Meteorological and agricultural drought monitoring in Southwest of Iran using a remote sensing-based combined drought index

Drought is one of the most devastating natural hazards in the world, affecting millions of individuals in in different ways, so it's better monitoring and comprehensive assessment is important. Univariate or multivariate drought indices are able to monitor one type of drought and can not reflect comprehensive drought information from meteorological to agricultural aspects. For this purpose, by combining the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), the Soil Water Index (SWI) and the precipitation condition index (PCI) a comprehensive drought index called Combined Drought Index (CDI) was proposed. In this study, meteorological and agricultural droughts from 2001 to 1397 in Karkheh Basin in southwestern Iran were monitored. The Principal Component Analysis (PCA) method, which is a mainstay of modern data analysis tools for constructing a composite index, was applied to a data matrix that contains the time series of the computed PCI, VCI, TCI, and SWI indices for a given location, and the first leading component of the PCA was introduced as CDI index. The results indicated that the highest correlation (r = 0.53, r = 0.56) between the CDI, SPI-1 and SDI was observed respectively, which indicates the ability of this index for drought comprehensive monitoring. It is also suggested that in order to improve the performance of the CDI, in addition to the considered parameters in this study, other factors affecting the performance of each of the remote sensing indicators such as vegetation type, plant root, soil texture type, evaporation and Transpiration also be considered in future studies.