Next Article in Journal
Geoheritage, Geotourism and the Cultural Landscape: Enhancing the Visitor Experience and Promoting Geoconservation
Previous Article in Journal
Effects of pH-Induced Changes in Soil Physical Characteristics on the Development of Soil Water Erosion
Previous Article in Special Issue
Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP) Satellite
Open AccessArticle

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

1
Unit for Research on Informatics for Droughts (URIDA), Central University of Technology, Free State, Private Bag X20539, Bloemfontein 9300, South Africa
2
National Drought Mitigation Center, School of Natural Resources (SNR), University of Nebraska-Lincoln, 815 Hardin Hall, 3310 Holdrege St., Lincoln, NE 68583, USA
*
Author to whom correspondence should be addressed.
Geosciences 2018, 8(4), 135; https://doi.org/10.3390/geosciences8040135
Received: 25 November 2017 / Revised: 25 March 2018 / Accepted: 9 April 2018 / Published: 16 April 2018
(This article belongs to the Special Issue Drought Monitoring and Prediction)
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. View Full-Text
Keywords: fuzzy cognitive maps (FCM); indigenous knowledge; drought early warning system; seasonal climate forecasts; sub-Saharan Africa fuzzy cognitive maps (FCM); indigenous knowledge; drought early warning system; seasonal climate forecasts; sub-Saharan Africa
Show Figures

Figure 1

MDPI and ACS Style

Masinde, M.; Mwagha, M.; Tadesse, T. Downscaling Africa’s Drought Forecasts through Integration of Indigenous and Scientific Drought Forecasts Using Fuzzy Cognitive Maps. Geosciences 2018, 8, 135.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop