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

Authors

Muthoni Masinde, Central University of TechnologyFollow
Mwanjele Mwagha, Central University of TechnologyFollow
Tsegaye Tadesse, University of Nebraska-LincolnFollow

ORCID IDs

https://orcid.org/0000-0002-8914-0055

https://orcid.org/0000-0002-4102-1137

Document Type

Article

Date of this Version

4-16-2018

Citation

2018 by the authors

Comments

Geosciences 2018, 8, 135; doi:10.3390/geosciences8040135 www.mdpi.com/journal/geosciences

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.