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Downscaling Africa’s Drought Forecasts through Integration of Indigenous and Scientific Drought Forecasts Using Fuzzy Cognitive Maps

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dc.contributor.author Masinde, Muthoni
dc.contributor.author Mwagha, Mwanjele
dc.contributor.author Tadesse, Tsegaye
dc.date.accessioned 2019-08-14T08:42:22Z
dc.date.available 2019-08-14T08:42:22Z
dc.date.issued 2018-04-16
dc.identifier.other doi:10.3390/geosciences8040135
dc.identifier.uri http://hdl.handle.net/11462/1986
dc.description Published Article en_US
dc.description.abstract In the wake of increased drought occurrences being witnessed in Sub-Saharan Africa, more localized and contextualized drought mitigation strategies are on the agendas of many researchers and policy makers in the region. The integration of indigenous knowledge on droughts with seasonal climate forecasts is one such strategy. The main challenge facing this integration, however, is the formal representation of highly-structured and holistic indigenous knowledge. In this paper, we demonstrate how the use of fuzzy cognitive mapping can address this challenge. Indigenous knowledge on droughts from five communities was modeled and represented using fuzzy cognitive maps. Maps from one of these case communities were then used in the implementation of the integration framework, called itiki. en_US
dc.language.iso en en_US
dc.publisher Geosciences en_US
dc.relation.ispartofseries Geosciences 2018, 8(4), 135;;
dc.subject Fuzzy cognitive maps (FCM) en_US
dc.subject Indigenous knowledge en_US
dc.subject Drought early warning system en_US
dc.subject Seasonal climate forecasts en_US
dc.subject Sub-Saharan Africa en_US
dc.title Downscaling Africa’s Drought Forecasts through Integration of Indigenous and Scientific Drought Forecasts Using Fuzzy Cognitive Maps en_US
dc.type Article en_US


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