A joint probabilistic index for objective drought identification: the case study of Haiti

Since drought is a multifaceted phenomenon, more than one variable should be considered for a proper understanding of such an extreme event in order to implement adequate risk mitigation strategies such as weather or agricultural indices insurance programmes or disaster risk financing tools. This paper proposes a new composite drought index that accounts for both meteorological and agricultural drought conditions by combining in a probabilistic framework two consolidated drought indices: the standardized precipitation index (SPI) and the vegetation health index (VHI). The new index, called the probabilistic precipitation vegetation index (PPVI), is scalable, transferable all over the globe and can be updated in near real time. Furthermore, it is a remote-sensing product, since precipitation is retrieved from satellite data and the VHI is a remote-sensing index. In addition, a set of rules to objectively identify drought events is developed and implemented. Both the index and the set of rules have been applied to Haiti. The performance of the PPVI has been evaluated by means of a receiver operating characteristic curve and compared to that of the SPI and VHI considered separately. The new index outperformed SPI and VHI both in drought identification and characterization, thus revealing potential for an effective implementation within drought early-warning systems.