Original Research

Integrated drought monitoring framework for Eswatini applying standardised precipitation index and normalised difference vegetation index

Daniel H. Mlenga, Andries J. Jordaan
Jàmbá: Journal of Disaster Risk Studies | Vol 12, No 1 | a749 | DOI: https://doi.org/10.4102/jamba.v12i1.749 | © 2020 Daniel H. Mlenga | This work is licensed under CC Attribution 4.0
Submitted: 12 September 2018 | Published: 14 December 2020

About the author(s)

Daniel H. Mlenga, Disaster Management Training and Education Centre for Africa, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein, South Africa
Andries J. Jordaan, Disaster Management Training and Education Centre for Africa, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein, South Africa


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Abstract

In the last decade, Eswatini has been affected by moderate to severe droughts, leading to huge impacts on the economic, environmental and societal sectors. The frequency and magnitude of drought have also increased, emphasising on the importance of drought monitoring. In view of the impacts of drought, it is of critical importance to monitor drought in near real-time and provide early warning information to stakeholders. The challenge however is the fragmentation of climatic data collection, the lack of agreed indicators and the poor coordination amongst institutions resulting in drought management being reactive, or ‘crisis management’ approach. A paradigm shift to a more risk reduction approach is therefore required to enable cost-effective and timely response to drought disasters. The capacity to monitor and predict the drought attributes (onset, frequency, duration and severity) is fundamental for spatiotemporal (drought) monitoring. Based on a review of country and regional networks, this research developed an integrated drought monitoring and early warning framework for Eswatini. The framework incorporated an early warning response trigger threshold derived from an integration of the standardised precipitation index and normalised difference vegetation index. The adoption of the framework allows for early warning and early action to mitigate the consequences of drought disasters. Drought preparedness and risk mitigation will help lower the eventual drought relief costs, protect food security and reduce the humanitarian impact on the population.

Keywords

coordination; drought; drought monitoring; early warning; normalised difference vegetation index; preparedness; standard precipitation index.

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