

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dc.contributor.author Mbewe, Mabvuto
dc.date.accessioned 2021-08-06T06:40:46Z
dc.date.available 2021-08-06T06:40:46Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/11070/3048
dc.description.abstract The purpose of the study was to unravel constituents of the indigenous knowledge systems (IKS) and appreciate people’s experiences in predicting the weather in daily undertakings. The objectives of the study were; to identify factors or systems used, establish the knowledge used in predicting the weather and compare the indigenous and current scientific method of predicting the weather. Qualitative and quantitative research designs were used. Primary data was collected through semi structured, face-to-face and in-depth interviews. This was complemented by secondary data collected through desk reviews of relevant published materials. The findings reveal that indigenous knowledge systems have been employed by people of Mukonchi chiefdom since time immemorial. There has also been reliance on IKS to make decisions pertaining to livelihoods such as agricultural activities. However, IKS in the area remains undocumented. Observation of several occurrences in combination or singularly relating to plants, animals, insects, and astronomical events were factors of significant importance in the knowledge of weather extrapolation. Elements such as age, frequency of use of the IKS, and level of education were seen to be of momentous prominence in utilisation of the indigenous knowledge as modern means of weather forecasting which are applicable to the local community environment. en_US
dc.language.iso en en_US
dc.subject Weather Knowledge en_US
dc.subject Climate Systems en_US
dc.subject Forecasting en_US
dc.subject Indigenous en_US
dc.title Indigenous knowledge systems for local weather predictions: A case of Mukonchi chiefdom in Zambia en_US
dc.type Article en_US


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