Articles | Volume 23, issue 9
https://doi.org/10.5194/nhess-23-2915-2023
https://doi.org/10.5194/nhess-23-2915-2023
Research article
 | 
01 Sep 2023
Research article |  | 01 Sep 2023

Linking reported drought impacts with drought indices, water scarcity and aridity: the case of Kenya

Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling

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Atzberger, C. and Eilers, P. H.: Evaluating the effectiveness of smoothing algorithms in the absence of ground reference measurements, Int. J. Remote Sens., 32, 3689–3709, https://doi.org/10.1080/01431161003762405, 2011. a
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Bachmair, S., Svensson, C., Hannaford, J., Barker, L. J., and Stahl, K.: A quantitative analysis to objectively appraise drought indicators and model drought impacts, Hydrol. Earth Syst. Sci., 20, 2589–2609, https://doi.org/10.5194/hess-20-2589-2016, 2016. a, b, c, d, e, f, g, h, i
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There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
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