Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices

Abstract

Karamoja is notoriously food insecure and has been in need of food aid for most years during the last two decades. One of the main factors causing food insecurity is drought. Reliable, area-wide, long-term data for detecting and monitoring drought conditions are critical for timely, life-saving interventions and the long-term development of the region, yet such data are sparse or unavailable. Due to advances in satellite remote sensing, characterizing drought in data-sparse regions like Karamoja has become possible. This study characterizes agricultural drought in Karamoja to enable a comprehensive understanding of drought, concomitantly evaluating the suitability of NDVI-based drought monitoring. We found that in comparison with the existing data, NDVI data currently provide the best, consistent, and spatially explicit information for operational drought monitoring in Karamoja. Results indicate that the most extreme agricultural drought in recent years occurred in 2009 followed by 2004 and 2002 and suggest that in Karamoja, moderate to severe droughts (e.g., 2008) often have the same impact on crops and human needs (e.g., food aid) as extreme droughts (e.g., 2009). We present in a proof-of-concept frame, a method to estimate the number of people needing food assistance and the population likely to fall under the integrated food security phase classification (IPC) Phase 3 (crisis) due to drought severity. Our model indicates that 90.7% of the variation in the number of people needing aid can be explained by NDVI data and NDVI data can augment these estimates. We conclude that the biggest drivers of food insecurity are the cultivation of crops on marginal land with insignificant inputs, the lack of irrigation and previous systematic incapacitation of livestock (pastoral) alternatives through government programming. Further research is needed to bridge empirical results with social–economic studies on drought impacts on communities in the region to better understand additional factors that will need to be addressed to ensure livelihood resilience.

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[Rainfall data source: Hijmans et al. (2005)]

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[Reproduced with permission from McKee et al. (1993)]

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Notes

  1. 1.

    Data for September to December 1991, May to December 1997, and January to April 2006 were incomplete.

  2. 2.

    More information available at http://modis-land.gsfc.nasa.gov/vi.html.

  3. 3.

    For information about the NextView License, please visit: http://cad4nasa.gsfc.nasa.gov/.

  4. 4.

    For more information visit http://www.ipcinfo.org/.

  5. 5.

    Estimated from UBOS 2016 population projection.

  6. 6.

    As per NUSAF 3 Disaster Risk Financing Handbook.

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Acknowledgements

I would like to thank Dr. Christopher Justice, Professor, Department of the Geographical Sciences University of Maryland for his guidance during this research, and his invaluable comments on earlier versions of this manuscript. I would also like to thank anonymous reviewers for the comments on previous versions of this paper.

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Correspondence to Catherine Nakalembe.

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Nakalembe, C. Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices. Nat Hazards 91, 837–862 (2018). https://doi.org/10.1007/s11069-017-3106-x

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Keywords

  • Agricultural drought
  • NDVI
  • SPI
  • Remote sensing
  • Karamoja
  • East Africa