Drought Vulnerability Assessment Based on a Multi-criteria Integrated Approach and Application of Satellite-based Datasets

Drought as a complex event depends on some geo-environmental parameters. The impact of this phenomenon on the economy and environment can be devastating. Recognizing drought-prone regions is essential for planning and adopting mitigation measures. This study focused on introducing a multiscale method based on the satellite datasets to assess drought vulnerability in non-gage areas. In this regard, two steps were considered and drought monitoring was done for the northwest part of Iran as the study area. In the first step, vulnerable areas were identified using multi-criteria-kernel-based techniques which integrated 17 geo-environmental parameters extracted from the in-situ observations and satellite datasets to develop drought vulnerability map. The considered models were evaluated via different metrics and most important variables were determined by performing sensitivity analysis. Results indicated that the south and central parts of the selected area were more prone to severe droughts. Among the used variables, soil moisture, precipitation, evaporation, humidity, and vegetation condition were the most effective parameters. In the second step, due to limitations of the in-situ observations, drought-prone areas were identified using only precipitation, vegetation condition, and land surface temperature variables extracted from the satellites. For this aim, a new multi-scale method was developed based on the Wavelet Transform (WT), Variational Mode Decomposition (VMD), Permutation Entropy (HPE), and kernel-based methods. The obtained results showed the appropriate efficiency of the proposed multiscale method in identifying drought-prone areas with different intensity.