Validating commonly used drought indicators in Kenya. (10th August 2021)

• Record Type: Journal Article
• Authors: Bowell, Andrew; Salakpi, Edward E; Guigma, Kiswendsida; Muthoka, James M; Mwangi, John; Rowhani, Pedram
• Is Part Of: Environmental research letters. Volume 16:Number 8(2021)
• Publication Date: 2021-08-10
• Subjects: NDVI -- VCI -- Earth Observation -- Food Security -- Early Warning Systems; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/ac16a2
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Drought is a complex natural hazard that can occur in any climate and affect every aspect of society. To better prepare and mitigate the impacts of drought, various indicators can be applied to monitor and forecast its onset, intensity, and severity. Though widely used, little is known about the efficacy of these indicators which restricts their role in important decisions. Here, we provide the first validation of 11 commonly-used drought indicators by comparing them to pasture and browse condition data collected on the ground in Kenya. These ground-based data provide an absolute and relative assessment of the conditions, similar to some of the drought indicators. Focusing on grass and shrublands of the arid and semi-arid lands, we demonstrate there are strong relationships between ground-based pasture and browse conditions, and satellite-based drought indicators. The soil adjusted vegetation index has the best relationship, achieving a mean r 2 score of 0.70 when fitted against absolute pasture condition. Similarly, the 3-month vegetation health index reached a mean r 2 score of 0.62 when fitted against a relative pasture condition. In addition, we investigated the Kenya-wide drought onset threshold for the 3-month average vegetation condition index (VCI3M; VCI3M < 35), which is used by the country's drought early warning system. Our results show large disparities in thresholds across different counties. Understanding these relationships and thresholds are integral to developing effective and efficient drought early warning systems. Our work offers evidence for the effectiveness of some of these indicators as well as practical thresholds for their use.