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

dc.contributor.authorMasinde, Muthoni
dc.contributor.authorMwagha, Mwanjele
dc.contributor.authorTadesse, Tsegaye
dc.date.accessioned2019-08-14T08:42:22Z
dc.date.available2019-08-14T08:42:22Z
dc.date.issued2018-04-16
dc.descriptionPublished Articleen_US
dc.description.abstractIn 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.identifier.otherdoi:10.3390/geosciences8040135
dc.identifier.urihttp://hdl.handle.net/11462/1986
dc.language.isoenen_US
dc.publisherGeosciencesen_US
dc.relation.ispartofseriesGeosciences 2018, 8(4), 135;;
dc.subjectFuzzy cognitive maps (FCM)en_US
dc.subjectIndigenous knowledgeen_US
dc.subjectDrought early warning systemen_US
dc.subjectSeasonal climate forecastsen_US
dc.subjectSub-Saharan Africaen_US
dc.titleDownscaling Africa’s Drought Forecasts through Integration of Indigenous and Scientific Drought Forecasts Using Fuzzy Cognitive Mapsen_US
dc.typeArticleen_US

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