Evaluation of a Combined Index Based on Hydrological Model for Drought Monitoring in Central Iran

In recent years, drought has become a global problem. Undoubtedly, drought monitoring is an important step for combating and reducing the resultant damage. Soil moisture, namely its spatial and temporal variability, is one of the most important environmental variables. Due to the difficulty cost, and timeliness of field measurements, this parameter has not been used widely in drought indexes. The recent development of global databases based on satellite imagery as well as rapid progress in hardware and software for modeling complex processes governing the water balance at the land surface employ these new tools to reduce the limitations in this field. The purpose of this research is to provide a comprehensive drought monitoring approach by integrating remote sensing data and the variable infiltration capacity (VIC) model with the Palmer Index (PDSI) in central Iran. In this study, the components of water and energy balance in the Central Iran region were simulated using the VIC land surface model. The output components of this model, especially soil moisture after evaluation, were used as inputs in the drought index based on Palmer's water balance. The integrated index of the VIC-PDSI in comparison with conventional Palmer indices and the SPI index at the 3, 6, 12, 24, and 48-month intervals was fitted with increments in moisture data and variations in the storage of water extracted from GRACE satellite data. Results showed that the combination of VIC-PDSI had the highest correlation coefficient of 0.87 with groundwater level change compared with other drought indices.