17 Jun 2022
17 Jun 2022

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

Marleen R. Lam1, Alessia Matanó2, Anne F. Van Loon2, Rhoda Odongo2, Aklilu D. Teklesadik3, Charles N. Wamucii1, Marc J. C. van den Homberg3, Shamton Waruru4, and Adriaan J. Teuling1 Marleen R. Lam et al.
  • 1Hydrology and Quantitative Water Management (HWM), Wageningen University & Research (WUR), Wageningen, the Netherlands
  • 2Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
  • 3510, an initiative of the Netherlands Red Cross, Anna van Saksenlaan 50, 2593 HT Den Haag, the Netherlands
  • 4National Drought Management Authority (NDMA), Lonrho House, 8th Floor, Standard Street, P.O Box 10304, G.P.O. 00100 Nairobi, Kenya

Abstract. The relation between drought severity, as expressed through widely used drought indices, and drought impacts is complex. In particular in water-limited regions where water scarcity is prevalent, the attribution of drought impacts is difficult. This study assesses the relation between reported drought impacts, drought indices, water scarcity, and aridity across several counties in Kenya. The monthly bulletins of the National Drought Management Authority in Kenya have been used to gather drought impact data. A Random Forest (RF) model was used to explore which set of drought indices best explains drought impacts on: pasture, livestock deaths, milk production, crop losses, food insecurity, trekking distance for water, and malnutrition. The findings of this study suggest a relation between drought severity and the frequency of drought impacts, whereby the latter also showed a relation with aridity, whilst water scarcity did not. The results of the RF model reveal that drought impacts can be explained by a range of drought indices across regions with different aridity. While the findings strongly depend on the availability of drought impact data and the socio-economic circumstances within a region, this study highlights the potential of linking drought indices with text-based impact reports. In doing so, however, spatial differences in aridity and water scarcity conditions have to be taken into account.

Marleen R. Lam et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-458', Paolo Tasseron, 17 Aug 2022
  • RC1: 'Review of Lam et al. (2022): Linking reported drought impacts with drought indices, water scarcity, and aridity: the case of Kenya', Anonymous Referee #1, 25 Nov 2022
  • RC2: 'Comment on egusphere-2022-458', Anonymous Referee #2, 28 Nov 2022

Marleen R. Lam et al.

Marleen R. Lam et al.


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Short summary
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 their 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.