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 ĩtiki.
Highlights
Africa continues to be the highest hit by global droughts as well as having the most deaths resulting from these droughts
The integration framework was realized in the form of a three-layered drought early warning system prototype: a drought knowledge capture layer, a drought monitoring and predication layer and drought forecast dissemination and communication
The indigenous knowledge used to generate Fuzzy cognitive mapping (FCM) maps was collected through case studies of five communities in Kenya, Mozambique and South Africa
Summary
Africa continues to be the highest hit by global droughts as well as having the most deaths resulting from these droughts. What is more striking is the fact that the 118 droughts (50% of the all droughts) in Africa led to over 99% (20,078 out of 20,251) of the total deaths resulting from the world’s droughts occurring in the same period (2006–2015). DEWS, in turn, require provision and access to timely and reliable climate information [1]. When it comes to Sub-Saharan Africa, there is a complex link between droughts and economic development (or lack of it). In most of these countries, rain-fed agriculture (extremely responsive to climate variability) accounts for over 70% of food production [2]
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