Development of a new composite drought index for multivariate drought assessment

Abstract

Summary Comprehensibly considering all physical forms of agricultural, hydrological, and meteorological drought is essential to develop reliable monitoring and prediction indices for the proper assessment of drought. This consideration encouraged to develop and evaluate a multivariate composite drought index (CDI) that considers all possible variables related to individual types of drought. The proposed CDI was primarily based on the weighted similarity measure (entropy weighted Euclidian distance) and the anomaly from the possible wettest and driest conditions of the selected study region (sub basin of Han River, South Korea). The CDI time series identified 2008–2009 as the driest year, while May 2008 was the driest month within the selected period (2003–2011). The comparative analysis revealed that the CDI monthly time series had a significant correlation with the aggregate drought index (ADI). In addition, in comparison with the single variable-based indices i.e., the standardized precipitation index (SPI) and the streamflow drought index (SDI), the CDI comprehensively responded to variability embedded in the individual drought attributes. Moreover, it was concluded that the developed CDI provided a physically sound, temporally flexible and unbiased index that can be directly associated with all possible variants and linked to the climate conditions of the study region without considering any feature extraction technique.