Developing a new socio-economic drought index for monitoring drought proliferation: a case study of Upper Ewaso Ngiro River Basin in Kenya

Abstract

The study focused on developing a novel socio-economic drought index (SeDI) for monitoring the severity of drought in a dry basin ecosystem dominated by nomadic pastoralists. The study utilized the domestic water deficit index, bareness index, normalized difference vegetation index, and water accessibility index as the input variables. An ensembled stochastic framework that coupled the 3D Euclidean feature space algorithm, least-squares adjustment, and iteration was used to derive the new SeDI. This approach minimized the uncertainties propagated by the stochastic nature of the input variables that has been a major bottleneck exhibited by the existing models. The regression analyses between the simulated SeDI and the observed ground river discharge registered a correlation coefficient (r) of −0.84 and a p-value of 0.02, while the correlation between the Hull’s score–derived SeDI and ground river discharge registered a correlation coefficient (r) of −0.75 and a p-value of 0.05. The assessment revealed that the newly derived SeDI was more sensitive to the river discharge than the Hull’s score–derived SeDI. The SeDI’s classification results for the period between 1986 and 2018 revealed that only January 2009 manifested a significant slight severity level covering about 12.4% of the basin. Additionally, the results indicated that the basin exhibited a moderate severity level ranging between 85 and 96%, a severe level ranging between 2.2 and 13.3%, and an extreme level ranging between 0.73 and 1.17%. The derived SeDI would serve as an early warning tool necessary for increasing the resilience to climate-related risks and offer support in reducing the loss of life and livelihood.